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Sports Medicine (2022) 52:1491–1532
https://doi.org/10.1007/s40279-021-01626-3
SYSTEMATIC REVIEW
A Systematic Review onFitness Testing inAdult Male
Basketball Players: Tests Adopted, Characteristics Reported
andRecommendations forPractice
MatthewMorrison1· DavidT.Martin1· ScottTalpey2· AaronT.Scanlan3· JaceDelaney· ShonaL.Halson1,4·
JonathonWeakley1,4,5
Accepted: 8 December 2021 / Published online: 4 February 2022
© The Author(s) 2022
Abstract
Background As basketball match-play requires players to possess a wide range of physical characteristics, many tests have
been introduced in the literature to identify talent and quantify fitness in various samples of players. However, a synthesis
of the literature to identify the most frequently used tests, outcome variables, and normative values for basketball-related
physical characteristics in adult male basketball players is yet to be conducted.
Objective The primary objectives of this systematic review are to (1) identify tests and outcome variables used to assess
physical characteristics in adult male basketball players across all competition levels, (2) report a summary of anthropo-
metric, muscular power, linear speed, change-of-direction speed, agility, strength, anaerobic capacity, and aerobic capacity
in adult male basketball players based on playing position and competition level, and (3) introduce a framework outlining
recommended testing approaches to quantify physical characteristics in adult male basketball players.
Methods A systematic review of MEDLINE, PubMed, SPORTDiscus, Scopus, and Web of Science was performed follow-
ing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify relevant studies. To be
eligible for inclusion, studies were required to: (1) be original research articles; (2) be published in a peer-reviewed journal;
(3) have full-text versions available in the English language; and (4) include the primary aim of reporting tests used and/or
the physical characteristics of adult (i.e., ≥ 18years of age) male basketball players. Additionally, data from the top 10 draft
picks who participated in the National Basketball Association combined from 2011–12 to 2020–21 were extracted from the
official league website to highlight the physical characteristics of elite 19- to 24-year-old basketball players.
Results A total of 1684 studies were identified, with 375 being duplicates. Consequently, the titles and abstracts of 1309
studies were screened and 231 studies were eligible for full-text review. The reference list of each study was searched, with
a further 59 studies identified as eligible for review. After full-text screening, 137 studies identified tests, while 114 studies
reported physical characteristics in adult male basketball players.
Conclusions Physical characteristics reported indicate a wide range of abilities are present across playing competitions. The tests
and outcome variables reported in the literature highlight the multitude of tests currently being used. Because there are no accepted
international standards for physical assessment of basketball players, establishing normative data is challenging. Therefore,
future testing should involve repeatable protocols that are standardised and provide outcomes that can be monitored across time.
Recommendations for testing batteries in adult male basketball players are provided so improved interpretation of data can occur.
Clinical Trial Registration This review was registered with the International Prospective Register of Systematic Reviews and
allocated registration number CRD42020187151 on 28 April, 2020.
Extended author information available on the last page of the article
1 Introduction
Basketball has been reported by The Fédération Internation-
ale de Basketball (FIBA) as the second most popular sport
in the world [1]. The duration of a game varies depending
on the governing body or federation, level of competition, as
well as the age and sex of players [2]. However, the typical
format for adult male matches are two 20-min halves (e.g.,
National Collegiate Athletic Association [NCAA]), four
10-min quarters (e.g., FIBA match-play), or four 12-min
quarters (e.g., National Basketball Association [NBA])
[2]. Basketball is typically played on a wooden court with
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1492 M.Morrison et al.
Key Points
Success in basketball is predicated on players optimising
multiple basketball-specific skills, which are influenced
by many different physical characteristics. As a result,
numerous tests have been introduced for the purposes of
identifying talent and quantifying fitness across various
samples of adult male players.
The wide range of tests and outcome variables reported
in the literature illustrates the need to identify (a) physi-
cal characteristics that are most important for optimal
match performance and (b) the most suitable tests and
outcome variables for quantifying physical characteris-
tics of interest.
Tests that are most suitable to identify talent may differ
from tests that are most suitable for tracking changes in
fitness and fatigue
Future research should focus on developing standardised
testing batteries in conjunction with the International
Basketball Federation and national governing bodies
that contribute to meaningful normative data. A large
international data set will facilitate an understanding
of historical trends and allow basketball practitioners
to become familiar with minimum and desirable fitness
standards for their players.
movements at varied intensities while defending opposing
players [12] and must be able to quickly identify and respond
to the movements of opponents, challenging their agility, lat-
eral movement and acceleration capabilities [21]. Although
basketball is considered a non-collision sport, players will
often block, push, and compete for possession with one
another as they attempt to create and defend space on the
court. The complex nature of basketball match-play clearly
indicates the development of multiple physical characteris-
tics can be advantageous to optimise match performance.
However, it is important to be able to measure these physical
characteristics independently of skill as physical capacities
and skill often require different training stimuli to develop.
To assess the physical characteristics of basketball play-
ers, it is essential that tests are valid and reliable to ensure
basketball practitioners can use the data to make informed
decisions regarding training prescription, guiding return
to play processes following injury, quantifying individual
player progression, profiling and ranking players, and moni-
toring player performance and fatigue [22–26]. Researchers
and practitioners often implement a diverse combination
of tests that assess general physical characteristics (e.g.,
linear sprint speed) [4, 27, 28], as well as specialised tests
that integrate sport-specific skills aimed to replicate certain
basketball-specific demands (e.g., dribbling speed tests)
[29–31]. However, the wide variety of tests and methods
implemented can make it difficult to compare the physical
characteristics of adult male basketball players within and
between different competition levels. The array of available
testing options makes it difficult to understand the physi-
cal characteristics required for successful performance in
adult male basketball players. Therefore, to help support the
quantification and comparison of physical characteristics in
adult male basketball players, it is important to identify the
most important and desirable characteristics for match per-
formance and report the most common tests and outcome
variables used to assess the physical characteristics.
We are unaware of any study that has provided a com-
prehensive analysis of tests and outcome variables used to
assess the physical characteristics of adult male basketball
players across all playing levels and positions. While Ziv
and Lidor [32] reviewed the physical characteristics of pro-
fessional male and female basketball players, over a dec-
ade has passed since this review was published and sub-
stantial growth in the basketball literature science has since
occurred. Additionally, Mancha-Triguero etal. [33] reviewed
tests used to assess the physical characteristics of high-level
male and female players but the range of tests reported were
limited with outcome data from each test not provided. Con-
sequently, no review exists examining the tests used and the
physical characteristics reported in combination in adult
male basketball players from a range of competition levels.
Given the world-wide popularity of basketball, it is prudent
playing areas of 28.7m × 15.2m (NBA) or 28m × 15m
(FIBA). Basketball teams consist of up to 12 players per
team with five players competing for each team on the court
at any one time during matches. The traditional five on-court
playing positions include point guard, shooting guard, small
forward, power forward, and centre, which are often catego-
rised as backcourt (i.e. point guard and shooting guard) and
frontcourt players (i.e., small forward, power forward, and
centre) [3, 4].
The physical demands of a basketball game have been
readily investigated [5–14]. Given the intermittent nature
and varying positional demands involved in basketball
match-play, a range of well-developed physical characteris-
tics are thought to be required by basketball players [15–19].
During basketball matches, players are required to cover
distances between 4400 and 7500m, which consists pre-
dominantly of jogging, sprinting, jumping and changes in
direction [12]. While frequently reaching speeds in excess of
7m·s−1, professional backcourt and frontcourt players have
been reported to perform (mean ± standard deviation) 42 ± 6
and 56 ± 2 jumps per game, respectively [20]. Furthermore,
players of all positions are required to execute shuffling
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1493
Testing Methods and Physical Characteristics of Male Basketball Players
to review the tests used to quantify the physical character-
istics of adult male basketball players across different com-
petition levels. Due to the extensive evidence available on
male basketball players, it is important to consolidate the
current literature for basketball researchers and practitioners
alike to develop a clear understanding of current practices in
this population. A summary of basketball tests can support
basketball practitioners when making decisions based on
test results. Furthermore, larger samples of normative data
aggregated across studies can lead to comprehensive profil-
ing and benchmarking of important physical characteristics
in adult male basketball players. Therefore, the purpose of
this review is three-fold, (1) to identify tests and outcome
variables used to assess physical characteristics in adult male
basketball players across all competition levels, (2) to report
a summary of anthropometric, muscular power, linear speed,
change-of-direction speed, agility, strength, anaerobic capac-
ity, and aerobic capacity in adult male basketball players
based on playing position and competition level, and (3)
to introduce a framework outlining recommended testing
approaches to quantify physical characteristics in adult male
basketball players.
2 Methods
2.1 Design andSearch Strategy
A systematic review was conducted following the Preferred
Reporting Items of Systematic Reviews and Meta-Analy-
ses(PRISMA) statement [34]. This review was registered
with PROSPERO (ID: CRD42020187151). The academic
databases MEDLINE, PubMed, SPORTDiscus, Scopus, and
Web of Science were searched from the earliest record until
August 2020 to identify English-language, peer-reviewed,
original research studies that investigated the tests used and/
or physical characteristics of adult male basketball players.
Studies were identified by searching key terms shown in
Table1. Search levels 1–4 were all linked by the Boolean
operator ‘AND’. Search terms within each search level
were joined with ‘OR’. When searching the PubMed and
MEDLINE databases ‘young adults 19–24years’ and ‘adults
19–44years’ limiters were applied to the population age. No
limiters were available to be used when searching Web of
Science or SPORTDiscus. All search results were extracted
and imported to reference manager software (EndNote X9;
Thomson Reuters, Philadelphia, PA, USA).
2.2 Assessment ofReporting Quality
The methodological quality of each study was assessed
using a modified version of the Downs and Black check-
list (Table1 of the Electronic Supplementary Material
[ESM]). This checklist has been used previously in system-
atic reviews related to sport science [35, 36] and is a valid
method of assessing the quality of studies with observational
study designs [37]. The modified version of the Downs and
Black checklist was used because the included questions and
criteria better align with the specific aims of this review
compared with the traditional version of the checklist. The
assessment included 12 questions (1–4, 6, 7, 10–12, 16,
18, 20) and was scored on a scale from ‘0’ (no, or unable
to determine) to ‘1’ (yes) for each question. Scores were
summed across questions for each study with a total score
of ‘12’ reflecting the maximum score (highest quality) able
to be attained.
2.3 Study Selection
After duplicate studies were removed, two reviewers (MM
and JW) independently screened all titles and abstracts
against inclusion and exclusion criteria of the review. Stud-
ies deemed outside the scope of the review were removed.
Any conflicts were settled by discussion between the review-
ers with a third reviewer consulted for consensus if required.
The full-text versions of the remaining studies were then
reviewed for eligibility. To be eligible for inclusion, studies
were required to: (1) be original research studies; (2) be pub-
lished in a peer-reviewed journal; (3) have full-text versions
available in English language; and (4) have the primary aim
of reporting tests used and/or the physical characteristics of
adult (i.e. ≥ 18years of age) male basketball players. Studies
Table 1 Search strategy used to
identify articles Search 1 Search 2 Search 3
(Male OR men) (Adult OR senior) Basketball
Search 4
(Fitness testing OR physical characteristics OR Testing OR physical performance OR
physical qualities OR physical profile OR anthropometric OR body height OR body weight
OR skinfold OR body composition OR body fat OR power OR countermovement jump OR
vertical jump OR broad jump OR muscular strength OR muscular endurance OR
acceleration OR speed OR sprint OR running OR agility OR change of direction OR
fitness OR physical fitness OR aerobic capacity OR repeated-sprint ability OR anaerobic
capacity)
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1494 M.Morrison et al.
were excluded from the review if they: (1) were systematic
or narrative reviews; (2) were meta-analyses; (3) had the
primary aim of investigating a nutritional supplement or
ergogenic aid; (4) examined referees instead of players; (5)
examined wheelchair players; or (6) examined players with
a mean age under 18years or competing in ‘junior’ com-
petitions. The reference lists of the included studies were
then manually reviewed for additional eligible studies. If
further studies were identified, they were subjected to the
same assessment previously described. Figure1 outlines the
selection process during the screening of studies. Data per-
taining to the first aim of this review involved a qualitative
synthesis of the available evidence, whereas a quantitative
synthesis was used to address the second aim.
2.4 Data Collection
Data extraction included study details (authors and publica-
tion year), all tests performed to quantify physical charac-
teristics (i.e., height, body mass, wingspan, body fat per-
centage, muscular power, linear speed, change-of-direction
speed, agility, strength, anaerobic capacity, and aerobic
capacity), and the outcome variables derived from each test.
If the methods of physical testing were not clearly outlined
in the study, the tests were not included in the data extrac-
tion process. If the authors of the study did not administer
the testing protocol as part of the study (e.g., they surveyed
coaches for results [38]), the study was not included. If a test
included a skill component (e.g., dribbling a basketball) or a
series of basketball-specific movements (e.g., sprinting and
then jumping), it was not included in the analysis.
Fig. 1 Flow of selection process
of eligible studies for qualitative
and quantitative synthesis
PRISMA 2009 Flow Diagram
Records idenfied through
database searching
(
n= 1684
)
ScreeningIncluded Eligibility Idenficaon
Addional records idenfied
through other sources
(
n= 59
)
Recordsaer duplicates removed
(n= 1309)
Recordsscreened
(n= 1309)
Records excluded
(n= 1078)
Full-text arcles assessed
for eligibility
(
n= 231
)
Full-text arcles excluded,
with reasons
(n= 92)
Research aims
(n= 48)
Populaon
(n= 35)
No access to full text
version
(n= 6)
Publicaon type
(n= 3)
Not available in English
(n= 2)
Studies included in
qualitave synthesisof
tests
(n= 137)
Studies included in
quantave synthesisof
physical characteriscs
(n= 114)
Full-text arcles excluded,
with reasons
(n=23)
Characteriscs reported
outside aims of review
(n=14)
Sufficient anthropometric
values not included (n= 9)
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1495
Testing Methods and Physical Characteristics of Male Basketball Players
After the tests were extracted, data relating to playing
position and competition level were identified and reported.
Competition levels were categorised as either amateur (club,
volunteer, or recreational players), collegiate (university or
collegiate players), representative (players selected to play
in a representative team), semi-professional (some players
are contracted or full time) or professional (all players on
the team are contracted full-time athletes or competing in a
country’s highest division or competition). Playing positions
were reported as they were identified in the original text of
each study. Additionally, outcome variables for anthropo-
metric, muscular power, linear speed, change-of-direction
speed, agility, strength, anaerobic capacity, and aerobic
capacity tests were retrieved. For tests that had multiple out-
come variables, after all data were collated, variables were
counted, and the two most frequently used outcome vari-
ables were extracted. However, for linear speed and change-
of-direction speed tests, only time was extracted because of
the variability in other outcome variables reported across
studies. Likewise, for assessments of strength, only one rep-
etition maximum (1RM) performances were extracted from
studies owing to the variability in other outcome variables.
Data were extracted from each study using the raw values
provided. In the case of an intervention study (e.g., the
implementation of a resistance training programme [39]),
baseline measurements were used. Furthermore, if multi-
ple groups were included in a study, the control group was
recorded to mitigate the bias of the intervention. To mini-
mise any potential bias or confounding outcomes, studies
that did not provide basic player information including age,
height, body mass, and competition level were not included
in the reporting of physical characteristics (the second aim
of this review) but remained in the review to address the first
aim. If data were presented using figures and raw data were
not clearly available, the authors of the study were contacted
to provide the raw values. If no response was received from
the authors of a study, means and measures of distribution
were extracted from figures in studies using WebPlotDigi-
tizer v4.0 [40], which has been shown as a valid (r = 0.989,
p < 0.001) and reliable (r = 0.997, p < 0.001) [41] tool for
the extraction of raw values from figures. If a study reported
variables using units in the Imperial system, they were con-
verted to the Metric system to allow for clear comparison
across studies.
To provide greater insight into the physical requirements
of professional basketball players competing at the high-
est level, publicly available NBA Draft Combine data were
downloaded from the league’s official website [42]. Data
representing 100 players (10 players per year over 10years)
were synthesised and used as reference data to describe
physical characteristics in this population. The mean, stand-
ard deviation, as well as minimum and maximum values for
height (cm), body mass (kg), body fat percentage, wingspan
(cm), Lane Agility Test time (s), Reactive Shuttle Test time
(s), ¾ court sprint time (s), number of bench press repeti-
tions at 84kg (185lb), vertical jump height (cm), and run-
ning vertical jump height (cm) were reported.
2.5 Categorisation andPresentation ofFindings
The included physical characteristics were chosen given
their importance during basketball match-play [7, 9, 10,
20, 43–45]. The three most frequently used tests for each
physical characteristic were selected to represent that char-
acteristic. Anthropometric data pertaining to height, wing-
span, mass, and body composition were reported. Muscular
power was represented indirectly by three bilateral jumping
tests: (1) the countermovement jump (CMJ), which repre-
sents the ability to use elastic energy that is generated during
a preparatory countermovement, without the influence of
the arms (i.e., hands placed on hips); (2) the vertical jump
(VJ), which involves both a preparatory countermovement
and arm swing; and (3) the squat jump (SJ), which repre-
sents the concentric only force expressed during a jump.
Linear sprint performances over 5m, 10m, and 20m were
reported. Change-of-direction speed tests, which differ
from assessments of agility because of their predetermined
directional requirements and lack of a perceptual decision-
making component [46], included were the Agility T-Test,
Lane Agility Test, and Y-Shaped change-of-direction Agil-
ity Test. Agility tests, which require players to change their
movement in response to a stimulus [46, 47], included the
Reactive Y-Change-of-Direction Test, the Reactive Change-
of-Direction Test, and the Reactive Agility Test. Strength
was categorised as lower-body and upper-body strength,
using the back squat and bench press, respectively. Only two
tests were provided for strength characteristics because of
the variability in the remaining tests across studies. Anaer-
obic capacity was reported using the Wingate Anaerobic
Cycle Test (WAnT), full court shuttle run, and the Running-
based Anaerobic Speed Test (RAST). Aerobic capacity was
reported using tests that assessed maximal oxygen uptake
(VO2max) or distance covered during a maximal running
test. The three tests predominantly used to assess aerobic
capacity were the Yo-Yo Intermittent Recovery Test Level 1
(Yo-Yo IRL1), Multi-Stage Fitness Test (MSFT), and incre-
mental treadmill tests.
