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Pacing Strategy Determinants During a 10-km Running Time Trial: Contributions of Perceived Effort, Physiological, and Muscular Parameters
Abstract
The purpose of the current study was to identify the main determinants of the self-selected pacing strategy during a 10-km running time-trial. Twenty eight male long-distance runners performed the following tests: a) maximal incremental treadmill test, b) economy running test, c) maximum dynamic strength test, and d) 10-km running time-trial on an outdoor track. A stepwise multiple regression model was used to identify the contribution of rating of perceived exertion (RPE), physiological, and muscular parameters on the pacing strategy adopted by athletes. In the start phase (first 400m), RPE accounted for 72% (P=0.001) of the pacing variance. Peak treadmill speed measured during a maximal incremental test explained 52% (P=0.001) of the pacing variance during the middle phase (400 to 9600 m), while maximal oxygen uptake and maximum dynamic strength accounted for additional 23% (P=0.002) and 5% (P=0.003), respectively. In the end phase (last 400m), peak treadmill speed accounted alone for 66% (P=0.003) of the pacing variance. These data suggest that predictors of the pacing strategy during a 10-km running time-trial have a transitional behavior from perceptive (start phase) to muscular and physiological factors (middle and end phases).
... Some people run for fun while others choose to seriously compete, attempting to run the shortest time for a fixed distance race (2). Outside of sprints, pacing oneself to run the best possible race is crucial (3)(4)(5). If the runner starts the race too slow, they may not finish in as fast a time as expected. ...
... If the runner starts the race too slow, they may not finish in as fast a time as expected. On the other-hand, if the runner goes out too fast, they may find themselves running out of energy, struggling to even finish the race (3)(4)(5). Determining the best pacing strategy for each individual runner is challenging, as a runner's optimal pace depends on several values that are individual to them, something this work aims to answer. Looking at data collected from timing mats in the 2015 Boston Marathon, Figure 1 plots how the runners placed vs. how their pace differed from their first 10 k and their overall pace. ...
... When running races such as the marathon, one must consider pacing strategies (3)(4)(5). The runner must not only consider oxygen availability, but how much energy the body has stored (14). ...
Introduction
Runners competing in races are looking to optimize their performance. In this paper, a runner's performance in a race, such as a marathon, is formulated as an optimal control problem where the controls are: the nutrition intake throughout the race and the propulsion force of the runner. As nutrition is an integral part of successfully running long distance races, it needs to be included in models of running strategies.
Methods
We formulate a system of ordinary differential equations to represent the velocity, fat energy, glycogen energy, and nutrition for a runner competing in a long-distance race. The energy compartments represent the energy sources available in the runner's body. We allocate the energy source from which the runner draws, based on how fast the runner is moving. The food consumed during the race is a source term for the nutrition differential equation. With our model, we are investigating strategies to manage the nutrition and propulsion force in order to minimize the running time in a fixed distance race. This requires the solution of a nontrivial singular control problem.
Results
As the goal of an optimal control model is to determine the optimal strategy, comparing our results against real data presents a challenge; however, in comparing our results to the world record for the marathon, our results differed by 0.4%, 31 seconds. Per each additional gel consumed, the runner is able to run 0.5 to 0.7 kilometers further in the same amount of time, resulting in a 7.75% increase in taking five 100 calorie gels vs no nutrition.
Discussion
Our results confirm the belief that the most effective way to run a race is to run approximately the same pace the entire race without letting one's energies hit zero, by consuming in-race nutrition. While this model does not take all factors into account, we consider it a building block for future models, considering our novel energy representation, and in-race nutrition.
... Regarding the physiological influence on pacing behaviour, Bertuzzi, Lima-Silva (Bertuzzi et al., 2014) reported that peak treadmill speed (PTS) during an incremental test, maximal oxygen consumption (VO 2 max), and maximum dynamic strength explained 80% of the speed variance during the middle phase of a 10-km race and the PTS alone explained 66% of the final 400m speed. In addition, Do Carmo, Barroso (Do Carmo, Barroso, Renfree, Gil, & Tricoli, 2016) observed that after an induced fast start, the ability to maintain speed during a 10-km race was associated with higher PTS. ...
... Lima-Silva, Bertuzzi (Lima-Silva et al., 2010) observed that runners with higher RE ran at faster speeds during the first 400-m of a 10-km race, executing a more aggressive fast start, as well as during the entire distance compared with less economical runners. In addition, more economical runners were able to maintain higher intensities for a longer time (Bertuzzi et al., 2014;Foster & Lucia, 2007;Paavolainen, Nummela, & Rusko, 2000). Taken together, it is reasonable to suggest that changes in some physiological variables can affect pacing behaviour and consequently performance. ...
... These changes were related to higher speed in the last 2800-m of a 10-km run. In fact, maximum strength is related to speed variance during the middle phase of a 10-km run and PTS explains 66% of the final 400-m speed (Bertuzzi et al., 2014). Taken together, we can suggest that the effects of a training program on pacing behaviour seems to be related to the specific training-induced adaptations. ...
The effects of plyometric training on middle- and long-distance running performances are well established. However, its influence on pacing behavior is still unclear. The aim of this study was to evaluate the effects of plyometric training on pacing behavior. Also, verify whether the adaptations induced by plyometric training would change ratings of perceived exertion (RPE) and/or affective feelings during the race. Twenty-eight male runners were assigned to two groups: control (C) and plyometric training (PT). PT held two weekly plyometric training sessions for eight weeks. Drop jump (DJ) performance, 10-km running performance, pacing behavior, RPE and affective feelings, VO2peak, ventilatory thresholds (VT1 and VT2), peak treadmill speed (PTS), and RE were measured. For group comparisons, a mixed model analysis for repeated measures, effect size (ES) and 90% confidence interval (CI90%) were calculated for all dependent variables. Significant differences pre to post was observed for PT group in DP (7.2%; p ≤ 0.01; ES = 0.56 (0.28 to 0.85)) and RE (4.5%; p ≤ 0.05; ES = -0.52 ((-0.73 to -0.31)) without changes in pacing behavior. While PT was effective for improving DJ and RE, there is no evidence that pacing behavior, RPE or affective feelings are directly affected by these adaptations during a 10-km time-trial run.