3 Results
3.1 Identification andSelection ofArticles
The search of databases identified 1684 studies. A total of
375 duplicates were removed, resulting in 1309 studies to be
screened by title and abstract. After screening, 231 studies
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1496 M.Morrison et al.
were eligible for full-text review with a further 59 eligible
studies identified in the reference lists during the full-text
screening. After full-text screening a total of 137 studies
were identified including tests and outcome variables while
114 studies reported physical characteristics in adult male
basketball players. Inter-reviewer reliability was calculated
using Cohen’s Kappa statistic (Κ = 0.85).
3.2 Assessment ofReporting Quality
Reporting quality scores ranged from 6 to 11 for the 12
items assessed in the modified Downs and Black checklist,
with a mean score of 9.47 ± 0.83 across the included studies
(Table1 of the ESM).
3.3 Data Collection Methods
The tests and outcome variables used to assess the physi-
cal characteristics of adult male basketball players across
all competition levels are displayed in Tables3–10 of the
ESM. Tests were categorised based on the characteristic
they assessed; body composition, muscular power, linear
speed, change-of-direction speed, agility, strength, anaero-
bic capacity, and aerobic capacity.
3.4 Overview ofIncluded Studies andTests
A total of 134 tests and 394 outcome variables assessing
physical characteristics in adult male basketball players
across all competition levels were included in this review.
Table2 summarises tests used across included studies to
represent each physical characteristic.
3.5 NBA Draft Combine Data Extraction
Data pertaining to the physical characteristics of 100 players
drafted into the NBA between the 2011–12 and 2020–21
seasons are presented in Table3. The mean draft pick num-
ber of the players who participated in the NBA Draft Com-
bine increased yearly from 9 ± 4 in 2011–12 to 35 ± 10 in
2020–21. Performance during the Reactive Shuttle Run was
only available from the 2013–14 season. Bench press per-
formance was not reported in the 2014–15, 2016–17, and
2020–21 seasons.
3.6 Anthropometric Characteristics
Height and body mass were reported in 116 (85%) of the 137
studies included in this review. Anthropometric data (i.e.,
height, body mass and body fat percentage) were reported
according to playing position (Figs.2, 3, 4) or as a mean
across the entire team (Table2 of the ESM).
Table 2 Tests selected to report the physical characteristics of adult male basketball players in this review
1RM one repetition maximum, COD change-of-direction, RAST Running-Based Anaerobic Speed Test, VO2max maximum oxygen uptake, Yo-Yo
IRL1 Yo-Yo Intermittent Recovery Test Level 1
Category Test Outcome variable Citations
Muscular power Countermovement jump Peak power and jump height 46
Squat jump Peak power and jump height 20
Vertical jump Peak power and jump height 33
Linear speed 5-m sprint Time 10
10-m sprint Time 18
20-m sprint Time 20
COD speed Agility T-Test Time 20
Y-Shaped COD Time 7
Lane Agility Test Time 4
Agility Y-Shaped Agility Tests Time, response time, and decision-making time 7
Strength Bench press 1RM 17
Back squat 1RM 7
Aerobic capacity Yo-Yo IRL1 Estimated VO2max and distance 12
Multi-Stage Fitness Test Estimated VO2max and number of shuttles 10
Incremental Treadmill Tests VO2max 21
Anaerobic capacity Full Court Shuttle Run Time 5
RAST Peak power, mean power, and fatigue index 6
Wingate Anaerobic Cycle Test Peak power, mean power, and fatigue index 8
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1497
Testing Methods and Physical Characteristics of Male Basketball Players
Mean height ranged between 177 and 214cm across
studies. The mean height of professional (183–202cm) and
collegiate (177–201cm) players had similar ranges. Addi-
tionally, semi-professional (182–198cm) and representa-
tive (182–197cm) players had mean heights that were also
comparable. Finally, the shortest players were observed
at the amateur level with mean height range from 180 to
195cm. When mean height was reported according to play-
ing position, guards (183–193cm [Fig.2]) were consist-
ently reported as being shorter than forwards (190–202cm
[Fig.3]), with centres observed as the tallest players
(198–214cm [Fig.4]). Positional mean heights at the profes-
sional level followed the same trend (guards: 183–193cm,
forwards: 190–201cm, and centres 198–214cm). Further-
more, three studies suggested the same positional trend
was present in the mean height of semi-professional play-
ers (guards: 183–187cm [4, 48, 49], forwards: 194 ± 5cm
[48, 49], forwards and centres: 194 ± 7cm [4], and centres:
198 ± 5cm [48, 49]). Only two studies (guards: 187 ± 7cm
[50], forwards: 202 ± 4cm [50], backcourt: 188 ± 6cm [3],
and frontcourt: 201 ± 6cm [3]) reported collegiate player
height according to playing position, while no studies
reported height in specific playing positions at the repre-
sentative or amateur levels.
Mean body mass reported across studies ranged between
68 and 111kg (Figs.2, 3, 4 and Table2 of the ESM). The
range in mean body mass of players competing at various
competition levels were: professional: 76–105kg; semi-
professional: 74–90kg; representative: 76–100kg; colle-
giate: 69–101kg; and amateur: 68–94kg. Observing mean
body mass by playing position revealed guards (77–90kg
[Fig.2]), were typically lightest, with forwards being heav-
ier than guards (82–105kg [Fig.3]), and centres being the
heaviest (93–111kg [Fig.4]). Professional guards had mean
body masses between 77 and 90kg, professional forwards
between 82 and 100kg, and centres between 96 and 111kg.
Three studies reported body mass by playing position at
the semi-professional level (guards: 78.1 ± 6kg [48, 49],
85.5 ± 12.3kg [4], forwards: 89.5 ± 7.9kg [48, 49], forwards
and centres: 109.4 ± 8.8kg [4], and centres: 92.6 ± 8.2kg
[48, 49]). Only two studies reported body mass by playing
position at the collegiate level (guards: 85.2 ± 7.4kg [50],
forwards: 105.3 ± 8kg [50], backcourt: 83.3 ± 8.1kg [3],
and frontcourt: 108.1 ± 9.9kg [3]). No studies reported body
mass by playing position at the representative or amateur
levels.
Wingspan was reported in three studies [3, 51, 52] with
a mean value range from 194 to 207cm. One study [51]
observed a wingspan of 200 ± 10cm in a team of collegiate
NCAA Division 2 players. A second study [3] reported a
wingspan of 199 ± 10cm across the team, with data also pro-
vided according to playing position (backcourt: 194 ± 10cm
and frontcourt: 205 ± 3cm) in collegiate NCAA Division
1 players. Finally, the wingspans of guards (190 ± 5cm),
forwards (197 ± 6cm), centres (207 ± 8cm) and the entire
team (198 ± 9cm) were observed in players competing pro-
fessionally in Poland [52].
Body composition was assessed in 68 (50%) of the 137
studies included in this review, with 14 different types of
tests and nine outcome variables used (Table3 of the ESM).
Data pertaining to body composition by playing position are
reported in Fig.2 (guards), Fig.3 (forwards) and Fig.4 (cen-
tres), and mean team measurements are provided in Table2
of the ESM. The most frequently implemented test and out-
come variable used across studies were the sum of skinfolds
at three sites (chest, abdomen, and thigh [16, 53–58], tri-
ceps, pectoral, and subscapular [59], and triceps, abdomen,
and thigh [4, 21, 60]) and body fat percentage, respectively
(Table3 of the ESM).
Mean body composition ranged between 7 and 24% body
fat across studies (Figs.2, 3, 4 and Table2 of the ESM).
Mean body fat percentage across competition levels revealed
professional players varied between 7 and 20%, while semi-
professional (9–16%), collegiate (10–14%), and represent-
ative (8–14%) levels exhibited similar ranges in body fat
percentage. Amateur players possessed varied mean body
composition measurements of between 10 and 24% body
fat. When mean body composition was reported accord-
ing to playing position, guards (7–20% [Fig.2]), forwards
(8–17% [Fig.3]), and centres (7–21% [Fig.4]) demonstrated
similar variance in body fat percentage. Professional guards
(7–20%), forwards (8–17%), and centres (7–21%) also pos-
sessed similar levels of body fat. Semi-professional guard
or backcourt (9–13%) and forward or frontcourt (11–17%)
body fat percentages were reported in three studies [4, 48,
49], whereas centres (11.7 ± 4.1%) were only reported in
two studies [48, 49]. Body fat percentages were reported
Table 3 Summary of National Basketball Association Draft Combine
performance over the previous 10years
SD standard deviation. Bench press = number of completed bench
press repetitions at 84kg (185lb)
Test Mean ± SD Minimum Maximum
Height (cm) 197.7 ± 7.6 181.6 212.7
Wingspan (cm) 210 ± 8.6 187.3 231.8
Body mass (kg) 97.2 ± 10.5 77.1 126.4
Body fat % 6.7 ± 1.9 3.2 13.6
Lane Agility Test (s) 11.1 ± 0.4 10.3 12.2
Reactive Shuttle Run (s) 3.0 ± 0.2 2.3 3.7
¾ Court sprint (s) 3.3 ± 0.1 3.6 3.0
Bench press 8.8 ± 4.7 0.0 20.0
Vertical jump (cm) 77.4 ± 7.7 62.2 96.5
Running vertical jump
(cm)
92.4 ± 7.9 74.9 110.5
Draft pick 16.6 ± 10.1 2 50
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1498 M.Morrison et al.
for guard and forward positions at the collegiate level in
one study [50] (Figs.2, 3). No studies reported body fat
percentage relative to playing position at the representative
or amateur playing levels.
3.7 Muscular Power
Muscular power was assessed predominantly using jump
tests, with 80 (58%) of the 137 studies in this review employ-
ing 18 different jump tests (Table4 of the ESM). The three
most frequent jump tests adopted across studies were the
CMJ (43 studies, 54% of studies assessing muscular power)
[14, 16, 27, 48, 51, 54, 55, 58, 61–7577–96], VJ (27 stud-
ies, 34% of studies assessing muscular power) [3, 14, 28,
39, 56, 59, 62, 66, 82, 90–92, 96–100, 102–111], and SJ (15
studies, 18% of studies assessing muscular power) [27, 58,
61, 63, 67, 72, 77–79, 81, 89, 90, 93, 95, 96]. Additional
jump tests used across studies are reported in Table4 of
the ESM. The most commonly reported outcome variables
were jump height and peak power (Table4 of the ESM).
Two throwing tests were also used in studies to assess mus-
cular power including a seated basketball throw [68] with
speed (km/hour) of the throw taken as the outcome vari-
able, and a seated medicine ball throw (1kg [87, 89] and
unknown mass [56]) with horizontal displacement (m) of
the ball used as the outcome variable. Additionally, mus-
cular power variables were also recorded during tests pre-
dominantly implemented to assess strength. These tests are
reported in Sect.3.2.7 and include bench press and squat
exercises (Table8 of the ESM).
Jump performance variables reported across studies dur-
ing the CMJ, VJ, and SJ are provided in Tables4, 5, and
6. Mean CMJ height ranged between 34 and 77cm, while
mean peak power outputs ranged between 2441 and 6647W
Fig. 2 Height, mass, and body fat percentage of the guard playing position in adult male basketball players
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1499
Testing Methods and Physical Characteristics of Male Basketball Players
(Table4). In professional players, mean CMJ height and
mean CMJ peak power ranged between 36 and 63cm and
between 3874 and 5468W, respectively. Mean CMJ height
(34–50cm) and mean CMJ peak power (2441–5078W)
were lower in semi-professional players than professional
players, while collegiate players had the greatest mean jump
height (36–77cm) and peak power output (4736–6647W).
Countermovement jump height was only reported in one
study [65] at the representative level with CMJ peak power
not reported. Countermovement jump height and CMJ peak
power were reported at the amateur level in one study [16]
(Table4). Countermovement jump performance was only
reported according to playing position at the professional
level [14, 27, 48, 79, 84, 88, 90], the collegiate level [75]
and as a combined group of players from amateur to profes-
sional levels [16]. Similar mean CMJ heights were evident
between positions in professional players (guards: 38–60cm,
forwards: 36–58cm, and centres: 36–57cm), while mean
absolute peak power was lowest in guards (3874–4510W),
then forwards (3930–5221W), and greatest in centres
(4536–5353W).
Mean jump height measured during the VJ was the
greatest across all jump tests, with a range from 39 to 83
cm, while mean VJ peak power ranged between 2121 and
6701W (Table5). Professional players recorded mean VJ
heights between 39 and 69cm and mean VJ peak power
outputs of 2215–6701W during the VJ. Semi-professional
players reached mean VJ heights between 41 and 65cm.
Fig. 3 Height, mass, and body fat percentage of the forward playing position in adult male basketball players
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1500 M.Morrison et al.
However, only two studies [66, 107] reported peak power
output (2121–3591W) for semi-professional players during
the VJ. Collegiate players recorded mean VJ heights between
44 and 83cm, whileno studies reported peak power output.
No studies reported VJ performance in representative play-
ers. Two studies [97, 98] reported VJ height in amateur play-
ers (41–52cm), while no studies reported peak power output
in amateur players. Vertical jump height relative to playing
position (guards: 44–65cm, forwards: 44–64cm, and cen-
tres: 39–63cm) was only reported in professional players
across three studies [14, 90, 109], one of which measured
peak power [90] (Table5). Positional VJ performance was
only reported in one study in semi-professional [28] and
collegiate [3] players (Table5). No studies reported posi-
tional VJ performance in representative or amateur players.
Mean SJ height ranged between 27 and 58cm, while
mean SJ peak power outputs were only reported in pro-
fessional players and ranged between 3639 and 5149W
(Table6). Professional players reached mean SJ jump
heights between 29 and 50cm. Only one study [58] reported
SJ height in semi-professional players, while peak power was
not reported. Squat jump height in collegiate players was
only reported in one study [95], while no studies reported SJ
peak power output in collegiate players. No studies reported
SJ height or peak power in representative or amateur players.
Mean SJ height [27, 79, 90] (guards: 30–41cm, forwards:
29–40cm, and centres: 33–36cm) and peak power [27, 90]
Fig. 4 Height, mass, and body fat percentage of the centre playing position in adult male basketball players
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1501
Testing Methods and Physical Characteristics of Male Basketball Players
Table 4 Jump height and peak power variables reported during the countermovement jump in adult male basketball players
Study Playing position Competition level Category Jump height (cm) Peak power (W)
Alemdaroglu [61] All Turkish D1 Professional 34.9 ± 3.8
Annino etal. [62] All Italian National Federal League L2 Professional 38.9 ± 3.6
Aoki etal. [63] All Brazilian National League Professional 38.1 ± 2.8
Barrera-Domínguez etal.
[64]
All Spanish National Division Professional 35.6 ± 4.8
Ben Abdelkrim etal. [65] All (U20)
All
Tunisian National Team
Tunisian National Team
Representative
Professional
49.1 ± 5.9
49.7 ± 5.8
4656 ± 81
4665 ± 116
Boone and Bourgois [27] Point guard
Shooting guard
Small forward
Power forward
Centre
Belgian D1
Belgian D1
Belgian D1
Belgian D1
Belgian D1
Professional
Professional
Professional
Professional
Professional
42.7 ± 3.8
41.3 ± 3.2
42.5 ± 3.8
42.4 ± 3.7
36.2 ± 4.1
4306 ± 373
4510 ± 322
4901 ± 387
5221 ± 364
5180 ± 451
Buśko etal. [66] All Warsaw Sports Club Polonia D2 Semi-profes-
sional
41.9 ± 4.0 2441 ± 440
Chaouachi etal. [67] All Tunisian National Team Professional 61.9 ± 6.2
Chen etal. [68] All Collegiate D1 Collegiate 45.6 ± 4.0
Ciacci and Bartolomei [96] All
All
National Level
National Level
Professional
Professional
39.2 ± 5.7
41.9 ± 5.2
Dawes and Spiteri [51] All NCAA D2 Collegiate 76.9 ± 7.5
Dello Iacono etal. [69] All Professional Basketball Club UK Professional 60.4 ± NR
Ferioli etal. [54] All
All
Italian Serie A and Serie A2
Italian Serie B
Professional
Semi-profes-
sional
50.3 ± 5.4
49.4 ± 5.4
5153 ± 593
4405 ± 667
Ferioli etal. [16] All
All
All
All
Guard
Forward
Centre
Italian Serie A
Italian Serie A2
Italian Serie B
Italian Serie D
Italian Serie A-D
Italian Serie A-D
Italian Serie A-D
Professional
Professional
Semi-profes-
sional
Amateur
Amateur – Pro
Amateur – Pro
Amateur – Pro
47.8 ± 5.7
49.2 ± 4.9
48.0 ± 6.1
51.8 ± 4.1
49.2 ± 4.9
48.6 ± 6.0
45.8 ± 6.0
5468 ± 820
5177 ± 629
4685 ± 723
4800 ± 536
4785 ± 678
5436 ± 738
5560 ± 682
Ferioli etal. [55] All
All
All
Italian Serie A
Italian Serie A2
Italian Serie B
Professional
Professional
Semi-profes-
sional
46.9 ± 4.4
50.9 ± 5.6
50.1 ± 4.8
5282 ± 582
5182 ± 745
4691 ± 624
Freitas etal. [70] All Spanish Liga EBA D4 Semi-profes-
sional
35.0 ± 7.0 5078 ± 437
Freitas etal. [71] All Spanish Liga EBA D4 Semi-profes-
sional
36.5 ± 7.2 4699 ± 781
Gomes etal. [72] All PSCB Professional 39.3 ± 5.6
Heishman etal. [74] All NCAA D1 Collegiate 58.3 ± 1.4 6374 ± 165
Heishman etal. [73] All NCAA D1 Collegiate 62.8 ± 1.5 6647 ± 171
Heishman etal. [75] All
Guards
Frontcourt
NCAA D1
NCAA D1
NCAA D1
Collegiate
Collegiate
Collegiate
38.7 ± 6.4
42.6 ± 0.4
34.6 ± 0.4
Jallai etal. [77] All Estonian 1st League Professional 43.2 ± 2.3
Khlifa etal. [78] All Tunisian D1 Professional 45.2 ± 1.3#
Köklü etal. [79] All
All
All
Guard
Forward
Centre
Turkish D1 and D2
Turkish D1
Turkish D2
Turkish D1 and D2
Turkish D1 and D2
Turkish D1 and D2
Professional
Professional
Professional
Professional
Professional
Professional
38.3 ± 5.3
40.6 ± 4.7
36.0 ± 5.0
38.2 ± 5.8
40.1 ± 5.1
36.6 ± 4.7
Laplaud etal. [80] All Professional Professional 63.0 ± 9.0
Maffiuletti etal. [81] All French Basketball Federation D2 Professional 51.0 ± 1.3
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1502 M.Morrison et al.
Table 4 (continued)
Study Playing position Competition level Category Jump height (cm) Peak power (W)
Maggioni etal. [58] All Volunteer Players Semi-profes-
sional
32.0 ± 4.9
Mandic etal. [82] All National League Serbia Professional 36.9 ± 3.7
Miura etal. [83] All National Collegiate Japan Collegiate 50.5 ± 5.4
Ostojic etal. [84] All
Guard
Forward
Centre
First National League Serbia
First National League Serbia
First National League Serbia
First National League Serbia
Professional
Professional
Professional
Professional
57.4 ± 7.7
59.7 ± 9.6
57.8 ± 6.5
54.6 ± 6.9
Pehar etal. [48] All
All
Guard
Forward
Centre
Guard
Guard
Forward
Forward
Centre
Centre
Bosnia and Herzegovina D1
Bosnia and Herzegovina D2
Bosnia and Herzegovina D1 and D2
Bosnia and Herzegovina D1 and D2
Bosnia and Herzegovina D1 and D2
Bosnia and Herzegovina D1
Bosnia and Herzegovina D2
Bosnia and Herzegovina D1
Bosnia and Herzegovina D2
Bosnia and Herzegovina D1
Bosnia and Herzegovina D2
Professional
Professional
Professional
Professional
Professional
Professional
Professional
Professional
Professional
Professional
Professional
45.5 ± 5.6
45.3 ± 6.1
46.4 ± 6.0
45.5 ± 5.5
43.9 ± 5.5
46.9 ± 5.4
46.0 ± 6.6
46.5 ± 5.3
44.5 ± 5.9
43.7 ± 5.6
44.5 ± 5.6
Pehar etal. [85] All Bosnia and Herzegovina D1 Professional 45.6 ± 5.5
Pliauga etal. [86] All Lithuanian National Basketball
League
Collegiate 47.8 ± 3.0
Pojskić etal. [88] Guard Bosnian Premier League Professional 40.4 ± 5.0 3874 ± 639
Forward Bosnian Premier League Professional 37.6 ± 6.8 3930 ± 604
Centre Bosnian Premier League Professional 36.0 ± 3.8 4536 ± 458
Pojskić etal. [87] Perimeter Bosnian Premier League Professional 38.5 ± 3.5
Pojskić etal. [89] Perimeter Bosnian and Herzegovina D1 Professional 38.5 ± 3.5
Ponce-González etal. [90] All
Guard
Forward
Centre
Perimeter
Inside
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Professional
Professional
Professional
Professional
Professional
Professional
36.8 ± 4.1
37.7 ± 3.8
35.6 ± 4.6
37.2 ± 4.9
37.4 ± 3.8
36.1 ± 4.9
4707 ± 676
4159 ± 218
4607 ± 606
5353 ± 538
4399 ± 521
5137 ± 672
Puente etal. [14] All National Spanish Basketball Federa-
tion
Professional 58 ± 4
Guard National Spanish Basketball Federa-
tion
Professional
Professional
58 ± 3
58 ± 5
Forward National Spanish Basketball Federa-
tion
Centre National Spanish Basketball Federa-
tion
Professional 57 ± 2
Rodriguez-Rosell etal.
[91]
All Spanish Liga EBA D4 Semi-profes-
sional
34.8 ± 5.8
Schiltz etal. [92] All European Cup D1 Professional 40.5 ± 5.7
Shalfawi etal. [93] All Professional level Norway Professional 52.0 ± 7.5 5167 ± 419
Stojanovic etal. [94] All Serbian Professional League Professional 39.8 ± 5.1
Xie etal. [95] All
All
NCAA D1 university team
NCAA D1 club team
Collegiate
Collegiate
71.9 ± 9.1
72.7 ± 4.3
Data are presented as mean ± standard deviation
D1 Division one competition, D2 Division two competition, D4 Division four competition, Inside power forward and centre positions, L2 second
league, Liga ACB Liga Endesa Asociación de Clubs de Baloncesto, Liga EBA Liga Española de Baloncesto Aficionado, NCAA National Colle-
giate Athletic Association, NR no data provided, Perimeter point guard, shooting guard and small forward positions, PSBC Paulista State Basket-
ball Championships, U20 players competing in an under 20years of age competition, # indicates standard error of measurement
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1503
Testing Methods and Physical Characteristics of Male Basketball Players
Table 5 Jump height and peak power variables reported during the vertical jump in adult male basketball players
Data are presented as mean ± standard deviation
88–89 data collected from collegiate team during the 1988–90 season, 89–90 data collected from collegiate team during the 1989–90 season,
90–91 data collected from collegiate team during the 1990–91 season, 91–92 data collected from collegiate team during the 1991–2 season,
Backcourt players guards, D1 Division one competition, D2 Division two competition, D3 Division three competition, D4 Division four compe-
tition, Inside power forward and centre positions, Frontcourt players forwards and centres, L2 second league, Liga ACB Liga Endesa Asociación
de Clubs de Baloncesto, Liga EBA Liga Española de Baloncesto Aficionado, NBA National Basketball Association, NCAA National Collegiate
Athletic Association, NR no data provided, Perimeter point guard, shooting guard and small forward positions, WPD indicates data extracted by
WebPlotDigitizer
Study Playing position Competition level Category Jump height (cm) Peak power (W)
Annino etal. [62] All Italian National Federal League L2 Professional 45.9 ± 3.4
Asadi etal. [97] All Provincial D1 Italy Amateur 41.3 ± 3.4
Balabinis etal. [98] All Undergraduate Teams Greece Amateur 52.2 ± 2.2
Balsalobre-Fernandez etal. [99] All Spanish Pro Liga ACB Professional 45.6 ± 5.9
Balsalobre-Fernandez etal. [100] All Spanish Pro Liga ACB Professional 43.9 ± 7.3 4856 ± 601WPD
Buśko etal. [66] All Warsaw Sports Club Polonia D2 Semi-professional 52.5 ± 5.1 3591 ± 788
Ciacci and Bartolomei [96] All
All
National Level Italy
National Level Italy
Professional
Professional
44.6 ± 6.2
49.3 ± 5.7
de Sousa Fortes etal. [59] All State Basketball Championship Brazil Professional 42.0 ± 8.0
Hoffman etal. [103] All NCAA D1 Collegiate 64.5 ± 9.7
Hoffman etal. [102] All NCAA D1 Collegiate 63.4 ± 6.9
Hoffman etal. [104] All 88–89
All 89 –90
All 90–91
All 91–92
NCAA D1
NCAA D1
NCAA D1
NCAA D1
Collegiate
Collegiate
Collegiate
Collegiate
68.1 ± 8.6
66.0 ± 6.9
72.6 ± 5.6
67.3 ± 6.0
Hunter etal. [105] All U.S College Collegiate 61.0 ± 7.4
Kariyawasam etal. [56] All National Level Sri Lanka Professional 47.9 ± 6.8
Kipp etal. [106] All NCAA D1 Collegiate 62.4 ± 5.4
Korkmaz and Karahan [107] All
All
All
Turkish D1
Turkish D2
Turkish D3 (regional)
Professional
Professional
Semi-professional
48.2 ± 4.0
48.3 ± 3.0
45.5 ± 4.0
2347 ± 161
2215 ± 130
2121 ± 130
Lehnert etal. [108] All Czech First League Professional 48.2 ± 4.6
Lockie etal. [3] All
Backcourt
Frontcourt
NCAA D1
NCAA D1
NCAA D1
Collegiate
Collegiate
Collegiate
77.9 ± 9.9
83.4 ± 8.4
69.9 ± 5.2
Mandic etal. [82] All National League Serbia Professional 43.3 ± 3.6
Montgomery etal. [28] All
Guard
Forward
Centre
Australian State Level
Australian State Level
Australian State Level
Australian State Level
Semi-professional
Semi-professional
Semi-professional
Semi-professional
61.9 ± 14.6
61.3 ± 19.9
61.2 ± 7.5
65.3 ± 9.0
Nikolaidis etal. [109] All
Guard
Forward
Centre
Italian First League
Italian First League
Italian First League
Italian First League
Professional
Professional
Professional
Professional
44.4 ± 6.8
45.1 ± 3.3
46.9 ± 7.8
39.0 ± 4.3
Pliaugu etal. [39] All Lithuania National Basketball League Collegiate 53.0 ± 9.5WPD
Ponce-González etal. [90] All
Guard
Forward
Centre
Perimeter
Inside
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Professional
Professional
Professional
Professional
Professional
Professional
44.2 ± 4.4
43.7 ± 1.8
43.9 ± 4.3
45.0 ± 7.0
44.4 ± 2.8
43.9 ± 6.5
5753 ± 932
4992 ± 546
5567 ± 606
6701 ± 709
5300 ± 663
6388 ± 931
Puente etal. [14] All National Spanish Basketball Federation Professional 64 ± 4
Guard National Spanish Basketball Federation Professional 65 ± 3
Forward National Spanish Basketball Federation Professional 64 ± 6
Centre National Spanish Basketball Federation Professional 63 ± 4
Rauch etal. [110] All NBA Professional 68.7 ± 7.4
Rodriguez-Rosell etal. [91] All Spanish Liga EBA D4 Semi-professional 40.5 ± 7.0
Schiltz etal. [92] All Professional D1 European Cup Professional 48.7 ± 5.3
Townsend etal. [111] All Collegiate D1 United States Collegiate 77.4 ± 6.4
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1504 M.Morrison et al.
(guards: 3639–4402W, forwards: 4034–5021W, and cen-
tres: 5054–5149W) were only reported according to play-
ing position at the professional level. Reliability statistics
for each of the jump tests reported in Tables4, 5 and 6 are
provided in Table13 of the ESM.
3.8 Linear Sprint Speed
Linear sprint tests were conducted in 39 (28%) of the 137
studies included in this review (Table5 of the ESM). The
most frequently included linear sprint distances were 5m (9
studies, 23% of studies assessing linear sprint speed) [4, 21,
27, 51, 58, 64, 65, 67, 112], 10m (16 studies, 41% of studies
assessing linear sprint speed) [21, 27, 60, 61, 64, 65, 67, 71,
79, 86, 91, 93, 95, 112, 113] and 20m (18 studies, 46% of
studies assessing linear sprint speed) [4, 21, 28–30, 39, 51,
58, 59, 72, 87, 89, 91, 93, 95, 107, 111, 114]. Time was the
most common outcome variable and was used in every linear
sprint test adopted across studies (Table5 of the ESM).
Over 5m, mean sprint times ranged from 0.80 to 1.51s
(Table7). Professional players demonstrated mean 5-m
sprint times between 0.82 and 1.51s (Table7). Only four
studies [4, 21, 58, 112] reported 5-m sprint times at the
semi-professional level (1.04–1.14s). One study reported
5-m sprint time in representative [65] and collegiate [51]
players (Table7). No studies reported 5-m sprint times in
amateur players. Mean sprint times over 10m ranged from
1.47 to 2.34s (Table7). Professional players recorded mean
Table 6 Jump height and power variables according to playing position and competition level during the squat jump in adult male basketball
players
Data are presented as mean ± standard deviation
D1 Division one competition, D2 Division two competition, Inside power forward and centre positions, Liga ACB Liga Endesa Asociación de
Clubs de Baloncesto, NCAA National Collegiate Athletic Association, Perimeter point guard, shooting guard and small forward positions, PSBC
Paulista State Basketball Championships, ^ indicates reported in W⋅kg−1, # indicates standard error of measurement
Study Playing position Competition level Category Jump height (cm) Peak power (W)
Alemdaroglu [61] All Turkish D1 Professional 32.9 ± 3.8
Aoki etal. [63] All Brazilian National League Professional 34.8 ± 2.6
Boone and Bourgois [27] Point guard
Shooting guard
Small forward
Power forward
Centre
Belgian D1
Belgian D1
Belgian D1
Belgian D1
Belgian D1
Professional
Professional
Professional
Professional
Professional
41.0 ± 3.8
39.5 ± 3.6
40.2 ± 3.7
39.1 ± 4.2
35.7 ± 3.2
4203 ± 371
4402 ± 358
4761 ± 381
5021 ± 423
5149 ± 399
Chaouachi etal. [67] All Tunisian National Team Professional 49.5 ± 4.8
Ciacci and Bartolomei [96] All
All
National Level Italy
National Level Italy
Professional
Professional
36.2 ± 5.0
42.5 ± 5.0
Gomes etal. [72] All PSBC Professional 33.4 ± 5.2
Jallai etal. [77] All Estonian 1st League Professional 40.4 ± 2.0 24.23 ± 5.77^
Khlifa etal. [78] All Tunisian D1 Professional 38.6 ± 1.1#
Köklü etal. [79] All
All
All
Guard
Forward
Centre
Turkish D1 and D2
Turkish D1
Turkish D2
Turkish D1 and D2
Turkish D1 and D2
Turkish D1 and D2
Professional
Professional
Professional
Professional
Professional
Professional
36.2 ± 5.5
37.8 ± 5.7
34.7 ± 5.7
36.4 ± 5.7
37.7 ± 5.2
34.7 ± 5.4
Maffiuletti etal. [81] All French Basketball Federation D2 Professional 44.1 ± 1.8
Maggioni etal. [58] All Volunteer Players Semi-professional 26.5 ± 3.8
Pojskic etal. [89] All Bosnia and Herzegovina D1 Professional 31.1 ± 31.1
Ponce-Gonzalez etal. [90] All
Guard
Forward
Centre
Perimeter
Inside
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Spanish Pro Liga ACB
Professional
Professional
Professional
Professional
Professional
Professional
30.6 ± 5.5
30.1 ± 5.7
28.5 ± 3.2
33.2 ± 7.3
29.6 ± 4.6
31.9 ± 6.8
4242 ± 746
3639 ± 413
4034 ± 390
5054 ± 544
3872 ± 449
4761 ± 807
Shalfawi etal. [93] All Professional level Norway Professional 43.1 ± 7.2 4609 ± 419
Xie etal. [95] All
All
NCAA D1 university team
NCAA D1 club team
Collegiate
Collegiate
57.8 ± 7.9
56.4 ± 3.7
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1505
Testing Methods and Physical Characteristics of Male Basketball Players
10-m sprint times between 1.47 and 2.34s. Homogenous
mean 10-m sprint times were reported in semi-professional
players (1.77–1.90s). Only one study [113] reported 10-m
sprint time in amateur players (Table7). Mean sprint times
over 20m ranged between 2.43 and 3.36s (Table7). Mean
sprint times over 20m were similar between professional
(2.43–3.24s) and semi-professional (2.80–3.24s) players.
One study [114] reported 20-m sprint times in representa-
tive players (Table7). Collegiate players recorded mean
20-m sprint times ranging from 2.80 to 3.36s. No studies
reported 20-m sprint time in amateur players. Linear sprint
performance according to playing position was reported at
the professional [27] and semi-professional [4] levels across
5m, professional [27, 79] and semi-professional [4] levels
across 10m, and professional [87, 89] and semi-professional
[4, 28] levels across 20m (Table7). Reliability statistics
for each of the linear sprint tests described in Table7 are
provided in Table13 of the ESM.
3.9 Change‑of‑Direction Speed
Change-of-direction speed was assessed in 38 (28%) of
the 137 studies in this review, with 17 different tests used
(Table6 of the ESM). All tests used time as the primary out-
come variable except the Multi-Stage Change of Direction
Exercise Test, which used metabolic power, running speed,
peak torque and fatigue index as outcome variables (Table6
of the ESM). The Agility T-Test was the most frequently
implemented change-of-direction speed test being used in
20 studies (53% of studies measuring change-of-direction
speed) [49, 58, 61, 65, 67, 70–72, 79, 87, 89, 97, 102–104,
112, 114–117]. Mean Agility T-Test time ranged between
8.84 and 10.90s across studies. Professional players demon-
strated mean Agility T-Test times between 8.84 and 10.04s,
which were similar to collegiate players (8.92–9.78s), and
quicker than mean times reported in semi-professional play-
ers (9.52–10.90s). Agility T-Test time was only reported
in representative players (9.21–10.05s) in two studies [65,
114] while only one study [97] observed amateur players
(Table8). Two studies [49, 79] reported Agility T-Test
times relative to playing position (guard: 8.96–9.24s, for-
ward: 8.84–9.48s, and centre: 9.73–10.04s), only at the
professional level. The Lane Agility Test was only used in
three studies (8% of studies measuring change-of-direction
speed) [3, 51, 111] and only assessing collegiate players
(10.16–11.80s), with one study [3] reporting results accord-
ing to playing position (Table8). Table8 contains Agility
T-Test, Lane Agility Test and Y-Shaped Change-of-Direction
Speed Test outcomes reported in adult male basketball play-
ers. Reliability statistics for each of the change-of-direction
tests described in Table8 are provided in Table13 of the
ESM.
3.10 Agility
Agility performance was reported in seven (5%) of the 137
studies included in this review (Table7 of the ESM). Only
three tests were used to assess agility including the Reac-
tive Agility Test [4, 21, 60], Reactive Change-of-Direction
Test [113, 118], and Reactive Y-Shaped Change-of-Direc-
tion Test [49, 85]. Time was the primary outcome variable
reported across studies in all agility tests, with response time
and decision-making time also reported in three studies [4,
21, 60]. Agility tests were performed slower compared to the
pre-determined change-of-direction speed tests following the
same design [4, 21, 49, 60, 113, 118]. The Reactive Agil-
ity Test was performed exclusively at the semi-professional
level [4, 21, 60] and performance ranged between 2.00 and
2.18s. Reactive COD Test performance ranged between
2.52 and 2.77s at the semi-professional [113, 118] level.