... One possible approach for understanding factors related to performance in running events is statistical modelling. Over the past years, several models have been developed to explain and predict performance in long-distance running events (Abad et al., 2016;Bertuzzi et al., 2014;Damasceno et al., 2015b;Lima-Silva et al., 2010;Da Silva et al., 2015;Sinnett et al., 2001). In this context, maximal oxygen uptake (VO 2max ) has traditionally been considered the key factor to predict performance in running events (Midgley et al., 2006). ...
... In this context, since the pioneering studies of Paavolainen et al. (1999a);(1999b), growing evidence shows that neuromuscular factors are, at least, as important as metabolic ones as predictors of performance. More recently, Bertuzzi et al. (2014) reported that 1 repetition maximum (1RM) explained 5% of variance in speed during the middle phase of a 10-km time trial (400-9600 m). Further, Damasceno et al. (2015b) reported that improvement of runner's neuromuscular characteristics was accompanied by a faster end spurt and a better performance during a 10-km time trial (10-km TT). ...
... For all runners, the time elapsed between the completion of the 10-km and the first jump was less than 45 s. For comparison with previous studies (Bertuzzi et al., 2014;Damasceno et al., 2015a), in addition to the total time (T 10km ), performance was analysed every 1,000 m, every 5,000 m (1 st vs. 2 nd half), as differences between halves (Δ5 km ), and the initial (400 m), middle (400-9600 m) and final (400 m) phases of the trial. Also, the coefficient of variation (CV%) of pacing was computed every 1,000 m (CV 1km ), and the fatigue index was also calculated as FI% = [(Highest Speed -Lower Speed)/ Highest Speed] * 100. ...
We aimed to develop models to explain performance and pacing during a 10-km running trial.
Well-trained runners (n = 27, VO2max = 62.3 ± 4.5 mL·kg⁻¹·min⁻¹) divided into High (HPG, T10km = 33.9 ± 1.2 min, n = 9) and Low (LPG, T10km = 37.9 ± 1.2 min, n = 18) performers completed, in different days, the half squat and loaded squat jump (LSJ) exercises (1st day), an incremental test and a submaximal running bout to induce jump potentiation (2nd day), and a 10-km time trial (3rd day). Pacing was significantly different between performance groups (p < 0.05). The inclusion of mechanical and metabolic variables increased the explained variance in performance (LPG, r²adj = 0.87, p < 0.001; HPG, r²adj = 0.99 p < 0.01). Analysis between potentiation and non-potentiation groups revealed significant differences for the speed in the last 400 m (p = 0.02), and in the final RPE (p = 0.03). Performance and pacing can be explained by combining metabolic and mechanical variables and should be controlled by performance level. The relationship between jump potentiation and speed during the last 400 m may suggest that post-activation performance enhancement could be involved in pacing regulation.
... In order to improve our understand of the regulation of pacing strategy, previous studies have demonstrated that different physiological and psychological variables are responsible for the changes in athlete's speed (Bertuzzi et al., 2014;Billat, Wesfreid, Kapfer, Koralsztein, & Meyer, 2006;Faulkner, Parfitt, & Eston, 2008). Bertuzzi et al. (2014) found that in the initial phase of a 10-km race time trial (first 400-m), the rating of perceived exertion (RPE) determined 72% of the variation of the athlete's speed. ...
... In order to improve our understand of the regulation of pacing strategy, previous studies have demonstrated that different physiological and psychological variables are responsible for the changes in athlete's speed (Bertuzzi et al., 2014;Billat, Wesfreid, Kapfer, Koralsztein, & Meyer, 2006;Faulkner, Parfitt, & Eston, 2008). Bertuzzi et al. (2014) found that in the initial phase of a 10-km race time trial (first 400-m), the rating of perceived exertion (RPE) determined 72% of the variation of the athlete's speed. In addition, peak speed (52%), maximum oxygen consumption (23%) and maximum dynamic strength (5%) explained 80% of the speed variation in the middle phase (400 to 9600m). ...
... The underlying mechanisms related to speed adjustments during the race are debated in theoretical models proposed by sports scientists (Bertuzzi et al., 2014;Hettinga, De Koning, Broersen, Van Geffen, & Foster, 2006;Marcora, Staiano, & Manning, 2009;St Gibson et al., 2006;Ulmer, 1996). In the teleoanticipation model proposed presented by Ulmer (1996), the task is preplanned by the athlete from the knowledge of the finishing point, and regulated in an anticipatory way through subconscious neural calculations via a "governor" and projected to the conscious brain as a sensation of fatigue (Foster et al., 2009;Gibson & Noakes, 2004;Ulmer, 1996). ...
Purpose: The aim of the study was to verify the agreement between preplanned and executed pacing during a 3-km race and determine whether adjustments are mediated by the rating of perceived exertion (RPE). Method: Thirteen young runners (eight males and five females, 17.5 ± 2.1 and 17.0 ± 1.6 years old, respectively) with national and international experience participated in the study. Before the simulated competition, the athletes informed of their preplanned pacing for the distance through a dashboard with the most common pacing profiles and were also asked to complete a questionnaire communicating their preplanned RPE for each lap of race. During 3-km, heart rate (HR), executed RPE and lap time were recorded. Results: Our results showed no significant association between preplanned and executed pacing (p = .631). Moreover, no significant difference between preplanned and executed RPE was found, including the analysis by laps and phases. RPE and HR increased over time during the race (p < .001). Conclusions: The athletes changed from their preplanned pacing, however, their RPE were similar in the preplanned and executed during the 3-km race. These findings indicate that the RPE could be responsible for adjustments in the pacing strategy.