Only one study [113] reported Reactive COD performance
at the amateur level (Table9). The Reactive Y-COD test was
only reported in two studies [48, 49] (Table9). No studies
measured the agility of players at collegiate or representative
levels. Only one study [49] reported agility performance by
playing position (Table9). Reliability statistics for each of
the agility tests described in Table9 are provided in Table13
of the ESM.
3.11 Strength
Strength testing was undertaken in 42 (31%) of the 137 stud-
ies in this review (Table8 of the ESM). Repetition maximum
outcome variables were most frequently gathered across
studies, with 1RM and 3RM being the most used protocols
(Table8 of the ESM). Bench press performance, represented
by 1RM were observed in 17 studies (40% of studies assess-
ing strength) [51, 56, 65, 67, 70–72, 98, 99, 102–105, 114,
119–121], with mean loads lifted between 70 and 112kg
(Table10). Professional players bench pressed 1RM loads
between 70 and 112kg (Table10). Only two studies reported
bench press 1RM each in semi-professional (76–86kg) [70,
71] and representative (77–101kg) [65, 114] players. Col-
legiate players bench pressed 1RM loads between 76 and
102kg (Table10). Only one study [98] reported bench press
1RM in amateur players and only one study [121] reported
bench press 1RM by playing position, at the professional
level (Table10).
The squat exercise (i.e., front and back squat) was used
in 16 studies (38% of studies assessing strength) [51, 59,
65, 67, 70, 71, 91, 98, 102–104, 111, 119, 122–124] to
assess strength with 1RM and 3RM protocols most fre-
quently used (Table8 of the ESM). Mean back squat
1RM loads ranged between 116 and 202kg across studies
(Table10). Professional players squatted greater mean 1RM
loads (143–202kg) than collegiate players (116–156kg)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1506 M.Morrison et al.
Table 7 Sprint times recorded during 5-m, 10-m and 20-m linear sprints in adult male basketball players
Data presented as mean ± standard deviation
BUSA British Universities Sports Association, D1 Division one competition, D2 Division two competition, D3 Division three competition, D4
Division four competition, Liga EBA Liga Española de Baloncesto Aficionado, NCAA National Collegiate Athletic Association, Perimeter point
guard, shooting guard and small forward positions, PSBC Paulista State Basketball Championships, SCCSBL South Chilean College System
Basketball League, U20 players competing in an under 20years of age competition, m/s indicates velocity in m.s−1, 1080 indicates performed using
1080 sprint with 1-kg resistance
Study Playing position Competition level Category 5-m sprint
time (s)
10-m sprint
time (s)
20-m sprint
time (s)
Alemdaroglu [61] All Turkish D1 Professional 1.86 ± 0.30
Barrera-Domínguez etal.
[64]
All Spanish National Division Professional 0.88 ± 0.04 1.47 ± 0.08
Ben Abdelkrim etal. [65] All (U20) Tunisian National Team Representative 1.00 ± 0.10
All Tunisian National Team Professional 1.04 ± 0.16 1.84 ± 0.10
1.88 ± 0.15
Boone and Bourgois [27] Point guard Belgian D1 Professional 1.40 ± 0.03 2.16 ± 0.09
Shooting guard Belgian D1 Professional 1.40 ± 0.09 2.19 ± 0.08
Small forward Belgian D1 Professional 1.45 ± 0.09 2.23 ± 0.09
Power forward Belgian D1 Professional 1.47 ± 0.08 2.25 ± 0.08
Centre Belgian D1 Professional 1.51 ± 0.07 2.34 ± 0.11
Chaouachi etal. [67] All Tunisian National Team Professional 0.82 ± 0.05 1.70 ± 0.06
Dawes and Spiteri [51] All NCAA D2 Collegiate 0.80 ± 0.04 2.80 ± 0.08
de Sousa Fortes etal. [59] All State Basketball Championship Brazil Professional 2.43 ± 0.21
Delextrat and Cohen [114] All
All
All
BUSA D1 and D2
BUSA D1
BUSA D2
Collegiate—Representative
Representative
Collegiate
3.33 ± 0.26
3.29 ± 0.12
3.36 ± 0.36
Freitas etal. [71] All Spanish Liga EBA D4 Semi-professional 1.91 ± 0.09
Gomes etal. [72] All PSBC Professional 3.24 ± 0.22
Köklü etal. [79] All Turkish D1 and D2 Professional 1.75 ± 0.08
All Turkish D1 Professional 1.78 ± 0.80
All Turkish D2 Professional 1.72 ± 0.80
Guards Turkish D1 and D2 Professional 1.72 ± 0.07
Forward Turkish D1 and D2 Professional 1.72 ± 0.07
Centre Turkish D1 and D2 Professional 1.80 ± 0.08
Korkmaz and Karahan [107] All Turkish D1 Professional 2.70 ± 0.14
All Turkish D2 Professional 2.80 ± 0.10
All Turkish D3 Semi-professional 2.80 ± 0.13
Lockie etal. [113] All Australian State level Semi-professional 1.81 ± 0.09
All Recreational Australia Amateur 1.88 ± 0.07
Maggioni etal. [58] All Volunteer Players Semi-professional 1.04 ± 0.05 1.77 ± 0.04 3.10 ± 0.12
Montgomery etal. [28] All Australian State Level Semi-professional 3.09 ± 0.10
Guard Australian State Level Semi-professional 3.04 ± 0.07
Forward Australian State Level Semi-professional 3.13 ± 0.13
Centre Australian State Level Semi-professional 3.10 ± 0.09
Pliauga etal. [39] All Lithuanian National Basketball League Collegiate 2.98 ± 0.32
Pliauga etal. [86] All Lithuanian National Basketball League Collegiate 1.80 ± 0.03
Pojskić etal. [87] Perimeter Bosnia and Herzegovina D1 Professional 3.14 ± 0.09
Pojskić etal. [89] Perimeter Bosnian Premier League Professional 3.14 ± 0.09
Poole etal. [112] All Australian State level QBL Semi-professional 1.14 ± 0.07 1.90 ± 0.10
Ramirez-Campillo etal. [29] All SCCSBL Collegiate 3.00 ± 0.11
Rodriguez-Rosell etal. [91] All Spanish Liga EBA D4 Semi-professional 1.84 ± 0.10 3.20 ± 0.16
Scanlan etal. [21] All Australian State Level Semi-professional 1.07 ± 0.07 1.83 ± 0.10 3.16 ± 0.19
Scanlan etal. [4] Backcourt Australian State Level Semi-professional 1.05 ± 0.03 1.78 ± 0.05 3.08 ± 0.12
Frontcourt Australian State Level Semi-professional 1.10 ± 0.09 1.87 ± 0.13
Scanlan etal. [30] All Australian State Level Semi-professional 3.24 ± 0.22
2.97 ± 0.06
Shalfawi etal. [93] All Professional Level Norway Professional 1.88 ± 0.21 3.20 ± 0.33
Townsend etal. [111] All Collegiate D1 United States Collegiate 3.31 ± 0.151080
Xie etal. [95] All NCAA D1 university and club teams Collegiate 5.67 ± 0.17m/s 7.94 ± 0.45m/s
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1507
Testing Methods and Physical Characteristics of Male Basketball Players
(Table10). Only two studies [70, 71] reported back squat
1RM loads in semi-professional players (149–157kg), while
one study [65] assessed back squat 1RM load in representa-
tive players. No studies reported back squat performance in
amateur players or relative to playing position. All additional
strength tests and outcome variables are reported in Table8
of the ESM, while the bench press and squat outcome vari-
ables reported in individual studies are shown in Table10.
Reliability statistics for each of the strength tests described
in Table10 are provided in Table13 of the ESM.
3.12 Anaerobic Capacity
Anaerobic capacity was assessed in 35 studies (26%) of the
137 studies in this review, using 20 different tests (Table9
of the ESM). The most frequently implemented tests were
the WAnT (nine studies, 26% of studies assessing anaero-
bic capacity) [61, 98, 109, 114, 117, 125–128], the RAST
(six studies, 18% of studies assessing anaerobic capac-
ity) [87–89, 99, 100, 129], and the full court shuttle run
(five studies, 14% of studies assessing anaerobic capacity)
[28, 51, 58, 116, 125]. Peak power, mean power, fatigue
index, and time were the most reported outcome variables
(Table11). Performance during the WAnT was reported in
seven studies [61, 109, 117, 125–128] at the professional
level (mean power: 683–823W, peak power: 951–1085W,
and fatigue index: 43–60%). However, only one study
reported WAnT performance each in representative [114]
and collegiate [114] players, while two studies [98, 125]
were observed at the amateur level (Table11). No studies
reported WAnT performance in semi-professional players.
Two studies [109, 126] reported WAnT performance accord-
ing to playing position (guards: peak power: 11–13W/kg,
fatigue index: 48–64%, forwards: peak power: 11–13W/kg,
fatigue index: 43–58%, centres: 10–11W/kg, fatigue index:
44–56%). The RAST was only reported in professional play-
ers [87–89, 99, 100, 129], with mean peak power ranging
between 761 and 957W and mean power between 608 and
772W. Two studies [88, 129] reported RAST performance
according to playing position. Four studies used the full
court shuttle run, with professional [125], semi-professional
[28, 58], collegiate [51] and amateur [125] players assessed
(Table11). The full court shuttle run was only reported rela-
tive to playing position in one study [28] consisting of semi-
professional players (Table11). Reliability statistics for each
of the anaerobic capacity tests described in Table11 are
provided in Table13 of the ESM.
3.13 Aerobic Capacity
Aerobic capacity was assessed in 57 (42%) of the 137 studies
included in this review, with 14 different tests used (Table10
of the ESM). Incremental treadmill tests (17 studies, 30%
of studies assessing aerobic capacity), which involved the
Bruce [105, 120, 130] and various incremental running pro-
tocols [27, 57–59, 90, 94, 121, 125, 126, 131–135], as well
as the Yo-Yo IRL1 (14 studies, 25% of studies assessing
aerobic capacity) [4, 16, 21, 28, 55, 58, 60, 63, 65, 67, 72,
136–138] and MSFT (eight studies, 14% of studies assessing
aerobic capacity) [51, 61, 79, 84, 87–89, 107] were the most
frequently used tests. The most common outcome variable
reported from aerobic testing was maximum oxygen uptake
(VO2max) [Table10 of the ESM]. However, if during a maxi-
mal test the criteria for VO2max was not achieved, VO2peak
was reported as the outcome variable [27, 131, 134].
Mean aerobic capacity during incremental treadmill tests
ranged from 42 to 61mL/kg/min across studies (Table12).
The mean aerobic capacity of professional players ranged
between 42 and 61mL/kg/min. Only one study [135]
assessed aerobic capacity in semi-professional players using
an incremental treadmill test, while no studies assessed rep-
resentative players. Mean aerobic capacity in collegiate play-
ers ranged between 50 and 58mL/kg/min. Aerobic capacity
in amateur players were only assessed in two studies [125,
135] using an incremental treadmill test. When observing
aerobic capacity according to playing position using incre-
mental treadmill tests, only professional player data were
apparent [27, 90, 121, 126, 131] with mean aerobic capacity
in guards ranging between 50 and 58mL/kg/min, in for-
wards between 46 and 58mL/kg/min and in centres between
42 and 58mL/kg/min.
Estimated VO2max from the MSFT ranged from 42 to
64ml/kg/min, while the number of shuttles completed were
between 66 and 106 across studies (Table12). The VO2max
of professional players ranged from 42 to 64mL/kg/min
using the MSFT. Only one study reported VO2max during the
MSFT each in semi-professional [107] and collegiate [61]
players (Table12). No studies reported MSFT in representa-
tive or amateur players. Mean estimated VO2max relative to
playing position using the MSFT was only reported in pro-
fessional players [79, 84, 88] with guards (45–64mL/kg/
min), forwards (43–62mL/kg/min) and centres (42–58mL/
kg/min) showing similar data.
Mean estimated VO2max derived during the Yo-Yo IRL1
ranged between 47 and 60mL/kg/min, while mean dis-
tances reached were between 636 and 2447m across stud-
ies (Table12). The VO2max of professional players using
the Yo-Yo IRL1 (47–60mL/kg/min) was only reported in
three studies [65, 67, 72], while the mean distance covered
ranged between 1120 and 2389m. The VO2max of semi-
professional players using the Yo-Yo IRL1 (48–52mL/kg/
min) was reported in three studies [4, 21, 60], while mean
distances covered ranged from 996 to 2265m. VO2max was
only observed in one study using the Yo-Yo IRL1 in repre-
sentative players [65] (Table12). No studies used the Yo-Yo
IRL1 to estimate VO2max in collegiate players, while two
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1508 M.Morrison et al.
Table 8 COD speed test performance according to playing position and competition level in adult male basketball players
Data presented as mean ± standard deviation
88–89 data collected from collegiate team during the 1988–90 season, 89–90 data collected from collegiate team during the 1989–90 season,
90–91 ata collected from collegiate team during the 1990–91 season, 91–92 data collected from collegiate team during the 1991–2 season, Back-
court players guards, BUSA British Universities Sports Association, COD change-of-direction, CODST Change-of-Direction Speed Test, D1
Division one competition, D2 Division two competition, D4 Division four competition, Frontcourt players forwards and centres, Liga EBA Liga
Study Playing position Competition level Category Test Time (s)
Alembaroglu [61] All Turkish D1 Professional Agility T-Te st 9.25 ± 0.46
Asadi etal. [97] All Provincial D1 Italy Amateur Agility T-Te st 12.00 ± 0.56
Barrera-Domínguez etal. [64] All Spanish National Division Professional Modified T-Test 6.49 ± 0.34
Ben Abdelkrim etal. [65] All (U20) Tunisian National Team Representative Agility T-Test 10.05 ± 0.44
All Tunisian National Team Professional Agility T-Test 9.99 ± 0.40
Chaouachi etal. [67] All Tunisian National Team Professional Agility T-Te st 9.70 ± 0.20
Delextrat and Cohen [114] All BUSA D1 and D2 Collegiate – Representative Agility T-Tes t 9.49 ± 0.56
All BUSA D1 Representative Agility T-Test 9.21 ± 0.24
All BUSA D2 Collegiate Agility T-Test 9.78 ± 0.59
Freitas etal. [70] All Spanish Liga EBA D4 Semi-professional Agility T-Tes t 9.52 ± 0.63
Freitas etal. [71] All Spanish Liga EBA D4 Semi-professional Agility T-Tes t 9.71 ± 0.67
Gomes etal. [72] All PSBC Professional Agility T-Tes t 9.28 ± 0.46
Hoffman etal. [102] All NCAA D1 Collegiate Agility T-Te st 8.92 ± 0.30
Hoffman etal. [103] All NCAA D1 Collegiate Agility T-Te st 9.18 ± 0.54
Hoffman etal. [104] All 88–89 NCAA D1 Collegiate Agility T-Test 9.11 ± 0.46
All 89–90 NCAA D1 Collegiate Agility T-Test 8.94 ± 0.34
All 90–91 NCAA D1 Collegiate Agility T-Test 9.00 ± 0.45
All 91–92 NCAA D1 Collegiate Agility T-Test 9.15 ± 0.41
Köklü etal. [79] All Turkish D1 Professional Agility T-Te st 9.49 ± 0.61
All Turkish D2 Professional Agility T-Tes t 9.76 ± 0.57
All Turkish D1 and D2 Professional Agility T-Test 9.61 ± 0.57
Guard Turkish D1 and D2 Professional Agility T-Te st 9.24 ± 0.56
Forward Turkish D1 and D2 Professional Agility T-Test 9.48 ± 0.46
Centre Turkish D1 and D2 Professional Agility T-Tes t 10.04 ± 0.35
Lehnert etal. [108] All Czech First League Professional Agility T-Te st 9.35 ± 0.49
Maggioni etal. [58] All Volunteer Players Semi-professional Agility T-Tes t 9.8 ± 0.2
Pojskić etal. [89] Perimeter Bosnia and Herzegovina D1 Professional Agility T-Te st 10.48 ± 0.41
Poole etal. [112] All Australian State Level Semi-professional Agility T-Tes t 10.90 ± 0.51
Sekulic etal. [49] Guard Bosnia and Herzegovina D1 and D2 Professional Agility T-Test 8.96 ± 0.37
Forward Bosnia and Herzegovina D1 and D2 Professional Agility T-Te st 8.84 ± 0.34
Centre Bosnia and Herzegovina D1 and D2 Professional Agility T-Test 9.73 ± 0.50
All Bosnia and Herzegovina D1 Professional Agility T-Test 9.02 ± 0.49
All Bosnia and Herzegovina D2 Professional Agility T-Test 9.14 ± 0.43
Dawes and Spiteri [51] All NCAA D2 Collegiate Lane Agility Test 11.24 ± 0.54
Lockie etal. [3] All NCAA D1 Collegiate Lane Agility Test 10.42 ± 0.61
Frontcourt NCAA D1 Collegiate Lane Agility Test 10.95 ± 0.78
Backcourt NCAA D1 Collegiate Lane Agility Test 10.16 ± 0.33
Townsend etal. [111] All Collegiate D1 United States Collegiate Lane Agility Test 11.80 ± 0.90
Lockie etal. [113] All Semi-Professional Semi-professional COD Left foot start 1.88 ± 0.09
All Semi-Professional Semi-professional COD Right foot start 1.88 ± 0.14
All Recreational Amateur COD Left foot start 1.94 ± 0.12
All Recreational Amateur COD Right foot start 1.96 ± 0.14
Pehar etal. [85] All Bosnia and Herzegovina D1 Professional Y-COD 1.68 ± 0.15
Scanlan etal. [60] All Australian State Level Semi-professional Y-CODST 1.64 ± 0.10
All STARTERS Australian State Level Semi-professional Y-CODST 1.65 ± 0.11
All NON−STARTERS Australian State Level Semi-professional Y-CODST 1.63 ± 0.10
Scanlan etal. [21] All Australian State Level Semi-professional Y-CODST 1.64 ± 0.10
Scanlan etal. [4]Backcourt Australian State Level Semi-professional Y-CODST 1.67 ± 0.10
Frontcourt Australian State Level Semi-professional Y-CODST 1.61 ± 0.11
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1509
Testing Methods and Physical Characteristics of Male Basketball Players
studies [16, 137] reported distance using the Yo-Yo IRL1 in
amateur players (636–1671m). Yo-Yo IRL1 performance
relative to playing position was only reported in semi-profes-
sional players using estimated VO2max [4] and distance [28],
and in one study [16], which reported the mean across ama-
teur, semi-professional, and professional players (Table12).
Reliability statistics for each of the aerobic capacity tests
described in Table12 are provided in Table13 of the ESM.
4 Discussion
The aims of this systematic review were to (1) identify tests
and outcome variables used to assess physical characteristics
in adult male basketball players across all competition levels,
(2) report a summary of anthropometric, muscular power,
linear speed, change-of-direction speed, agility, strength,
anaerobic capacity, and aerobic capacity in adult male bas-
ketball players based on playing position and competition
level, and (3) introduce a framework outlining recommended
testing approaches to quantify physical characteristics in
adult male basketball players. As expected, the number of
tests and outcome variables reported reveal extensive vari-
ability in how the physical characteristics of adult male bas-
ketball players are tested. An indirect finding of this review
was the wide range of approaches and variability in proce-
dures and calculations of basic outputs (e.g., jump height
measured through flight time vs take-off velocity). Addition-
ally, the validity and reliability statistics of commonly used
tests were often not reported. Thus, it is difficult to draw firm
conclusions about the physical characteristics of basketball
players. The wide-ranging physical performances observed
were likely influenced by the choice of test and methodology
employed by researchers. These issues have made it difficult
to establish consensus based on the basketball literature. To
improve the overall understanding of the physical charac-
teristics required to excel at different competition levels in
adult male basketball, researchers and practitioners should
consider: (1) the validity, reliability and standardisation of
tests being employed; (2) the appropriateness and specificity
of the tests being implemented; and (3) the ability of testing
information to discern players of different playing positions
and competition levels. It is important to ensure outcome
variables gathered are valid and reliable in order to detect
meaningful changes over time. As each test may have an
inherent level of variability or ‘noise’, discerning changes
that are practically relevant is critical. Particularly when
using data to quantify player progression, or to use perfor-
mance data gathered during a test to guide rehabilitation, or
when monitoring performance and fatigue. Furthermore, it
is advised that researchers attempt to align with practitioners
to continue to develop standardised testing batteries (e.g.,
NBA draft combine) that optimally support the profiling of
adult male basketball players.
4.1 Tests andOutcome Variables
Anthropometric values of height and body mass were
reported in all 114 studies eligible to address the second
aim of this review. Body composition was primarily meas-
ured using low-cost, easy to implement tests, such as sum
of skinfold measurements. Furthermore, muscular power
was most commonly measured indirectly with a combina-
tion of three bilateral jumps (i.e., CMJ, CJ and SJ) that
provide insight into varying speed-strength jump quali-
ties [78, 139]. Linear sprint performances were primarily
reported over distances of 5, 10, and 20m. Of those three
distances, 5m, which is reflective of an athlete’s abil-
ity to accelerate and is similar to movements frequently
encountered during match-play, was the least reported.
The Agility T-Test was the most commonly used test to
assess change-of-direction speed, potentially because of
the ease of implementation and inclusion of basketball-
specific lateral movements. However, in recent years,
collegiate-level players from the NCAA were observed
using the Lane Agility Test to assess change-of-direction
speed [3, 51]. This trend may be attributed to researchers
and practitioners implementing tests that align with the
testing protocols adopted by the NBA Draft Combine.
Agility tests were the least reported category of test in the
literature, and despite all studies assessing agility using a
similar Y-Shape design the distances covered and stimuli
used varied. Strength tests primarily incorporated bench
press and back squat 1RM protocols. The frequency of
strength testing observations was less than jump, linear
sprint, change-of-direction speed, anaerobic capacity, and
aerobic capacity tests, which may be due to varying levels
of resistance training competency, biomechanical con-
straints introduced by the typically larger anthropometric
values of basketball players, and the residual fatigue often
accumulated by maximal strength testing. The anaerobic
capacity of basketball players was tested predominantly
Española de Baloncesto Aficionado, NCAA National Collegiate Athletic Association, perimeter point guard, shooting guard and small forward
positions, PSBC Paulista State Basketball Championships, U20 under 20years of age competition
Modified T-Test requires players to sprint 5m forward, shuffle 2.5m laterally to the left, then shuffle 5m to the right, shuffle 2.5m to the left
and then backpedal to the starting position
Table 8 (continued)
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1510 M.Morrison et al.
Table 9 Agility performance according to playing position and competition level in adult male basketball players
Data presented as mean ± standard deviation
Backcourt players guards, COD change-of-direction, D1 Division one competition, D2 Division two competition, Frontcourt players forwards and centres, Y-COD Y-shaped Change-of-Direc-
tion, Y-CODST Y-Shaped Change-of-Direction Speed Test
Study Playing position Competition level Category Test Time (s) Response time (ms) Decision-mak-
ing time (ms)
Jeffries etal. [118] All Australian State Level Semi-professional Reactive COD left leg start 2.77 ± 0.17
All Australian State Level Semi-professional Reactive COD right leg start 2.75 ± 0.19
Lockie etal. [113] All Australian State Level Semi-professional Reactive COD left leg start 2.52 ± 0.17
All Australian State Level Semi-professional Reactive COD right leg start 2.53 ± 0.19
All Australia Recreational Competition Amateur Reactive COD left leg start 2.67 ± 0.13
All Australia Recreational Competition Amateur Reactive COD right leg start 2.70 ± 0.12
Pehar etal. [85] All Bosnia and Herzegovina D1 Professional Reactive Y-COD 1.99 ± 0.15
Scanlan etal. [4] Backcourt Australian State Level Semi-professional Reactive Agility Test 2.1 ± 0.13 367 ± 140 128 ± 30
Frontcourt Australian State Level Semi-professional Reactive Agility Test 2.09 ± 0.17 368 ± 137 129 ± 42
Scanlan etal. [21] All Australian State Level Semi-professional Reactive Agility Test 2.09 ± 0.04 367 ± 132 128 ± 35
Scanlan etal. [60] All Australian State Level Semi-professional Reactive Agility Test 2.09 ± 0.14 367 ± 132 128 ± 35
All STARTERS Australian State Level Semi-professional Reactive Agility Test 2.00 ± 0.12 308 ± 101 111 ± 27
All NON−STARTERS Australian State Level Semi-professional Reactive Agility Test 2.18 ± 0.09 427 ± 141 146 ± 35
Sekulic etal. [49]Guard Bosnia and Herzegovina D1 and D2 Professional Reactive Y-COD dominant leg start 1.94 ± 0.14
Forward Bosnia and Herzegovina D1 and D2 Professional Reactive Y-COD dominant leg start 1.95 ± 0.17
Centre Bosnia and Herzegovina D1 and D2 Professional Reactive Y-COD dominant leg start 2.04 ± 0.17
All Bosnia and Herzegovina D1 Professional Reactive Y-COD dominant leg start 1.93 ± 0.13
All Bosnia and Herzegovina D2 Professional Reactive Y-COD dominant leg start 2.03 ± 0.19
Guard Bosnia and Herzegovina D1 and D2 Professional Reactive Y-COD non-dominant leg start 2.08 ± 0.15
Forward Bosnia and Herzegovina D1 and D2 Professional Reactive Y-COD non-dominant leg start 2.10 ± 0.13
Centre Bosnia and Herzegovina D1 and D2 Professional Reactive Y-COD non-dominant leg start 2.15 ± 0.18
All Bosnia and Herzegovina D1 Professional Reactive Y-COD non-dominant leg start 2.06 ± 0.14
All Bosnia and Herzegovina D2 Professional Reactive Y-COD non-dominant leg start 2.16 ± 0.17
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1511
Testing Methods and Physical Characteristics of Male Basketball Players
Table 10 Bench press and back squat 1RM results according to playing position and competition level in adult male basketball players
Data are presented as mean ± standard deviation
1RM one repetition maximum, 88–89 data collected from collegiate team during the 1988–90 season, 89–90 data collected from collegiate team during the 1989–90 season, 90–91 data col-
lected from collegiate team during the 1990–91 season, 91–92 data collected from collegiate team during the 1991–92 season, BUSA British Universities Sports Association, D1 Division one
competition, D2 Division two competition, D4 Division four competition, Liga ACB Liga Endesa Asociación de Clubs de Baloncesto, Liga EBA Liga Española de Baloncesto Aficionado, NBA
National Basketball Association, NCAA National Collegiate Athletic Association, PSBC Paulista State Basketball Championships, U20 under 20years of age competition, a indicates half squat,
h indicates measured using hydraulic isokinetic bench press, (NBA) indicates collegiate player who went on to play in the NBA after college, (Pro) indicates collegiate player who went on to play
professionally outside of the NBA after college, S/M indicates Smith Machine, V indicates 1RM estimated using velocity measures, ^ indicates 1RM calculated from 3RM testing
Study Playing position Competition level Category Bench press (kg) Squat (kg)
Balabinis etal. [98] All Greek undergraduate-aged teams Amateur 85.2 ± 0.4
Balsalobre-Fernandez etal. [99] All Spanish Pro Liga ACB Professional 101.9 ± 12.5S/M
Ben Abdelkrim etal. [65] All (U20) Tunisian National Team Representative 76.7 ± 8.9 183.3 ± 17.8
All Tunisian National Team Professional 87.7 ± 14.3 201.5 ± 16.2
Cabarkapa etal. [124] All NCAA D1(NBA) Collegiate 153.3 ± 26.2
All NCAA D1(Pro) Collegiate 144.6 ± 23.8
Chaouachi etal. [67] All Tunisian National Team Professional 79.0 ± 6.0 143.0 ± 13.4a
Dawes and Spiteri [51] All NCAA D2 Collegiate 96.2 ± 17.0^ 134.4 ± 19.3^
de Sousa Fortes etal. [59] All State Basketball Championship Brazil Professional 187.9 ± 22.9S/M
Delextrat and Cohen [114] All BUSA D1 and D2 Representative-Collegiate 91.9 ± 25.6
First Team BUSA D1 Representative 101.3 ± 26.9
Second Team BUSA D2 Collegiate 82.5 ± 24.0
Freitas etal. [70] All Spanish Liga EBA D4 Semi-professional 85.8 ± 20.3S/M,v 157.4 ± 22S/M,a
Freitas etal. [71] All Spanish Liga EBA D4 Semi-professional 76.4 ± 14.2S/M,v 149.1 ± 23.0S/M,a
Gillam [119] All NCAA D2 Collegiate 76.3 ± 11.3 115.9 ± 18.0
Gomes etal. [72] All PSBC Professional 105.9 ± 18.3
Hoffman etal. [103] All NCAA D1 Collegiate 84.1 ± 12.2 119.4 ± 25.2
Hoffman etal. [102] All NCAA D1 Collegiate 87.4 ± 14.3 140.7 ± 21.0
Hoffman etal. [104] All 88–89 NCAA D1 Collegiate 88.1 ± 14.5 143.4 ± 24.3
All 89–90 NCAA D1 Collegiate 97.0 ± 19.2 145.9 ± 24.4
All 90–91 NCAA D1 Collegiate 101.6 ± 20.2 155.9 ± 18.6
All 91–92 NCAA D1 Collegiate 102.1 ± 19.1
Hunter etal. [120] All Collegiate U.S Collegiate 79.5 ± 11.8
Hunter etal. [105] All NCAA D1A Collegiate 91.4 ± 18.5 139.3 ± 7.4
Kariyawasam etal. [56] All National Level Sri Lanka Professional 111.6 ± 64.1
Parr etal. [121]Guard NBA Professional 86.6 ± 14.9h
Forward NBA Professional 101.1 ± 20.8h
Centre NBA Professional 69.9 ± 0.0h
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1512 M.Morrison et al.
Table 11 Repeated sprint, running-based anaerobic sprint test and Wingate anaerobic cycle test performance according to playing position and
competition level in adult male basketball players
Study Playing position Competition level Category Test Variable Outcome
Dawes and Spiteri [51] All NCAA D2 Collegiate Full court shuttle run Time (s) 27.8 ± 0.9
Fatouros etal. [125] All Greek D2 Competition Professional Full court shuttle run Time (s) 27.4 ± 0.7
All Greek Recreational Amateur Full court shuttle run Time (s) 29.2 ± 0.9
Maggioni etal. [58] All Volunteer Players Semi-professional Full court shuttle run Time (s) 27.8 ± 0.8
Montgomery etal. [28] All Australian State Level Semi-professional Full court shuttle run Time (s) 27.5 ± 1.2
Guard Australian State Level Semi-professional Full court shuttle run Time (s) 26.9 ± 0.9
Forward Australian State Level Semi-professional Full court shuttle run Time (s) 27.9 ± 1.4
Centre Australian State Level Semi-professional Full court shuttle run Time (s) 27.6 ± 1.4
Pojskić etal. [87] All Bosnian Premier League Professional RAST Maximal power (W) 761 ± 125
Mean power (W) 620 ± 99.4
Fatigue index (W/s) 8.2 ± 1.4
Pojskić etal. [88] Guard Bosnian Premier League Professional RAST Maximal power (W) 773 ± 129
Mean power (W) 635 ± 110
Fatigue index (W/s) 8.1 ± 2.5
Forward Bosnian Premier League Professional RAST Maximal power (W) 762 ± 123
Mean power (W) 608 ± 89.6
Fatigue index (W/s) 8.8 ± 2.7
Centre Bosnian Premier League Professional RAST Maximal power (W) 858 ± 109
Mean power (W) 713 ± 69.5
Fatigue index (W/s) 10.5 ± 2.24
Pojskić etal. [89] All Bosnian and Herzego-
vina D1
Professional RAST Maximal power (W) 761 ± 125
Mean power (W) 620 ± 99.4
Fatigue index (W/s) 8.2 ± 1.4
Balsalobre-Fernandez
etal. [99]
All Spanish Pro Liga ACB Professional RAST Peak power (W) 957 ± 194
Mean power (W) 772 ± 126
Fatigue index (%) 33.1 ± 8.0
Balsalobre-Fernandez
etal. [100]
All Spanish Pro Liga ACB Professional RAST Peak power (W) 889 ± 230WPD
Mean power (W) 737 ± 134WPD
Fatigue index (%) 32.4 ± 7.2WPD
de Araujo etal. [129] All Elite National Team and
League Brazil
Professional RAST Peak power (W) 901 ± 39.1
Mean power (W) 701 ± 22.7
Fatigue index (%) 41.5 ± 2.5
Guard Elite National Team and
League Brazil
Professional RAST Peak power (W) 853 ± 59.0
Mean power (W) 683 ± 49.0
Fatigue index (%) 42.1 ± 4.5
Forward Elite National Team and
League Brazil
Professional RAST Peak power (W) 923 ± 79.8
Mean power (W) 700 ± 40.7
Fatigue index (%) 40.6 ± 4.4
Centre Elite National Team and
League Brazil
Professional RAST Peak power (W) 912 ± 42.0
Mean power (W) 717 ± 26.4
Fatigue index (%) 42.1 ± 4.3
Alemdaroglu [61] All Turkish D1 Professional Wingate Anaerobic Cycle Test Peak power (W)
Mean power (W)
Fatigue index (%)
955 ± 118
703 ± 79.3
54.7 ± 7.3
Balabinis etal. [98] All Undergraduate Teams
Greece
Amateur Wingate Anaerobic Cycle Test Peak power (W) 841 ± 92.4
Delextrat and Cohen
[114]
All BUSA D1 Representative Wingate Anaerobic Cycle Test Peak power (W/kg) 10.2 ± 0.9*
Mean power (W/kg) 8.2 ± 0.9*
Fatigue index (%) 57.4 ± 14.9
All BUSA D3 Collegiate Wingate Anaerobic Cycle Test Peak power (W/kg) 10 ± 0.9*
Mean power (W/kg) 7.8 ± 1.1*
Fatigue index (%) 47.2 ± 15.1
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1513
Testing Methods and Physical Characteristics of Male Basketball Players
with repeated sprint protocols varying in distance or a
resisted cycling WAnT test. Aerobic capacity was most
frequently assessed using running incremental treadmill
tests or estimated using the Yo-Yo IRL1 and the MSFT.
The incremental treadmill test was primarily reported at
the professional level, which may suggest the resources
required to undertake the incremental treadmill test may
not be feasible to obtain and implement across all com-
petition levels.
The wide variety of testing approaches reported across
studies make it challenging to establish normative data or
identify minimum thresholds for physical characteristics in
adult male basketball players. Researchers and practitioners
are encouraged to diligently consider the tests they select
when assessing physical characteristics in players, as each
Table 11 (continued)
Study Playing position Competition level Category Test Variable Outcome
Fatouras etal. [125] All Greek D2 Competition Professional Wingate Anaerobic Cycle Test Peak power (W/kg) 11.2 ± 2.1
Mean power (W/kg) 9.3 ± 0.9
All Greek Recreational Amateur Wingate Anaerobic Cycle Test Peak power (W/kg) 9.7 ± 1.9
Mean power (W/kg) 7.2 ± 2.1
Harbili [128] All Turkish National League
D3
Professional Wingate Anaerobic Cycle Test Peak power (W) 951.6 ± 86.9
Peak power (W/kg) 10.3 ± 1.4
Mean power (W) 683.7 ± 40.5
Mean power (W/kg) 7.4 ± 0.8
Fatigue index (%) 59.9 ± 6.3
Nikolaidis etal. [109] Guard Italian First League Professional Wingate Anaerobic Cycle Test Peak power (W) 992 ± 155
Peak power (W/kg) 11.4 ± 1.1
Mean power (W) 737 ± 78
Mean power (W/kg) 8.5 ± 0.7
Fatigue index (%) 47.5 ± 6.6
Forward Italian First League Professional Wingate Anaerobic Cycle Test Peak power (W) 1052 ± 93
Peak power (W/kg) 11.1 ± 1.1
Mean power (W) 823 ± 94
Mean power (W/kg) 8.7 ± 1.1
Fatigue index (%) 42.9 ± 4.7
Centre Italian First League Professional Wingate Anaerobic Cycle Test Peak power (W) 1085 ± 93
Peak power (W/kg) 10 ± 1.1
Mean power (W) 807 ± 91
Mean power (W/kg) 7.4 ± 0.8
Fatigue index (%) 44.4 ± 5.5
Popadic Gacesa etal.