... With regards to sex differences, women marathon runners adopted a more even pacing in marathon [3,20] and in 100 km, than men [21]. Perceived effort and physiological parameters have been identified as correlates of pacing, and their role might vary across a 10 km race; e.g., perceived effort influenced speed at the start of the race, whereas mainly aerobic capacity and muscle strength-to a lesser degree-influenced speed for the rest of the race [22]. Moreover, with regards to the relationship of pacing with motivation, it has been shown that men with more even pacing scored higher in psychological coping, self-esteem, life meaning, recognition, and competition, than their counterparts with more variable pacing [23]. ...
... Following a variable self-pacing has been shown to present certain advantages-i.e., enhancement of critical power and high-intensity exercise performance compared to constant work rate cycling exercise [33]. In addition, the rate of perceived exertion has been shown to associate with pacing [22] and might vary across race [34]. Moreover, it was acknowledged that head-to-head competition improved performance compared to running alone [35]. ...
... Considering the race distance, runners should be guided to regulate their pacing as less or more variable, depending on whether they intended to run a half-marathon or marathon, respectively. Since recent studies reported an association of pacing with physiological and psychological parameters in marathon [23] and 10 km run [22], future research should verify this association in half-marathon, too. ...
Half-marathon is the most popular endurance running race in terms of number of races and runners competing annually; however, no study has been even compared pacing strategies in this race distance with marathon. The aim of the present study was to profile pacing in half-marathon, compare half-marathon and marathon for pacing, and estimate sex differences in pacing. A total of 9137 finishers in the half-marathon (n=7,258) and marathon race (n=1,853) in Ljubljana 2017 were considered for their pacing in five race segments (0-23.7%, 23.7-47.4%, 47.4-71.1%, 71.1-94.8% and 94.8-100% of the race. Half-marathon runners followed a positive pacing with every segment being slower than its previous one without the presence of an endspurt. Compared to marathon, [where average percent of change in speed (ACS) was 5.71%], a more even pacing was observed in half-marathon (ACS = 4.10%). Moreover, women (ACS = 4.11%) had similar pacing as men (ACS = 4.09%) in half-marathon. In summary, running a half-marathon followed a unique pattern that differentiated this race distance from marathon with the former showing a more even pacing with absence of endspurt and sex difference compared to the latter. Consequently, runners should be advised to adopt a less variable pacing when competing in a half-marathon independently from their sex. To the best of our knowledge, the more even pacing in half-marathon than in marathon was a novel finding as it was the first study to compare the two race distances for this characteristic.
Keywords: aerobic exercise; endurance; marathon; performance; running
... Pacing is the variation in running velocity in a given distance (Abbiss & Laursen, 2008). It is a determinant and decisive aspect for the performance and success of runners, especially in medium-and long-distance events, significantly influencing the end result of these events (Abbiss & Laursen, 2008;Bertuzzi et al., 2014;Tucker, Lambert, & Noakes, 2006). Although pacing has not been recognised as the best strategy during this activity (Bertuzzi, Nakamura, Rossi, Kiss, & Franchini, 2006;Loftin, Sothern, Tuuri, Tompkins, & Koss, 2009), athletes who can regulate their energy expenditure to prevent premature fatigue can perform activities in the shortest possible time (Atkinson, Peacock, & Law, 2007;Gosztyla, Edwards, Quinn, & Kenefick, 2006). ...
... Through the analysis of the race strategy it is possible to divide the performance for the analysis of the velocity variation, since each phase can be influenced by certain variables (e.g. start: RPE; middle: maximal oxygen uptake VO 2max , peak velocity on treadmill V peak , lower limb maximal dynamic strength test 1RM and end: V peak ) (Bertuzzi et al., 2014). Although studies have shown that these variables can be altered with endurance training (Esfarjani & Laursen, 2007;Manoel et al., 2017;Smith et al., 2003), so far, only the study by Damasceno et al. (2015) verified the effect of strength training on pacing strategy. ...
... The overall mean velocity (MV) for each trial was calculated by dividing the total distance covered by the trial duration. Additionally, partial MVs were calculated in three phases: (1) start (first 400 m), (2) middle (400-9600 m) and (3) end (last 400 m), as previously reported (Bertuzzi et al., 2014;Lima-Silva et al., 2010). ...
The aim of this study was to verify the effect of endurance training on the pacing strategy and analyse the risk of premature fatigue during the 10-km performance in moderately trained runners. Study participants were 14 runners (18–35 years) who had training prescribed with peak velocity (Vpeak) and its time limit (tlim). Three tests were performed on a treadmill: two maximum incrementals for VO2max and Vpeak and one for tlim. The 10-km running performance was evaluated on a 400-m track. The mean velocity, heart rate (HR) and rate of perceived exertion (RPE) were monitored at each trial of 10-km running performance. Evaluations were collected pre and after 4 weeks of endurance training. The RPE and HR increased linearly throughout the test, and the risk of fatigue decreased after 3 km. The pacing strategy used by the participants was the “U” running pace in pre- and post-training. There was improvement in the 10-km run after training (40.8 ± 2.8 vs. 39.6 ± 2.7 min). The study showed that 4 weeks of endurance training does not change the pacing strategy and the risk of premature fatigue. However, the training was responsible for improving the 10-km running performance.
... Rate of perceived exertion (RPE) was measured through the 6-20 Borg Scale 10 . The tests were performed at the same time of the day (between 5 and 8 p.m.) 11 , under temperatures ranging from 22.2 ± 6.8 °C, with humidity ranging from 54.3 ± 13.4%. ...