[127]
All Elite Serbian Players Professional Wingate Anaerobic Cycle Test Peak power (W)
Peak power (W/kg)
Mean power (W)
Mean power (W/kg)
1001 ± 150
10.7 ± 1.7
669 ± 77.1
7.2 ± 1
Sallet etal. [126] All French D1 and D2 Professional Wingate Anaerobic Cycle Test Peak power (W/kg) 12.2 ± 2.7
Fatigue index (%) 58.9 ± 13.5
Guards French D1 and D2 Professional Wingate Anaerobic Cycle Test Peak power (W/kg)
Fatigue index (%)
13.1 ± 1.7
63.8 ± 14.7
Forwards French D1 and D2 Professional Wingate Anaerobic Cycle Test Peak power (W/kg) 12.7 ± 3.5
Fatigue index (%) 58.1 ± 9.3
Centres French D1 and D2 Professional Wingate Anaerobic Cycle Test Peak power (W/kg) 11.1 ± 2.1
Fatigue index (%) 56.3 ± 15.7
Soslu etal. [117] All Turkish Professional
Competition
Professional Wingate Anaerobic Cycle Test Peak power (W)
Peak power (W/kg)
Mean power (W)
Mean power (W/kg)
849 ± 128
12.4 ± 3.0
681 ± 86
8.7 ± 1.2
Data are presented as mean ± standard deviation
BUSA British Universities Sports Association, D1 Division one competition, D2 Division two competition, D3 Division three competition, Liga
ACB Liga Endesa Asociación de Clubs de Baloncesto, NCAA National Collegiate Athletic Association, RAST Running-based Anaerobic Sprint
Test, WPD indicates data retrieved using WebPlotDigitizer
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1514 M.Morrison et al.
Table 12 Maximum oxygen uptake and distance variables during aerobic capacity tests according to playing position and competition level in adult male basketball players
Study Playing position Competition level Category Test VO2max (ml/kg/min) Distance (m)
Bolonchuk etal. [130] All U.S. Collegiate Collegiate Incremental Treadmill Test 53.8 ± 4.5
Boone and Bourgois [27] Point guard Belgian D1 Professional Incremental Treadmill Test 57.4 ± 4.8peak
Shooting guard Belgian D1 Professional Incremental Treadmill Test 55.3 ± 3.6peak
Small forward Belgian D1 Professional Incremental Treadmill Test 52.9 ± 5.6peak
Power forward Belgian D1 Professional Incremental Treadmill Test 50.4 ± 5.2peak
Centre Belgian D1 Professional Incremental Treadmill Test 50.9 ± 5.2peak
Boone etal. [131] Guard Belgian D1 Professional Incremental Treadmill Test 60.3 ± 3.7peak
Forward Belgian D1 Professional Incremental Treadmill Test 56.4 ± 4.1peak
Centre Belgian D1 Professional Incremental Treadmill Test 52.7 ± 3.4peak
Chatzinikolaou etal. [132] All National Division Greece Professional Incremental Treadmill Test 54.5 ± 2.9
de Sousa Fortes etal. [59] All State Basketball Championship
Brazil
Professional Incremental Treadmill Test 52.6 ± 6.1
Dragonea etal. [133] All Greek A1 and A2 Leagues Professional Incremental Treadmill Test 51.6 ± 3.8
Fatouros etal. [125] All Greek D2 Professional Incremental Treadmill Test 53.4 ± 8.5
All Greek Recreational Competition Amateur Incremental Treadmill Test 47.6 ± 6.9
Hunter etal. [120] All U.S College Collegiate Incremental Treadmill Test 49.7 ± 8.5
Hunter etal. [105] All NCAA D1A Collegiate Incremental Treadmill Test 50.0 ± 7.7
Maggioni etal. [58] All Volunteer players Semi-professional Incremental Treadmill Test 54.2 ± 4.1
McInnes etal. [134] All NBL Professional Incremental Treadmill Test 60.7 ± 8.6peak
Metaxas etal. [135] All Greek National League D1 Professional Incremental Treadmill Test 51.3 ± 4.1
All Greek National League D2 Professional Incremental Treadmill Test 50.4 ± 5.4
All Greek National League D3 Semi-professional Incremental Treadmill Test 47.8 ± 5.3
All Greek National League D4 Amateur Incremental Treadmill Test 49.1 ± 5.6
Narazaki etal. [57] All NCAA D1 Collegiate Incremental Treadmill Test 57.5 ± 8.2
Parr etal. [121] Guard NBA Professional Incremental Treadmill Test 50.0 ± 5.4
Forward NBA Professional Incremental Treadmill Test 45.9 ± 4.3
Centre NBA Professional Incremental Treadmill Test 41.9 ± 4.9
Ponce-González etal. [90] All Spanish Pro Liga ACB Professional Incremental Treadmill Test 57.7 ± 5.5
Guard Spanish Pro Liga ACB Professional Incremental Treadmill Test 58.0 ± 5.0
Forward Spanish Pro Liga ACB Professional Incremental Treadmill Test 57.5 ± 4.6
Centre Spanish Pro Liga ACB Professional Incremental Treadmill Test 57.5 ± 8.7
Perimeter Spanish Pro Liga ACB Professional Incremental Treadmill Test 57.0 ± 4.3
Inside Spanish Pro Liga ACB Professional Incremental Treadmill Test 58.7 ± 7.5
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1515
Testing Methods and Physical Characteristics of Male Basketball Players
Table 12 (continued)
Study Playing position Competition level Category Test VO2max (ml/kg/min) Distance (m)
Sallet etal. [126] All French League D1 and D2 Professional Incremental Treadmill Test 54.9 ± 7.2
Guard French League D1 and D2 Professional Incremental Treadmill Test 57.5 ± 9.2
Forward French League D1 and D2 Professional Incremental Treadmill Test 55.2 ± 6.5
Centre French League D1 and D2 Professional Incremental Treadmill Test 52.9 ± 6.2
All French League D1 Professional Incremental Treadmill Test 53.7 ± 6.7
All French League D2 Professional Incremental Treadmill Test 56.5 ± 7.7
Stojanovic etal. [94] All Serbian Professional League Professional Incremental Treadmill Test 51.9 ± 4.1
Aoki etal. [63] All Brazilian National League Professional Yo-Yo IRL1 1120 ± 413
Ben Abdelkrim etal. [65] All (U20) Tunisian National Team Representative Yo-Yo IRL1 55.4 ± 4.6
All Tunisian National Team Professional Yo-Yo IRL1 59.9 ± 5.3
Chaouachi etal. [67] All Tunisian National Team Professional Yo-Yo IRL1 59.1 ± 6.2 2389 ± 616
Ferioli etal. [136] All
All
Italian Serie A and Serie A2
Italian Serie B
Professional
Semi-professional
Yo-Yo IRL1
Yo-Yo IRL1
1669 ± 357
1708 ± 444
Ferioli etal. [16] All Italian Serie A2 Professional Yo-Yo IRL1 2135 ± 356
All Italian Serie B Semi-professional Yo-Yo IRL1 2265 ± 578
All Italian Serie D Amateur Yo-Yo IRL1 1671 ± 370
Guard Italian Serie A-D Amateur – Profes-
sional
Yo-Yo IRL1 2447 ± 427
Forward Italian Serie A-D Amateur – Profes-
sional
Yo-Yo IRL1 2078 ± 350
Centre Italian Serie A-D Amateur – Profes-
sional
Yo-Yo IRL1 1853 ± 524
Ferioli etal. [55] All Italian Serie A2 Professional Yo-Yo IRL1 1765 ± 324
All Italian Serie B Semi-professional Yo-Yo IRL1 1610 ± 330
Gomes etal. [72] All PSBC Professional Yo-Yo IRL1 46.7 ± 2.8
Maggioni etal. [58] All Volunteer Players Semi-professional Yo-Yo IRL1 1445 ± 420
Montgomery etal. [28] All Australian State Level Semi-professional Yo-Yo IRL1 1592 ± 629
Guard Australian State Level Semi-professional Yo-Yo IRL1 1807 ± 701
Forward Australian State Level Semi-professional Yo-Yo IRL1 1372 ± 537
Centre Australian State Level Semi-professional Yo-Yo IRL1 1500 ± 528
Scanlan etal. [137] All Australian State Level Semi-professional Yo-Yo IRL1 1283 ± 362
All Australian Recreational Competi-
tion
Amateur Yo-Yo IRL1 636 ± 297
Scanlan etal. [4] Backcourt Australian State Level Semi-professional Yo-Yo IRL1 51.9 ± 4.8
Frontcourt Australian State Level Semi-professional Yo-Yo IRL1 47.1 ± 5.0
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1516 M.Morrison et al.
Table 12 (continued)
Study Playing position Competition level Category Test VO2max (ml/kg/min) Distance (m)
Scanlan etal. [21] All Australian State Level Semi-professional Yo-Yo IRL1 49.5 ± 5.3
Scanlan etal. [60] Starters Australian State Level Semi-professional Yo-Yo IRL1 48.4 ± 6.6
Non-starters Australian State Level Semi-professional Yo-Yo IRL1 50.6 ± 3.9
Scanlan etal. [138] All Australian Regional and State
level
Semi-professional Yo-Yo IRL1 996 ± 464
Alemdaroğlu [61] All Turkish D1 Professional Multi-Stage Fitness Test 50.6 ± 6.7
Dawes and Spiteri [51] All NCAA D2 Collegiate Multi-Stage Fitness Test 41.8 ± 3.5 66 ± 10SHUT
Köklü etal. [79] All Turkish D1 Professional Multi-Stage Fitness Test 42.5 ± 8.6
All Turkish D2 Professional Multi-Stage Fitness Test 44.5 ± 7.0
Guard Turkish D1 and D2 Professional Multi-Stage Fitness Test 45.4 ± 8.3
Forward Turkish D1 and D2 Professional Multi-Stage Fitness Test 43.3 ± 7.2
Centre Turkish D1 and D2 Professional Multi-Stage Fitness Test 42.1 ± 8.1
Korkmaz and Karahan
[107]
All Turkish D1 Professional Multi-Stage Fitness Test 55.6 ± 2.6
All Turkish D2 Professional Multi-Stage Fitness Test 57.2 ± 2.8
All Turkish D3 Semi-professional Multi-Stage Fitness Test 50.5 ± 4.9
Ostojic etal. [84] All First National League Serbia Professional Multi-Stage Fitness Test 49.8 ± 4.9
Guard First National League Serbia Professional Multi-Stage Fitness Test 52.5 ± 4.8
Forward First National League Serbia Professional Multi-Stage Fitness Test 50.7 ± 2.3
Centre First National League Serbia Professional Multi-Stage Fitness Test 46.3 ± 4.9
Pojskić etal. [88] Guard Bosnian Premier League Professional Multi-Stage Fitness Test 64.4 ± 7.1 106 ± 14SHUT
Forward Bosnian Premier League Professional Multi-Stage Fitness Test 62.4 ± 6.1 102 ± 12SHUT
Centre Bosnian Premier League Professional Multi-Stage Fitness Test 57.9 ± 7.2 93 ± 15SHUT
Pojskić etal. [89] Perimeter Bosnia and Herzegovina D1 Professional Multi-Stage Fitness Test 63.7 ± 6.8
Pojskić etal. [87] Perimeter Bosnian Premier League Professional Multi-Stage Fitness Test 63.7 ± 6.8
Data are presented as mean ± standard deviation
Backcourt players guards, D1 Division one competition, D2 Division two competition, D3 Division three competition, D4 Division four competition, Frontcourt players forwards and centres,
Inside power forward and centre positions, Liga ACB Liga Endesa Asociación de Clubs de Baloncesto, NBA National Basketball Association, NBL Australian National Basketball League, NCAA
National Collegiate Athletic Association, Perimeter point guard, shooting guard and small forward positions, PSBC Paulista State Basketball Championships, U20 players competing in an under
20years of age competition, Yo-Yo IRL1 Yo-Yo Intermittent Recovery Test Level 1, peak indicates VO2peak, SHUT indicates number of shuttles completed
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1517
Testing Methods and Physical Characteristics of Male Basketball Players
test and testing methodology has an inherent level of accu-
racy and reproducibility [140]. For example, when consider-
ing the methodology of jumping tests, a range of technology
with varying levels of accuracy have been used to assess
jump height, including force platforms [16, 61, 71, 110],
three-dimensional cameras [110], contact mats [62, 83, 96],
Vertec [107], and chalk marks on a wall [103, 104]. The
nuances associated with the various methodologies could
influence results and need to be considered when comparing
results between studies [140]. As consensus is reached with
choice of test and methodology employed to measure key
physical characteristics in adult male basketball players, it
will become easier to monitor players and develop meaning-
ful normative physical standards. In this regard, researchers
and practitioners are encouraged to collaborate with FIBA
and national governing bodies to develop standardised test-
ing guidelines for broad application to basketball teams.
Basketball practitioners now have an abundance of pub-
lished tests and methodologies to consider prior to assessing
players. Additionally, there are outcome variables provided
in multiple tests that represent different physical abilities.
For example, jump height during a SJ provides insight
into the ability to express concentric-only force, whereas
jump height during a CMJ reflects the ability to use elas-
tic energy that is generated during the countermovement
[141]. Further, jump height from a running vertical jump
is a measure of jumping performance specific to most com-
mon game situations [142]. Interpreting test results may be
further complicated by multiple methods being available to
calculate the same outcome variable. For instance, modi-
fied reactive strength index is commonly calculated as jump
height divided by contraction time, yet can be calculated
using jump height determined via flight time or impulse
momentum [101]. This example highlights a major con-
cern as variables such as flight time may be manipulated
by a change in movement strategy by players (e.g., tucking
legs on descent) subsequently altering results. Therefore,
there are many aspects of current test selection that can be
improved so all findings can contribute to establishing mean-
ingful normative reference data.
Considering the wide variety of testing options adopted
by basketball researchers and practitioners, relevance to the
sport must be maintained and tests that do not directly trans-
fer to basketball match-play should be carefully considered
prior to implementation. When researchers and practition-
ers are selecting a test, they are encouraged to determine
whether the bioenergetic and biomechanical components of
a test are relevant and applicable to the needs of adult male
basketball players. Furthermore, it is recommended that bas-
ketball researchers and practitioners consult with each other
so that testing approaches can continue to be refined.
Basketball practitioners have several considerations and
constraints at the organisational and team level that may
influence selecting an appropriate testing battery. The
accessibility of resources, technology, the expertise of
staff on hand, availability of players, and influence of addi-
tional stakeholders can all influence the testing procedures
adopted. Once tests are selected, an additional considera-
tion when testing is the motivation of players. It is impor-
tant to ensure players are executing testing with maximal
intent when maximal efforts are required to avoid report-
ing submaximal performances. Providing the appropriate
environment for testing is important as athletes are often
tested for varying purposes (e.g., team selection, pre-sea-
son assessment) and at times, may lack incentive to give
maximal effort. Basketball practitioners are encouraged to
emphasise the importance of maximal effort during testing,
as players who are fitter may appear as more resilient, effec-
tive and desirable for coaches. Despite these constraints,
basketball practitioners are encouraged to select tests that
are able to provide data that can allow for the monitoring
of player progression, ranking or differentiation of players,
and appropriate prescription of subsequent training. Addi-
tionally, basketball researchers and practitioners may wish
to report test outcomes using ratios or indices (e.g., speed
for height, agility to height ratio) that account for individual
anthropometry as this may be beneficial when attempting
to compare players who play across multiple positions. By
scaling outcomes gathered from physical tests, performance
may be able to be normalised and account for differences in
player body size in sports where stature and mass are wide
ranging [143].
4.2 Physical Characteristics
4.2.1 Anthropometry
Taller players with longer wingspans may have the ability
to rebound the ball at greater heights, take up more space
when defending an opponent, and more effectively contest
shots. For a given speed of movement, skill set, and fitness
level, basketball inherently favours taller players as reflected
by anthropometry measures being the most frequently meas-
ured physical characteristics across studies in this review.
When competition levels were grouped by mean team
height, higher level players such as those competing pro-
fessionally were taller than amateur players. However, the
range of mean height observed across studies was similar for
professional, semi-professional, representative, and colle-
giate adult male players. When height was reported relative
to playing position, a clear trend emerged across competi-
tion levels with guards identified as the shortest players, for-
wards being taller than guards, and centres being the tallest
players. Height and wingspan measured at the NBA Draft
Combine have been identified as predictors of future playing
performance in the NBA [144]. However, in many basketball
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1518 M.Morrison et al.
studies, wingspan was scarcely reported [3, 51, 52]. To bet-
ter understand the interaction of player height, wingspan and
performance, basketball researchers and practitioners should
measure and report wingspan alongside height and body
mass as part of a standardised anthropometrical assessment.
Body mass followed a similar trend to height, with broad
ranges observed at most competition levels. Mean body mass
in semi-professional players exhibited the smallest range
across studies of any competition level, possibly owing to
the large representation in this review of players from Aus-
tralian state-level competitions [4, 21, 28, 30, 60, 112, 113,
118, 137, 138, 145]. Furthermore, the body mass of play-
ers at higher competition levels tended to be heavier than
players competing at lower levels likely because of play-
ers at higher levels possessing greater lean body mass and
height. Positional differences in body mass were noted, with
guards being lightest, forwards being heavier than guards,
and centres heaviest [27, 49, 129]. This positional trend in
body mass was apparent in players at the professional level;
however, because of the lack of evidence available, posi-
tional differences in body mass at the semi-professional, rep-
resentative, collegiate, and amateur levels are not yet clear.
4.2.2 Body Composition
Body composition was shown to differ between competition
levels in adult male basketball players. In this regard, semi-
professional, representative, and collegiate players typically
possessed a lower proportion of body fat than amateur play-
ers. Data retrieved from the NBA Draft Combine showed
elite players drafted into the NBA typically exhibit very low
levels of body fat. This finding may be because of higher
level players having more availability for training and greater
access to performance resources (e.g., dietitians and strength
and conditioning coaches) or it may be the case that selectors
for the NBA prefer lean players, as how lean a player is may
have the potential to influence their match-play and abil-
ity to perform basketball skills. However, the comparison
of body fat percentages using skinfold assessments across
studies in this review must be made with caution as the
anatomical landmarks used were not always consistent. For
example, when the sum of three skinfolds was used to cal-
culate body fat percentage, they were taken from the chest,
abdomen, and thigh [53, 56, 57], the triceps, abdomen, and
thigh [4, 21, 60], and the triceps, chest, and subscapular
[59] in different studies. A further consideration regarding
body composition is often different techniques and equations
can be used, leading to differences in body fat estimates.
These variations in methodology may influence the results
presented. When mean body fat percentage was reported
according to playing position, similar ranges were observed
between guards (7–20%), forwards (8–17%), and centres
(7–21%). However, the range of body fat of each position
was noticeably influenced by one study [109], and when data
from this study were excluded, values decreased across play-
ing positions (guards: 7–14%, forwards: 8–15%, and centres:
7–16%). These ranges may be a more appropriate summation
of the body fat percentages in adult male players identified
in this review and suggest body composition may be similar
across playing positions.
A further consideration for basketball researchers and
practitioners when interpreting or comparing results is the
time of testing. For example, players may be assessed at
the commencement of pre-season and record considerably
different results compared with the middle of season, when
they are likely insuperior physical condition. When measur-
ing anthropometry, it is recommended basketball practition-
ers initiate their testing batteries with measures of height,
body mass, body composition, and wingspan as these meas-
urements may change after the initiation of other tests (e.g.,
fluid loss from an aerobic capacity test). Throughout this
review, the phase of the basketball season and where testing
occurred was often not reported. To improve future basket-
ball research, it is strongly encouraged that when the testing
occurs is clearly stated when reporting the physical charac-
teristics of basketball athletes. Furthermore, when using sum
of skinfolds to measure body composition, the specific sites
should be clearly identified and used repeatedly over time
for consistent measurements. The use of an International
Society for the Advancement of Kinanthropometry-certified
anthropometrist may also be of benefit for the accuracy and
reproducibility of measurements [146]. It is recommended
to use the sum of eight skinfold sites, measured at the biceps,
triceps, subscapular, iliac crest, supraspinale, abdominal,
anterior thigh and medial calf, in line with the recom-
mended protocols outlined bythe International Society for
the Advancement of Kinanthropometry due to the efficiency
of testing, ability to detect meaningful change over time, and
standardisation of measurement [147].
4.2.3 Muscular Power
Well-developed muscular power is favourable to meet the
physical demands of basketball match-play [16, 104, 114,
148]. Jump variables were used most frequently to indirectly
assess muscular power characteristics, which may be due to
the range of tasks specific to basketball involving various
forms of jumps (e.g., rebounding, contesting a shot) and the
high frequency of jumping executed throughout matches [12,
149, 150]. The greatest jump heights reported in the litera-
ture were from the VJ test in collegiate players (77 ± 6cm)
[111] and players who were assessed at the NBA Draft Com-
bine (77 ± 8cm). Collegiate players (44–83cm) tended to
record higher VJ performances than professional players
(36–63cm), and semi-professional players (35–50cm),
while insufficient studies were observed at the representative
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1519
Testing Methods and Physical Characteristics of Male Basketball Players
and amateur levels to draw conclusions. No differences in
VJ height were observed between playing positions at the
professional level with insufficient studies available across
other playing levels to make conclusions regarding posi-
tional differences. Considering there were discrepancies
between professional, semi-professional, and collegiate
players observed, it is important to consider that different
testing methods (e.g., three vs five jumps, mean jump height
vs greatest jump height) may have been used across studies.
Therefore, the influence of the different methods used to
quantify jump height on the quality of the reported data is
not known and requires further investigation.
Mean CMJ height ranged from 35 to 77cm across studies
in adult male basketball players. Multiple studies reported
jump height and peak power of professional, semi-profes-
sional, and collegiate players. Findings demonstrated heter-
ogenous outcomes for jump height and peak power output
both within (e.g., professional vs professional) and between
(e.g., professional vs collegiate) competition levels. The lack
of research at the representative and amateur playing lev-
els limited the ability to draw conclusions regarding CMJ
performance for players competing at these levels. The
variation in CMJ height and peak power output observed
in professional, semi-professional, and collegiate players
may be reflective of the different testing methodologies
used across studies combined with the varying abilities of
players assessed across different competition levels. When
mean CMJ height was reported according to playing posi-
tion irrespective of competition level, similar ranges were
observed (guards: 38–60cm, forwards: 36–58cm, and cen-
tres: 36–57cm). From a methodological perspective, when
conducting a CMJ on a force platform, basketball practition-
ers are able to record and track variables that are sensitive to
changes over time (e.g., relative power output [151]), as well
as monitor acute changes in jump performance (e.g., height)
or strategy (e.g., flight time to contraction time ratio [152]).
These varied options for interpretation may be of particular
benefit when assessing and monitoring player fatigue and
readiness across the season [153].
The SJ was also implemented to assess adult male basket-
ball players throughout the literature but only in professional
and collegiate players. Insufficient data were reported at the
semi-professional, representative, collegiate, and amateur
competition levels to draw conclusions. While professional
player SJ height ranged (29–50cm) across studies. Posi-
tional differences in SJ height were reported only at the
professional level, with no clear differences apparent and
centres exhibiting the least variability (guards: 30–41cm,
forwards: 29–40cm, centres: 33–36cm). The jump height
attained during the SJ was consistently lower than the CMJ
and VJ. These differences are due to the concentric-only
force expression of the SJ and the inability to use elastic
energy generated during the preparatory countermovement
evident in the CMJ and VJ [150]. However, when the SJ and
CMJ tests are used together, the combination of outcome
variables (e.g., jump height) can be used as a diagnostic
tool, allowing basketball practitioners to evaluate the abil-
ity of players to use their stretch–shortening cycle while
jumping [90]. However, identifying the reliability of these
diagnostic variables such as the eccentric utilisation ratio,
which can be calculated as CMJ height divided by SJ height
(peak power may also be used), requires more research in
basketball players.
The high frequency of jumps performed during basket-
ball games has been well established [10, 12]. However, the
quantity of different jump types (e.g., stationary jump vs run-
ning vertical jump, unilateral vs bilateral take-off), the num-
ber of maximal and submaximal jumps, and whether there
are differences in the frequency of different jumps between
playing positions or competition levels is unknown. This
gap in the literature is a limitation when designing train-
ing programmes to enhance jump performance in basketball
players, as the exact type of jumping demands imposed on
players are not fully understood. While it is clear different
jump strategies exist, it is important to recognise they are
underpinned by different speed-strength qualities (e.g., reac-
tive strength, concentric-only speed strength) [139]. Con-
sequently, to holistically assess jumping ability in players,
multiple tests may be required. A battery of tests that target a
range of force production strategies such as SJ for concentric
only force production, CMJ for long-slow stretch shortening
cycle force production, and drop or repeated jumps for short-
fast stretch shortening cycle production warrant considera-
tion. Additionally, assessing jump performance from vary-
ing approaches and take-off strategies may provide further
insight into jumping ability. Reporting arm reach during a
jump, or the combination of jump height and wingspan may
provide novel insight into the maximal ability of players to
secure a rebound or tip the ball to advantage during match-
play. The combination of multiple jump tests may enable
individual jump-profiles to be developed and allow train-
ing programmes to target the unique deficiencies of each
player. However, it must be acknowledged that implementing
an extensive jump battery may not be practical. Therefore,
basketball practitioners may wish to select the most appro-
priate tests from the provided recommendations that best
suits their needs.
Basketball players are frequently required to execute
repeated jumps to challenge opposition shots and contest
rebounds during match-play. While stationary bilateral
jumps provide valuable information regarding the vertical
jump ability of players, often multiple jumps are required
in quick succession (e.g., multiple jumps while contesting
a rebound). Therefore, an assessment of the speed-strength
quality that underpins repeated jumping is warranted during
testing. The reactive strength index represents reactive jump
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1520 M.Morrison et al.
ability and has traditionally been assessed using drop jumps
[154] or repeated jump protocols [96, 155] in male basket-
ball players. However, we propose a novel bilateral hopping
test protocol [156, 157] to measure both reactive strength
and leg stiffness. While we are unaware of any basketball
research that incorporates the bilateral hopping test, reactive
strength index and leg stiffness are important qualities in
basketball players because of the need to perform repeated
jumps during training and matches. Furthermore, the bilat-
eral hopping test has been shown to demonstrate greater
between-day reliability compared with other repeated jump
tests in adolescent rugby union players (e.g., five repeated
jumps in place [157]). Additionally, the bilateral hopping
test can be efficiently completed through a single test (com-
pared with drop jump profiles that require multiple jumps)
and can be standardised with the use of a metronome to
ensure consistency.
4.2.4 Linear Sprint Performance
The game demands of basketball require well-developed lin-
ear sprint and acceleration capacities [12, 61, 65, 158–160].
Throughout the literature, heterogenous linear sprint dis-
tances have been used to assess adult male basketball play-
ers. When observing the three most commonly used dis-
tances, often insufficient data were observed to draw firm
conclusions. Of the studies that reported linear sprint per-
formance across distances up to 20m, only three [4, 21, 58]
also reported 5-m and 10-m splits. Over 10m, the limited
available evidence [4, 27, 79] suggests guards (1.72–2.19s)
and forwards (1.72–2.25s) possess similar linear sprint
speed, and are faster than centres (1.80–2.34s). Considering
the match demands of basketball [7, 11, 12], researchers and
practitioners are strongly encouraged to capture split times
at the 5-m and 10-m marks during a 20-m linear sprint test.
The additional data captured at 5m and 10m reflect dis-
tances that are encountered during match-play [7, 112] and
may provide further insight into the acceleratory ability of
players. Furthermore, basketball researchers and practition-
ers would benefit by reporting sprint times relative to play-
ing position to help establish meaningful position-specific
normative data that can assist with determining minimum
thresholds for playing standards for adult male basketball
players. Additionally, reporting sprint times relative to
height may provide novel insight into the sprint capabilities
of players and may be appropriate for categorising players
who play across multiple positions throughout a match.
4.2.5 Change‑of‑Direction Speed
The ability to rapidly change direction within the confines
of the court is important for basketball performance [20, 65,
161, 162]. Change-of-direction speed was most commonly
assessed using the Agility T-Test. Observations between
competition levels suggest change-of-direction speeds are
similar between professional (8.84–10.04s) and collegiate
(8.92–9.78s) players, with slower times evident in semi-
professional players (9.52–10.90s). There were insufficient
data to draw conclusions regarding positional differences
in Agility T-Test performance. Further research is recom-
mended to explore whether differences in change-of-direc-
tion speed are apparent between playing positions at other
competition levels. However, the Agility T-Test has been
scrutinised as it has been shown to favour specific physical
characteristics such as 10-m linear sprint speed (r = − 0.92)
and shuffling speed to the right (r = − 0.75) in semi-profes-
sional male basketball players [112]. A further concern of
the Agility T-Test is the distances covered are not reflective
of match requirements in basketball [12, 112]. Consequently,
a proposed modified Agility T-Test, where the distances are
shortened to better reflect match demands players encounter
has been suggested as an alternative option to assess change-
of-direction speed in basketball players [148]. Nevertheless,
this test has only been reported in one study examining adult
male basketball players [64], and the validity and utility of a
modified Agility T-Test as a measure of change-of-direction
speed in adult male basketball players is not yet known and
warrants further research.
Alternative change-of-direction speed tests such as the
Y-Shaped Change-of-Direction Speed Test have also been
used to assess adult male basketball players, but only in
semi-professional players. Consequently, firm conclusions
regarding the efficacy of the Y-Shaped Change-of-Direction
Speed Test to discriminate between playing positions and
competition levels is unclear. Moreover, a concern of the
Y-Shaped Change-of Direction Speed Test is the lack of lat-
eral movements, which are regularly performed in basketball
match-play. In recent years, the Lane Agility Test has been
used to assess change-of-direction speed at the collegiate
level in adult male basketball players [3, 51, 111]. Similar
to the Agility T-Test, the requirements of the Lane Agility
Test are not reflective of most movement tasks commonly
required during basketball match-play (i.e., no cognitive or
perceptual elements present). Nonetheless, the Lane Agil-
ity Test consists of pre-determined periods of accelerat-
ing, lateral shuffling, and backwards running, all of which
are typical movements in basketball. Mean Lane Agility
Test performance was similar between collegiate players
(10.4–11.8s) and data captured at the NBA Draft Combine
(10.3–12.2s). Considering the collegiate playing pathway
is a common route to playing professionally in the NBA,
basketball researchers and practitioners may benefit from
implementing the Lane Agility Test to their testing batteries
to familiarise their players with the demands of the NBA
Draft Combine if their players intend on entering the NBA
draft. However, further exploration to identify the ability of
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1521
Testing Methods and Physical Characteristics of Male Basketball Players
the Lane Agility Test to discriminate change-of-direction
speed between playing positions and competition levels is
required. These findings suggest change-of-direction speed
alone may not yet provide basketball researchers and prac-
titioners with sufficient information to confidently evaluate
and discriminate between adult male players competing at
different levels.
4.2.6 Agility
Basketball match-play requires players to interpret stimuli
and rapidly execute an appropriate movement response
[20, 149], highlighting the need for a perceptual element to
be present when assessing agility [47]. However, physical
and technical components such as lower-body strength and
movement strategy also contribute to agility performance
[46, 47]. The introduction of a decision-making constraint
has indicated some agility tests are better able to discrimi-
nate between competition levels (semi-professional vs ama-
teur [113]) and playing roles (starters vs non-starters [60])
compared with pre-planned change-of-direction tests in
adult male basketball players. Consequently, the perceptual
component present during an agility test may be of greater
importance in discriminating between players at different
competition levels than pre-planned change-of-direction
speed. However, it is important to acknowledge that change-
of-direction speed and agility are independent skills [46].
Considering the limited amount of research investigating
agility in basketball players, further research is needed to
explore potential differences between playing positions and
competition levels in adult male basketball players and to
develop an efficacious and ecologically valid agility test.
Finally, if implementing an agility test in basketball play-
ers, the type of stimuli being used should be considered. In
football codes, a sport-specific stimulus has been shown to
be an important component when assessing agility [163]
with players competing at higher levels often performing
better than players competing at lower levels in Austral-
ian rules football [164, 165] and rugby league [166, 167].
Throughout the literature, timing light systems [113, 118],
light-up cone systems [49, 85], and humans who initiate
movement [4, 21, 60] were the stimuli identified in agility
tests used to assess adult male basketball players. Across
studies included in this review, basketball researchers and
practitioners emphasised accuracy during trials (i.e., the par-
ticipant made the correct decision) as ‘important’ [4, 60] as
identifying and executing the appropriate movement strategy
during match-play may lead to better outcomes (e.g., antici-
pating the opponents movement and drawing an offensive
foul) than if the incorrect decision was made (e.g., being
called for a blocking foul due to being out of position rather
than successfully drawing an offensive foul). However, the
accuracy of the attempts were not always reported [4, 21,
49, 60, 85, 113, 118]. Often if players made the incorrect
decision or anticipated the required movement rather than
responding to the stimuli during a trial, the attempt was dis-
carded, not included in the data reported, and repeated [113,
118]. Therefore, it is recommended basketball researchers
and practitioners report the outcome of agility trials (i.e.,
successful or unsuccessful) in the future as this may pro-
vide greater insight to the decision-making ability of play-
ers. The development of an outcome-based assessment of
attacking and defending agility in basketball may provide
a more comprehensive assessment of agility in adult male
basketball players.
4.2.7 Strength
Muscular strength is an important quality in basketball
players [94, 124, 168–170]. The limited data pertaining to
lower-body strength across competition levels suggest pro-
fessional players (back squat 1RM: 143–202kg) possess
greater lower-body strength than collegiate players (back
squat 1RM: 116–156kg). In collegiate players, lower-body
strength has been related to career obtainment, with stronger
players reaching higher competition levels than their weaker
peers [124]. Additionally, back squat 1RM has been shown
to have a strong correlation with playing time in NCAA
division 1 (r = 0.64) and division 2 (r = 0.74) competi-
tions [51, 104]. The limited evidence available inhibits the
ability to discern if lower-body strength can discriminate
between playing positions in adult male basketball players.
Consequently, the current positional demands and minimum
physical thresholds of lower-body strength required by each
playing position and competition level are unknown in adult
male basketball. To address these gaps, basketball research-
ers and practitioners are encouraged to report strength test-
ing results according to playing position to elucidate any
positional differences that may be present.
Upper-body strength is often required in basketball
matches when players compete to create and defend space.
However, it is important to acknowledge that in order for iso-
lated upper-body strength to transfer to match-play, contribu-
tions from force production components of the lower body
may be required. The range of 1RM loads lifted during the
bench press were similar between professional (70–112kg)
and collegiate (76–102kg) players, with insufficient data
reported for other competition levels. The lack of upper-
body strength data observed for players competing at lower
competition levels could be attributed to strength testing not
being prioritised by basketball researchers and practitioners
due to the fatigue induced from testing and level of exercise
competency required of players. A possible solution for bas-
ketball researchers and practitioners to gather strength data
from their players is to use a linear position transducer(LPT)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1522 M.Morrison et al.
during resistance training sessions to measure kinetic and
kinematic outputs [36, 171]. The use of an LPT during
strength training can provide valid and reliable performance
data [172], which is able to be tracked over time to monitor
player progression (e.g., changes in bar speed at a specified
load) [171, 173], and used to predict maximal strength whilst
inducing minimal fatigue [171, 174, 175]. Only one study
[121] reported bench press 1RM relative to playing posi-
tion in adult male basketball players. Consequently, further
research is required to confidently establish the upper-body
strength characteristics of each playing position.