... The overall mean velocity (MV) for each trial was calculated by dividing the total distance covered by the trial duration. Additionally, partial MVs were calculated in three phases: (1) start (first 400 m), (2) middle (400-9600 m) and (3) end (last 400 m), as previously reported 11,12 . These phases were chosen due to the findings of Bertuzzi et al. 11 , who identified these distances are determined by different factors (e.g., start: Rate of perceived exertion; middle: VO 2max , peak running aerobic speed, and 1 repetition maximal for lower limbs; end: peak running aerobic speed). ...
... Additionally, partial MVs were calculated in three phases: (1) start (first 400 m), (2) middle (400-9600 m) and (3) end (last 400 m), as previously reported 11,12 . These phases were chosen due to the findings of Bertuzzi et al. 11 , who identified these distances are determined by different factors (e.g., start: Rate of perceived exertion; middle: VO 2max , peak running aerobic speed, and 1 repetition maximal for lower limbs; end: peak running aerobic speed). ...
Aims
The use of electromagnetic waves by phototherapy to skeletal muscle presents potential ergogenic effects. The aim of this study was to analyze the effect of using bioceramic clothes on performance, heart rate (HR) and rating of perceived exertion (RPE) during a 10 km race. Our hypothesis is that the use of such clothes modifies these variables.
Methods
Participants were 10 runners (27.9 ± 4.2 years) who performed two 10 km performances on track under different intervention conditions: bioceramic garments (CER) and placebo garments (PLA). The mean velocity (MV), HR and rate of perceived exertion (RPE) were monitored at each trial. Additionally, partial MV was calculated in three phases: (1) start (first 400 m), (2) middle (400-9600 m) and (3) end (last 400 m).
Results
MV in CER condition was significantly higher than in PLA condition (11.8 ± 1.0 km·h⁻¹ vs 11.4 ± 1.2 km·h⁻¹; F = 6.200; P = 0.034; ŋp² = 0.408). HR and RPE values in CER condition were not different from PLA condition.
Conclusions
Our main finding was that the use of bioceramic clothes (CER) increased MV when compared to the PLA condition. Based on these results, bioceramic may be used as an ergogenic resource to increase performance.
... vez que ela parece re etir as respostas integradas de diferentes sistemas, combinando as alterações siológicas e psicológicas 8,15,17,[32][33] . De fato, os dados observados no presente estudo corroboram outros trabalhos que sugerem a importante in uência da PSE sobre os ajustes da estratégia de prova 15,17,[34][35] . ...
... As altas velocidades iniciais observadas no nosso estudo podem ter ocorrido devido à baixa PSE; ou seja, os atletas se sentiam confortáveis para correr em altas velocidades. Esses resultados são suportados pelo estudo de B et al. 34 . Os autores observaram que a PSE foi o único fator determinante da velocidade nos primeiros 400 m em uma corrida de 10 km. ...
... Em resumo, os achados do presente estudo con rmam os resultados observados na literatura 15,17,[34][35] , sugerindo que corredores com nível amador, porém experientes em provas de média e longa distâncias, ajustam a estratégia de prova durante uma corrida de 10 km conforme a PSE. Assim como demonstrado por D K et al. 17 em esteira, os resultados do presente estudo sugerem que em provas de pista o risco de fadiga prematura parece ser fundamental para a realização do "sprint"-nal. ...
O objetivo do estudo foi verificar as modificações na estratégia de prova frente às alterações do risco de fadiga prematura e da percepção subjetiva de esforço (PSE) em corredores durante uma corrida de 10 km. Participaram do estudo 55 corredores com tempo nos 10 km de 41:39 ± 3:52 min:s. A estratégia de prova e a PSE foram avaliadas a cada quilômetro. O risco de fadiga prematura foi determinado pelo produto entre a PSE e a distância restante de prova e a estratégia de prova foi determinada pela curva da velocidade e distância. A ANOVA de um caminho para medidas repetidas foi utilizada para determinar as diferenças na velocidade, PSE e risco de fadiga a cada quilômetro e entre a velocidade a cada quilômetro e a velocidade média da prova. O coeficiente de correlação de Pearson foi calculado entre a PSE e o risco de fadiga prematura com a velocidade. A velocidade do primeiro quilômetro foi 8,1% maior do que a média (p ≤ 0,001). A velocidade diminuiu gradualmente ao longo da prova, ocorrendo um novo aumento no décimo quilômetro. A PSE aumentou linearmente ao longo da prova e o risco de fadiga diminuiu significantemente após o terceiro quilômetro. Houve forte correlação negativa entre a PSE e a velocidade desenvolvida durante a prova (r = -0,80; p = 0,006). Foi observada uma correlação moderada negativa entre o risco de fadiga prematura e a velocidade (r = -0,57; p = 0,04). Com isso, os achados do presente estudo sugerem que a PSE parece ter importante papel sobre os ajustes da velocidade ao longo da prova, sendo que o aumento da velocidade observado no último quilômetro pode estar associado ao baixo risco de fadiga prematura.
... Pacing strategy has been defined as the distribution of speed, and consequently energy expenditure, during an athletic competition (Abbiss and Laursen 2008), being an important determinant of athletic performance (Bertuzzi et al. 2014). It is believed that athletes choose an appropriate running speed in order to avoid premature exhaustion and therefore optimize their overall performance (Thiel et al. 2012). ...
... For example, Lima-Silva et al. (2010) observed that runners with a higher running economy (RE), peak treadmill speed (PTS), and a faster speed corresponding to the onset of blood lactate accumulation were able to adopt a more aggressive U-shaped speed curve, probably due to reduced afferent signals during the race. Using a stepwise multiple regression model, a recent study showed that maximum dynamic strength (1RM), PTS, and maximal oxygen uptake (VO 2 max) explained 80 % of the speed variation during the middle (400-9600 m) of a 10-km running time trial (Bertuzzi et al. 2014). Interestingly, PTS, which integrates aerobic power, anaerobic capacity, and neuromuscular capability, was the only variable able to predict the end-spurt (last 400 m), accounting alone for 66 % of the pacing variance. ...