The evidence collated in this review indicate that strength
testing in adult male basketball players requires further
research to fully understand the minimum strength stand-
ards required of each playing position and competition level.
Nonetheless, it is recommended basketball researchers and
practitioners continue testing maximal upper-body and
lower-body strength to monitor changes in strength across
time. Additionally, the assessment of maximal strength will
allow for accurate prescription of resistance training loads
(e.g., %1RM). Furthermore, the combination of dynamic and
isometric strength tests may allow basketball researchers and
practitioners to profile temporal and absolute force produc-
tion ability in players. While there are numerous isometric
tests available to assess force production characteristics,
such as the isometric squat and isometric mid-thigh pull
(IMTP), there is little published evidence exploring their
utility and efficacy in basketball. The IMTP is an isomet-
ric test proposed to measure strength and force production
characteristics of basketball players, owing to the ease of
use and minimal fatigue induced in players [148]. The IMTP
may also provide basketball researchers and practitioners
with an option to test players who do not have the compe-
tency to undertake maximal dynamic strength testing. Fur-
thermore, highly sensitive variables (e.g., early-phase force
development across time bands) measured during the IMTP
may be used to monitor player fatigue [176]. Therefore, a
strength profile comprising the IMTP, bench press, and back
squat may allow basketball researchers and practitioners to
develop baseline levels of strength that support training
prescription and are also able to guide return to play from
injury.
4.2.8 Anaerobic Capacity
Well-developed anaerobic capacity allows basketball play-
ers to repeatedly perform high-intensity movements that
are typically separated by brief rest periods during matches
[17, 88, 177]. Assessment of anaerobic capacity involved
either running or resisted cycling tests. Regarding running
tests, full court shuttle run performance was homogenous
(27.4–27.8s) across professional [125], semi-professional
[28], and collegiate [51] adult male basketball players.
Additional data are needed to determine if positional differ-
ences in the full court shuttle run exist and if the test is able
to confidently discriminate between competition levels. The
RAST was also used to assess anaerobic capacity exclusively
in professional players, prohibiting the ability to compare
performance between competition levels. Insufficient studies
were observed to draw conclusions regarding positional dif-
ferences in RAST performance in adult male basketball play-
ers. Subsequently, further research is required to elucidate
any differences in RAST performance by playing position
or competition level.
Regarding cycling tests, the WAnT cycle test was primar-
ily used to assess anaerobic capacity and only reported in
professional players. This isolated use of the WAnT cycle
test in professional teams may be due to higher level organi-
sations having greater access to specialised equipment and
expertise to reliably implement this test. Additionally, the
time associated with testing players using the WAnT cycle
test may be impractical at lower competition levels. Insuf-
ficient data were available to draw conclusions regarding
positional performance during the WAnT. While the data
gathered from the WAnT cycle test provide valuable insight
regarding the anaerobic capacity of basketball players, the
time and resources required to implement the WAnT are
considerable. Furthermore, the transfer of cycling anaero-
bic power to relevant sustained high-intensity movement
patterns in basketball are not known. Therefore, basketball
researchers and practitioners are encouraged to continue
assessing the anaerobic capacity of adult male basketball
players using tests that are accessible and appropriate to their
needs. Additionally, reporting outcome variables indicative
of anaerobic capacity relative to playing position using data
in absolute terms and relative to body mass is recommended.
4.2.9 Aerobic Capacity
Basketball players require well-developed aerobic capaci-
ties to tolerate the intermittent bouts of varying intensity
encountered during matches [129, 155, 178–181]. Players
with a high aerobic capacity are better able to tolerate mul-
tiple high-intensity sprints and have improved fatigue resist-
ance [182]. Throughout the literature, mean estimated and
measured VO2max ranged from 42 to 64mL/kg/min across
studies in adult male basketball players. This variation in
results may be attributed to different tests being adopted
(e.g., MSFT vs Yo-Yo IRL1 vs incremental treadmill test)
and the inherent levels of error when calculating VO2max
during each test [183].
The use of incremental treadmill tests was evident at pro-
fessional (50–61mL/kg/min) and collegiate (50–58mL/kg/
min) levels and revealed similar well-developed mean aero-
bic capacity across both competition levels. Insufficient data
were observed at the semi-professional, representative, and
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1523
Testing Methods and Physical Characteristics of Male Basketball Players
amateur levels to draw conclusions regarding the incremen-
tal treadmill test. Positional comparisons indicated guards
possess the greatest mean aerobic capacity across studies
in professional players (50–60mL/kg/min), then forwards
(46–58mL/kg/min), followed by centres (42–58mL/kg/
min). The positional differences in aerobic capacity may
be attributed to the unique match roles required of each
position. The frequent use of incremental treadmill tests to
assess VO2max in professional and collegiate players may be
attributed to basketball practitioners at these levels having
greater access to resources such as laboratory-based physi-
ological testing equipment than lower levels. Furthermore,
professional and collegiate players may have a greater avail-
ability for testing throughout the year compared with other
competition levels (e.g., semi-professional players may have
competing demands such as supplementary jobs).
In a practical setting, the ability to test players efficiently
is an important consideration for basketball researchers
and practitioners, and the ability to test multiple athletes
simultaneously is often advantageous. A variety of running-
based tests that are able to assess multiple players at once
were identified in the literature. The two most commonly
used tests were the Yo-Yo IRL1 and the MSFT, with the
Yo-Yo IRL1 used most frequently at the professional and
semi-professional levels. In contrast, the MSFT was used
mainly in professional players. Positional differences in
VO2max attained during the MSFT reflect a similar trend
to aerobic capacity from incremental treadmill tests, with
professional guards recording the greatest estimated VO2max
(45–64mL/kg/min), then forwards (43–62mL/kg/min), and
centres (42–58mL/kg/min). However, insufficient data were
available to compare MSFT performance across competition
levels and to identify differences in VO2max between playing
positions using the Yo-Yo IRL1. Therefore, further research
is required to contribute meaningful data for the develop-
ment of normative standards regarding the aerobic capacity
requirements according to playing position and competition
level in adult male basketball players.
5 Limitations
While this review presents a contemporary and compre-
hensive analysis of basketball tests and reveals the physi-
cal characteristics of adult male basketball players, there
are limitations that should be considered. First, this review
excluded tests involving a basketball-specific skill compo-
nent (e.g., dribbling or shooting) and tests that assessed
several physical characteristics simultaneously (e.g.,
Basketball Exercise Simulation Test [137, 138]). While
these tests may offer novel insight regarding basketball-
related fitness, they are often assessing multiple physical
characteristics at the same time, and therefore were not
considered in this review. Second, the interaction between
physical characteristics, psychological influences, techni-
cal abilities, tactical abilities, and the competitive environ-
ment in relation to basketball performance was not inves-
tigated. Thus, discriminating between competition levels
or selecting players principally based on their physical
characteristics is cautioned, as enhanced physical char-
acteristics alone do not guarantee that a player will be
successful. Furthermore, it is important to acknowledge
that varying levels of inherent natural ability, underpinned
largely by genetic components exist. However, there are
elements of fitness such as fatigue resistance and muscu-
lar endurance that are able to be enhanced by appropriate
training. Finally, due to the heterogeneity of testing meth-
ods reported in the literature, we were unable to perform
a meta-analysis of physical characteristics across playing
positions and competition levels.
6 Practical Recommendations
andConsiderations forTesting Physical
Characteristics
With the wide range of tests and outcome variables available
to basketball researchers and practitioners, developing a test-
ing battery that is both valid and reliable but also informa-
tive and efficient can be challenging and at times conten-
tious. Establishing a universal standardised test battery is
further complicated by constraints such as resource avail-
ability, access to players, and competition or travel schedules
that may interfere with scheduling testing sessions. While
acknowledging these challenges, testing recommendations
and outcome variables for each physical characteristic have
been provided (Fig.5 and Table13). The proposed bat-
tery aims to allow for the standardisation of testing and the
implementation of a reproducible protocol that can be used
to inform subsequent training practice. Furthermore, the rec-
ommended tests are selected based on their efficiency (i.e.,
ability to test multiple players simultaneously or in succes-
sion) and the ability to use variables from multiple tests to
infer additional qualities (e.g., sprint momentum, eccentric
utilisation ratio). Finally, the testing battery is aimed to be
applicable for the real-world assessment of adult male bas-
ketball players while drawing upon the scientific literature.
It should be noted that this battery is not an exhaustive list
of tests and outcome variables, and basketball researchers
and practitioners are recommended to add or remove tests
and output variables as they see fit provided their decisions
are guided by logic, rationale, and data.
It is undeniable that anthropometry is an important con-
sideration for basketball players [10, 32, 33, 184–192]. Thus,
the measurement of height, body mass, and wingspan are
strongly recommended at the beginning of testing. Following
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1524 M.Morrison et al.
these assessments, the sum of eight skinfolds, reported
in mm, is suggested because of the low associated cost,
relative ease of implementation, and the ability to gather
reliable results provided tester competency as outlined by
Kasper etal. [147]. With the high prevalence of jumping
during basketball match-play [12, 20], a range of jumping
tests have been recommended, including the CMJ, VJ, SJ,
and the bilateral hopping test, with each jump test assess-
ing different characteristics. For measures of linear sprint
speed and change-of-direction speed, 20-m linear sprints and
a modified Agility T-Test are recommended, respectively.
Because of the relatively short length of a basketball court
(~ 28m), a 20-m sprint with 5-m and 10-m split times also
recorded may be more appropriate to assess linear sprint per-
formance compared with tests across longer distances that
have been adopted in some studies (e.g., 40m [56, 93]). The
modified Agility T-Test is recommended as the distances
covered during the test are limited to 5m in any direction,
before requiring a change of direction. The shorter distances
are more reflective of match demands compared with the
traditional Agility T-Test [112]. To assess agility, further
research is required to develop an agility test that is repeat-
able, practical to implement, and reflects the demands of
basketball. The Y-shaped Agility test may provide basketball
practitioners with insight into the agility of players, although
the movement demands are not specific to basketball match-
play. Therefore, a definitive agility test for use in adult male
basketball players cannot be recommended at this stage.
For measures of strength, 1–3RM during the back squat
and bench press are suggested given their ability to provide
data that can be monitored over time, inform training pre-
scription, and provide baseline strength measurements for
return to play protocols following injury. While the need to
produce force is undoubtedly important in the production
of power, it may also help support players in maintaining
or securing an advantageous position during matches (e.g.,
backing down an opponent in the low post). It is also recom-
mended that during strength testing, as players are building
towards their maximal effort, the velocity of submaximal
loads are monitored with an LPT [36]. Use of linear position
transducers will support the development of load-velocity
profiles in players, which can be used to assess changes in
force production with submaximal loads, enhance training
prescription, and monitor fatigue [171]. It should also be
noted that an IMTP could be a feasible alternative if move-
ment proficiency and competency during common resist-
ance training exercises is lacking. Because of the variabil-
ity amongst anaerobic tests in the literature, no definitive
anaerobic capacity test has been recommended. However,
if researchers and practitioners wish to assess anaerobic
capacity, an ecologically valid and reliable test should be
considered. Finally, the use of the Yo-Yo IRL1 has been
suggested to assess aerobic capacity due to its validity, reli-
ability, and feasibility [193, 194]. It is acknowledged that the
gold standard gas analysis may provide improved accuracy
in measuring VO2max; however, because of the constraints
commonly associated with this testing (e.g., predominantly
in laboratory settings, time, cost, non-basketball-specific
movement patterns in test protocols), an efficient on-court
solution has been recommended that has been repeatedly
Fig. 5 Recommendations for testing the physical characteristics of adult male basketball players.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1525
Testing Methods and Physical Characteristics of Male Basketball Players
Table 13 Recommended tests and outcome variables to assess the physical characteristics of adult male basketball players
Characteristic Test Outcome variable Technical note Citation count
Anthropometry Height (cm) Measuring anthropometry at the
beginning of the testing battery is
recommended while players are
in a rested state
114
Body mass (kg) 114
Wingspan (cm) 3
Body composition Eight-site skinfolds Sum of eight skinfolds (mm) High inter-tester variability exists.
To gather reliable results, an
experienced tester should conduct
this test. Preferably, the same
practitioner is recommended to
administer this teston different
occasions.An estimation equa-
tion specific to the population is
recommended. Sites used should
be reported and used consistently
2
Muscular power Countermovement jump Jump height (cm)
Mean concentric relative power
(W/kg)
To reduce error introduced with
movement strategies, it is recom-
mended that height is calculated
using impulse from a force plat-
form. Relative mean power can
be used as an auxiliary to support
interpretation of jump data
46
Vertical jump Jump height (cm)
Mean concentric relative power
(W/kg)
See above 33
Squat jump Jump height (cm)
Mean concentric relative power
(W/kg)
Must carefully monitor force–time
output to ensure no preparatory
countermovement is used. Squat
jump height can be coupled with
countermovement jump height to
support monitoring and prescrip-
tion through calculation of the
‘eccentric utilisation ratio’
19
Linear speed 20-m sprint Time intervals (s)
Momentum (kg⋅m/s)
Performance time measured at
5-m, 10-m and 20-m inter-
vals.Accelerationovereach
intervalshouldbe calcu-
lated.Starting positionmustbe
standardised(e.g. 50cm from
first interval)
20
Change-of-direction speed Modified agility T-test Time (s) Total distance covered is 20m,
with no more than 5m covered
before requiring a change of
direction. Player must remain
facing forwards for the duration
of the test
1
Strength 1–3RM Back squat Absolute load (kg)
Relative strength
Load-velocity profile
Players must be competent with
technique to safely implement
test. Squat depthmustbe stand-
ardised. Additionally, during sub-
maximal efforts, a linear position
transducer should be used to
develop individualised load-
velocity profiles.Dependent upon
athlete technical proficiency, an
isometric mid-thigh pull may be
an alternate or supplementary test
8
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1526 M.Morrison et al.
used in the literature to assess several samples of adult male
basketball players [28, 65, 67, 72, 137].
7 Conclusions
This review collates all tests and outcome variables used to
assess the physical characteristics of adult male basketball
players in the literature to date. The number of tests and
outcome variables identified confirm that a gold-standard
testing battery for assessing the physical characteristics of
basketball players does not exist. While it appears basketball
practitioners are prioritising the assessment of specific phys-
ical characteristics (i.e., anthropometrics, muscular power,
linear speed, change-of-direction speed, agility, strength,
anaerobic capacity, and anaerobic capacity), the methods
of assessment often vary in regard to technology used (e.g.,
force platform vs jump mat), variables reported (e.g., mean
jump height from multiple attempts vs. peak jump height)
and test protocols implemented (e.g., number of jumps per-
mitted during a jump test). Further, the varying levels of
inherent validity and reliability across the spectrum of tests
reported make the establishment of normative data challeng-
ing and the comparison of physical characteristics across
studies difficult to make in basketball players. To develop
meaningful normative data, basketball practitioners must
develop standardised testing protocols that are reproducible
and reflective of match demands. Developing league-wide
and federation-wide testing batteries would allow for the
longitudinal assessment of players in large cohorts and the
establishment of minimum physical standards for playing
positions and competition levels.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s40279- 021- 01626-3.
Declarations
Funding At no point was funding received by any of the authors for
the writing of this manuscript.
Conflict of interest Matthew Morrison, David Martin, Scott Talpey,
Aaron Scanlan, Jace Delaney, Shona Halson, and Jonathon Weakley
declare they have no conflicts of interest relevant to the content of this
review.
Ethical approval Not applicable.
Consent to participate Not applicable.
Consent for publication Not applicable.
Availability of data and material All data and materials reported in this
systematic review are from peer-reviewed publications and publicly
available data from official organisation websites (https:// www. nba.
com/ stats/ draft/ combi ne/). All of the extracted data are included in the
manuscript and supplementary files.
Code availability Not applicable.
Authors’ contributions MM and JW conceptualised the review and cri-
teria. MM and JW completed the screening and data extraction of all
data within this manuscript. ST, ATS, and DTM assisted with the for-
mulation of clearly stated objectives, refinement of final methodology,
and contributed to the interpretation of findings. MM, JW, ATS, JD,
and SH completed the writing of the manuscript. All authors reviewed
and refined the manuscript.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article's Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
RM repetition maximum, VO2max maximum oxygen uptake, Yo-Yo IRL1 Yo-Yo Intermittent Recovery Test Level 1
Table 13 (continued)
Characteristic Test Outcome variable Technical note Citation count
1–3RM Bench press Absolute load (kg)
Relative strength
Load-velocity profile
Players must be competent with
the technique to safely imple-
ment test. Bench press range of
motion must be standardised.
Load-velocity profiles should
be developed from sub-maximal
loads using a linear position
transducer
14
Aerobic capacity Yo-Yo IRL1 Finishing level
Estimated VO2max (mL/kg/min)
Yo-Yo IRL1 must be completed on
the same flooring (e.g. court) and
in similar environmental condi-
tions (e.g. consistent temperature)
12
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1527
Testing Methods and Physical Characteristics of Male Basketball Players
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Authors and Aliations
MatthewMorrison1· DavidT.Martin1· ScottTalpey2· AaronT.Scanlan3· JaceDelaney· ShonaL.Halson1,4·
JonathonWeakley1,4,5
* Jonathon Weakley
Jonathon.weakley@acu.edu.au
1 School ofBehavioural andHealth Sciences, Australian
Catholic University, Brisbane, QLD, Australia
2 School ofScience, Psychology andSport, Federation
University Australia, Ballarat, VIC, Australia
3 Human Exercise andTraining Laboratory, School ofHealth,
Medical andApplied Sciences, Central Queensland
University, Rockhampton, QLD, Australia
4 Sports Performance, Recovery, Injury andNew Technologies
(SPRINT) Research Centre, Australian Catholic University,
Brisbane, QLD, Australia
5 Carnegie Applied Rugby Research (CARR) Centre, Institute
ofSport, Physical Activity andLeisure, Leeds Beckett
University, Leeds, UK
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
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