... The ability of the skeletal muscles to produce force has been related to both neural and metabolic factors (Aagaard and Mayer 2007). In this respect, previous studies have used vertical jump (Mikkola et al. 2011), all-out exercises (Rønnestad et al. 2014), iEMG (Mikkola et al. 2007), and 1RM tests (Bertuzzi et al. 2014) to assess the neuromuscular and anaerobic adaptations provided by strength training in long-distance athletes. An improved ability to produce maximal and explosive strength would be expected when participants who have no prior strength training experience complete a 4-to 8-week ST program. ...
The purpose of this study was to analyze the impact of an 8-week strength training program on the neuromuscular characteristics and pacing adopted by runners during a self-paced endurance running.
Eighteen endurance runners were allocated into either strength training group (STG, n = 9) or control group (CG, n = 9) and performed the following tests before and after the training period: (a) incremental test, (b) running speed-constant test, (c) 10-km running time trial, (d) drop jump test, (e) 30-s Wingate anaerobic test, (f) maximum dynamic strength test (1RM). During 1RM, the electromyographic activity was measured.
In the STG, the magnitude of improvement for 1RM (23.0 ± 4.2 %, P = 0.001), drop jump (12.7 ± 4.6 %, P = 0.039), and peak treadmill speed (2.9 ± 0.8 %, P = 0.013) was significantly higher compared to CG. This increase in the 1RM for STG was accompanied by a tendency to a higher electromyographic activity (P = 0.080). The magnitude of improvement for 10-km running performance was higher (2.5 %) for STG than for CG (-0.7 %, P = 0.039). Performance was improved mainly due to higher speeds during the last seven laps (last 2800 m) of the 10-km running trial. There were no significant differences between before and after training period for maximal oxygen uptake, respiratory compensation point, running economy, and anaerobic performance for both groups (P > 0.05).
These findings suggest that a strength training program offers a potent stimulus to counteract fatigue during the last parts of a 10-km running race, resulting in an improved overall running performance.
... Because no significant change in body mass occurred in either group to suggest hypertrophy, the observed 1RM increases likely stemmed from positive neural adaptations 14,16,37,38 . Although electromyographic analyses were not performed here, Mikkola et al. 37 showed that greater leg press 1RM following HST was accompanied by enhanced EMG activity in recreational endurance runners. ...
... Storen et al. 14 likewise noted improvements of 33% and 26% in half squat 1RM and rate of force development, respectively, which accompanied a 21% a greater TTE at maximal aerobic speed following HST in well trained runners. Bertuzzi et al. 38 found that running speed during the intermediate stage of a 10 km time trial (400-9600m) was partially attributed to squat 1RM, in addition to VO2max and velocity at VO2max. As supported by these findings, greater force producing capability is postulated to lower the relative force required per stride, which may delay fatigue 39 . ...
Background:
The purpose of this study was to compare the effects of supplementing habitual run training with periodized lower body strength training versus high intensity circuit strength training on running performance and related variables in experienced runners.
Methods:
Nineteen (N.=19) participants performed 8 weeks of 2 d·wk-1 periodized lower body strength training (PLB), N.=9, or high intensity circuit training (CT), N.=10. PLB sessions included 2 sets of the back squat, standing calf raise, leg press, and dumbbell lunge, with intensity linearly periodized. CT sessions simulated CrossFit-style programming and included 2-4 heavy (>10-RM) sets of a compound lift, followed by a high intensity, whole body resistance circuit. Three-km time trial (TT), V̇O 2 max, relative leg press 1-RM, running economy (RE) at 2 standard submaximal velocities (SV1, SV2) between 11 and 14 km∙hr-1, RPE at SV1/SV2, and peak/mean power were assessed pre and post-intervention.
Results:
Similar (P≤0.02) increases occurred in RE at 11 km∙hr-1 (36.4±3.1 to 35.4±2.4 mL·kg-1·min-1) and RPE at SV1 (12.5±1.3 to 11.4±1.6). Relative 1-RM (2.54±0.41 to 3.40±0.72) and RPE at SV2 (14.1±1.3 to 12.9±1.8) improved in both groups (P≤0.03). However, PLB showed larger improvements in 1-RM (0.43±0.18 vs. 0.2±1.9, t=2.75, P=0.015) and RPE at SV2 (-1.75±0.9 vs. -0.63±1.1, t=2.30, P=0.037). TT, V̇O 2 max, RE at 12-14 km∙hr-1, and power were unchanged (P≥0.27).
Conclusions:
PLB and CT enhanced 1-RM, RE at 11 km∙hr-1 and RPE at SV1/SV2, but neither modality improved TT performance, V̇O 2 max, anaerobic power, or RE at faster velocities. PLB resulted in greater improvements in 1-RM and RPE at SV2.
... The 10-km mean velocity (MV) for each trial was calculated by dividing the total distance by the trial duration. Additionally, partial MVs were calculated in three phases: (1) start (first 400 m), (2) middle (400-9600 m) and (3) end (last 400 m), as previously reported [25,26]. ...
... This strategy is commonly used by moderate and high-performance runners [26,42]. After assessing the contribution of some physiological and muscular variables to the rhythm strategy adopted during the 10 km running performance, Bertuzzi et al. [25] concluded that V peak , V O 2max and 1 maximum repetition are the variables that best explain the performance in the intermediate phase (0.4-9.6 km) and only V peak in the final phase (9.6-10 km), reaffirming its high performance prediction capacity for this type of test. ...
Objectives
The aim of this study was to determine the peak running velocity on the track field (V peak_TF ) based on the laboratory treadmill test (V peak_T ), and relate the V peak values as well as their correlation with the 10-km running performance in trained endurance runners.
Method
Twenty male trained endurance runners (age: 29.5 ± 5.3 years; V̇O 2max : 67.5±17.6 ml · kg ⁻¹ ·min ⁻¹ ) performed three maximum incremental tests to determine the V peak : one for V peak_T determination and two to obtain V peak_TF on the official track field (400 m), and a 10-km running performance. During the incremental tests, maximum heart rate (HR max ), maximal rating of perceived exertion (RPE max ), and peak lactate concentration (LA peak ) were determined.
Results
The results showed significant difference between the V peak_TF and V peak_T (18.1 ± 1.2 vs . 19.2 ± 1.5 km·h ⁻¹ , respectively), as well as the total time of the tests, the distance traveled and the RPE max determined during the tests. A high correlation was observed between the V peak values (r = 0.94), and between V peak_TF and V peak_T with 10-km running performance (r = -0.95 vs . r = -0.89, respectively).
Conclusions
The good agreement and association with V peak_T and high correlation with 10-km running performance demonstrate that the novel track field test is efficient for V peak_TF determination.
... Additionally, partial MV were calculated in three phases: (1) start (first 400 m), (2) middle (400-9.600 m) and (3) end (last 400 m), as previously reported 1,17 . Mineral water was provided ad libitum in cups throughout performances, so that runners could hydrate themselves as they were used to do in long-distance races. ...
... Caffeine appears to stimulate a faster onset of performance, which may be related to its potential ergogenic effects, mainly the effect of the stimulant on the central nervous system (CNS), thus increasing alertness and reducing perceived exertion 31 . Bertuzzi et al. 17 , concluded after evaluating the contribution of some physiological and muscular variables for the pacing strategy adopted during 10-km running performance running, that the rating of perceived exertion is the variables that best explain the performance in the start phase (0.4 km) of the 10-km running performance, and its reduction may have been responsible for making runners perceive a slower speed or effort than they actually are performing. ...
Background: Long distance practice running are growing and nutritional ergogenic are commonly used as a potential aid in final training and competition performance. Caffeine (CAF) and carbohydrates (CHO) are among the most commonly used supplements due to their expected ergogenic properties that can optimize energetic systems. The objective of this study was to examine potential changes in 10-km running performance with acute isolated and combined CAF and CHO supplementation. Material and method: Fifteen recreational endurance-trained runners performed four 10-km running performance on an official athletic track (400 m) under four supplementation conditions: placebo and placebo (PLA+PLA), placebo and caffeine (PLA+CAF), placebo and carbohydrates (PLA+CHO), caffeine and carbohydrates (CAF+CHO). CAF and CHO supplementation consisted of capsules of 6 mg·kg-1 and 8% CHO solution (1 g·kg-1) respectively, ingested 60 and 30 minutes before the performance tests. Placebo was obtained through empty capsules for CAF and juice for CHO without sugar (Clight®). During each trial running speed to calculate 10-km mean velocity (MV) and maximum heart rate (HRmax) were analyzed. Results: There was a difference in the pacing strategy adopted by the runners with higher MV during the initial phase for PLA+CAF and CAF+CHO groups and in the final phase for PLA+ CHO. However, there was no statistically significant difference in 10-km running performance between the conditions, as well as for HRmax. Conclusions: The use of acute, isolated and combined CAF+CHO supplementation had influence in the pacing strategy, but no in 10- km final performance, of recreational runners.
... This individual response to the enforced fast start was not associated with 10-km performance since the athletes in the PR group were not the most trained or faster when compared with NR, but the differences seems to be related to physiological parameters. 6,22 Lima-Silva et al 6 showed that the capacity to adopt a fast-start strategy in high-level runners was correlated with higher RE and treadmill PV during a graded exercise test. Bertuzzi et al 22 confirmed these results and showed that PV may do Carmo et al explain 55% of the speed variation in the middle phase and 66% of the variation during the end spurt in 10-km running. ...
... 6,22 Lima-Silva et al 6 showed that the capacity to adopt a fast-start strategy in high-level runners was correlated with higher RE and treadmill PV during a graded exercise test. Bertuzzi et al 22 confirmed these results and showed that PV may do Carmo et al explain 55% of the speed variation in the middle phase and 66% of the variation during the end spurt in 10-km running. Our results corroborated those of previous studies, since we observed higher PV and vVO 2max in the PR group than in NR. ...
The effects of an enforced fast-start on long distance performance are controversial and seem to depend on the athlete's capacity to delay and tolerate metabolic disruption. The aim of this study was to investigate the effects of an enforced fast-start on 10-km running performance and the influence of the some physiological and performance variables on the ability to tolerate an enforced fast-start during the running. Fifteen moderately-trained runners performed two 10-km time-trials: free-pacing (FP-TT) and fast-start (FS-TT). During FS-TT, speed during the first kilometer was 6% higher than in FP-TT. Maximal oxygen uptake (VO2max), peak velocity (PV), velocity associated with VO2max (vVO2max), ventilatory threshold, and running economy (RE) at 10 km·h-1, 12 km·h-1 and FP-TT average velocity (AV-10 km) were individually determined. There were no differences between FP-TT and FS-TT performance (45:01 ± 4:08 vs 45:11 ± 4:46 min:s, respectively, p=0.4). We observed that eight participants improved (+2.2%) their performance and were classified as positive responders (PR) and seven decreased (-3.3%) performance and were classified as negative responders (NR). Running speed was significantly higher for PR between 6 km and 9.2 km (p<0.05) during FS-TT. In addition, PR presented higher PV (p=0.02) and vVO2max (p= 0.01) than NR, suggesting the PV and vVO2max might influence the ability to tolerate a fast-start strategy. In conclusion, there was an individual response to the enforced fast-start strategy during 10-km running, and those who improved performance also presented higher vVO2max and PV, suggesting a possible association between these variables and response to the strategy adopted.
... Uma alternativa que vem sendo utilizada é analisar o pacing por trechos da prova (HETTINGA et al., 2006;LIMA-SILVA et al., 2010;BERTUZZI et al., 2014). Neste contexto, Hettinga et al. (2006) dividiu o pacing de um contrarrelógio de 4-km de ciclismo em dois trechos pela metade da prova, dividindo em 2.000 m iniciais e 2.000 m finais para manipular diferentes padrões de pacing. ...
... Neste contexto, Hettinga et al. (2006) dividiu o pacing de um contrarrelógio de 4-km de ciclismo em dois trechos pela metade da prova, dividindo em 2.000 m iniciais e 2.000 m finais para manipular diferentes padrões de pacing. Para analisar o pacing parabólico, a divisão em três trechos da prova leva em conta o início, meio e fim (LIMA-SILVA et al., 2010;BERTUZZI et al., 2014). ...
The selection of pacing is determinant for the sport success, but the analysis of modest variations in pacing requires further studies. The purpose of this study was to determine parameters in the performance curve on cycling time trial to investigate pacing variations and reproducibility. The test sections analysis was also performed. 19 amateur cyclists performed two tests of 4-km, in which parameters were analyzed in the individual performance curves and the average power of the test sections. The time and the average power were similar between tests. There was no difference between the parameters observed in the performance curve comparing the test 1 and 2, but these showed a high value of typical error. The test portions analysis was more consistent, with an alternative to analyze pacing. Despite consistent performance in time trial 4-km, the parameters determined varied widely between individuals.
... It was previously demonstrated that the time needed for the stabilization of physiological variables (e.g., oxygen uptake) that are important for this event was greater than the time required to complete this first section of the run (36). In this context, Bertuzzi et al. (33) demonstrated that in a 10-km running time trial, only the rate of perceived exertion accounted for the variance of speed during the start phase. Therefore, the authors suggest that psychological factors may be more important during the early stages of a running race than physiological factors (33). ...
... In this context, Bertuzzi et al. (33) demonstrated that in a 10-km running time trial, only the rate of perceived exertion accounted for the variance of speed during the start phase. Therefore, the authors suggest that psychological factors may be more important during the early stages of a running race than physiological factors (33). This could explain the results found in the present study, because the first 400 m were not correlated with any measured physiological variable. ...
This study aimed to verify the association between the contribution of energy systems during an incremental exercise test (IET), pacing, and performance during a 10-km running time trial. Thirteen male recreational runners completed an incremental exercise test on a treadmill to determine the respiratory compensation point (RCP), maximal oxygen uptake (V˙O2max), peak treadmill speed (PTS), and energy systems contribution; and a 10-km running time trial (T10-km) to determine endurance performance. The fractions of the aerobic (WAER) and glycolytic (WGLYCOL) contributions were calculated for each stage based on the oxygen uptake and the oxygen energy equivalents derived by blood lactate accumulation, respectively. Total metabolic demand (WTOTAL) was the sum of these two energy systems. Endurance performance during the T10-km was moderately correlated with RCP, V˙O2maxand PTS (P<@0.05), and moderate-to-highly correlated with WAER, WGLYCOL, and WTOTAL (P<0.05). In addition, WAER, WGLYCOL, and WTOTAL were also significantly correlated with running speed in the middle (P<0.01) and final (P<0.01) sections of the T10-km. These findings suggest that the assessment of energy contribution during IET is potentially useful as an alternative variable in the evaluation of endurance runners, especially because of its relationship with specific parts of a long-distance race.
... Therefore, the main aim of the present study was to analyze the influence of competitors on pacing, overall performance, and mood state profile during a middle-distance running time trial. Based on previous findings suggesting that internal cues from cardiorespiratory and neuromuscular systems have low influence during the initial phase of a middle distance running race [21], it was hypothesized that during head-to-head competition the runners would adopt a more intense running speed at the beginning of a 3-km running. This increased running speed at the start might carry to an improved overall performance, but at the expense of a greater exercise-induced decrement in vigor and increment in fatigue, compared with individual running. ...
... It has Table 3 Correlations between physiological variables and magnitude of difference between running speeds during collective and individual conditions (n = 9). been suggested that the existence of a "perceptive zone" of speed control during the first 400 m of the race in which physiological cues used in the processing of the pacing (e.g., blood lactate accumulation, minute ventilation, and heart rate responses) is low [21]. This suggests that the presence of competitors induces a more aggressive fast start because the initial phase of the trial appears to be less influenced by physiological feedback and, therefore, more susceptible to the influence of the external cues. ...
... a final sprint during the last 400 m (1,3,4,20,42). This speed distribution pattern may reflect a complex process that regulates exercise intensity to prevent homeostasis failure in bodily systems (24,40). ...
... In addition, a H CHO diet was inferred to be possibly beneficial and a L CHO diet as possibly harmful for overall performance, compared with the N CHO diet. The higher running speed at the start and at the final (compared with the middle of the race) found in the current study for all dietary regimens is in line with previous studies with adult runners running a 10,000 m race (1,3,4,20,42). A similar pacing pattern has been found in studies with younger participants (age range from 11 to 14 yr); however, these patterns were found for shorter running distances (~750-900 m) and in untrained/inexperienced participants (7,18,23). ...
This study analyzed the pacing employed by young runners in 10,000 m time-trials under three dietary regimens of different carbohydrate (CHO) intakes. Nineteen boys (13-18 years-old) ate either their normal-CHO diet (56% CHO), high- (70% CHO), or low- (25% CHO) CHO diets for 48 h; the boys then performed a 10,000 m run (crossover design). The high-CHO diet led to faster final sprint (14.4 ± 2.2 km·h-1) and a better performance (50.0 ± 7.0 min) compared with the low-CHO diet (13.3 ± 2.4 km·h-1 and 51.9 ± 8.3 min, respectively, p < 0.05). However, the final sprint and performance time in the high-CHO or low-CHO diets were statistically not significantly different from the normal-CHO diet (13.8 ± 2.2 km·h-1 and 50.9 ± 7.4 min; p > 0.05). CHO oxidation rate during the constant load exercise at 65% of VO2max was elevated in high-CHO diet (1.05 ± 0.38 g·min-1) compared with low-CHO diet (0.63 ± 0.36 g·min-1). The rating of perceived exertion increased linearly throughout the trial, independently of the dietary regimen. In conclusion, the high-CHO diet induced higher CHO oxidation rates, increased running speed in the final 400 m and enhanced overall running performance, compared with low-CHO.
... Based on this finding, it is plausible to suggest that the greater RPE found during the start phase after SS may reflect an increased neural drive resulting from intention to produce the same amount of force and thus maintain a high initial running speed. This is in agreement with a previous suggestion that RPE has a relevant role in the speed control during the start phase of a running race [42]. ...
... Taking into consideration the fact that the 3-km running was performed with an average time of 11 min, it can be suggested that the negative effects of SS on overall exercise performance was negligible. Thus, the negative effect of the SS in running performance might be restricted to the initial phase of a middle-distance event when the metabolic cues are less important for the running pacing strategy [42]. ...
Purpose
Previous studies report that static stretching (SS) impairs running economy. Assuming that pacing strategy relies on rate of energy use, this study aimed to determine whether SS would modify pacing strategy and performance in a 3-km running time-trial.
Methods
Eleven recreational distance runners performed a) a constant-speed running test without previous SS and a maximal incremental treadmill test; b) an anthropometric assessment and a constant-speed running test with previous SS; c) a 3-km time-trial familiarization on an outdoor 400-m track; d and e) two 3-km time-trials, one with SS (experimental situation) and another without (control situation) previous static stretching. The order of the sessions d and e were randomized in a counterbalanced fashion. Sit-and-reach and drop jump tests were performed before the 3-km running time-trial in the control situation and before and after stretching exercises in the SS. Running economy, stride parameters, and electromyographic activity (EMG) of vastus medialis (VM), biceps femoris (BF) and gastrocnemius medialis (GA) were measured during the constant-speed tests.
Results
The overall running time did not change with condition (SS 11:35±00:31 s; control 11:28±00:41 s, p = 0.304), but the first 100 m was completed at a significantly lower velocity after SS. Surprisingly, SS did not modify the running economy, but the iEMG for the BF (+22.6%, p = 0.031), stride duration (+2.1%, p = 0.053) and range of motion (+11.1%, p = 0.0001) were significantly modified. Drop jump height decreased following SS (−9.2%, p = 0.001).
Conclusion
Static stretch impaired neuromuscular function, resulting in a slow start during a 3-km running time-trial, thus demonstrating the fundamental role of the neuromuscular system in the self-selected speed during the initial phase of the race.
... Variable self-pacing has been shown to present certain advantages, that is, enhancement of critical power and high-intensity exercise performance compared to constant work rate cycling exercise [50]. In addition, the rate of perceived exertion has been shown to be associated with pacing [51] and might vary across races [52]. Moreover, compared to running alone, it was found that head-to-head competition performance improved [53]. ...
Background
Ultramarathon running is the most popular ultraendurance competition in terms of the number of races and runners competing annually worldwide; however, no study has compared pacing and performance over a long period.
Objective
This study analyzes the pacing of successful finishers and nonfinishers in multistage ultramarathons worldwide.
MethodsA total of 4079 athletes (men=3288; women=791) competing in 99 multistage ultramarathon events from 1983 to 2021 were analyzed, including the number of participants, age, gender, rank, and running speed of successful finishers.
ResultsThe results showed a significant increase in the number of events (n=338) and a significant increase in the number of finishers and nonfinishers (n=5575) in the ultramarathons worldwide during this period. The general linear models (GLMs) of pacing variation showed nonsignificant effects for gender (F1,36.2=2.5; P=.127; ηp2=0.063) and age group (F10,10=0.6; P=.798; ηp2=0.367), but it showed a significant interaction (gender × age) effect (F10,2689=2.3; P=.008; ηp2=0.009). Post hoc analyses showed that men have a higher pacing variation than women in the under 30 years (U30), U35, U45, and U50 groups. Additionally, the fastest women’s age group (U35) had the lowest pacing variation. The GLM of pacing variation by gender and event distance showed significant effects for both gender (F1,3=18.5; P
... This finding agrees with cross-sectional studies reporting positive influences of diverse neuromuscular performances on pacing in endurance athletes. Intervention studies have suggested potentiation effects of strength exercises during warming up on the first laps of short time trials in runners, [124][125][126][127] cyclists, 128 and rowers, 129 without improving overall performance. Conversely, impaired neuromuscular function after static stretching 130 reduced the starting speed of 3km running trials without affecting the final time. ...
Scientific interest in pacing goes back >100 years. Contemporary interest, both as a feature of athletic competition and as a window into understanding fatigue, goes back >30 years. Pacing represents the pattern of energy use designed to produce a competitive result while managing fatigue of different origins. Pacing has been studied both against the clock and during head-to-head competition. Several models have been used to explain pacing, including the teleoanticipation model, the central governor model, the anticipatory-feedback-rating of perceived exertion model, the concept of a learned template, the affordance concept, the integrative governor theory, and as an explanation for "falling behind." Early studies, mostly using time-trial exercise, focused on the need to manage homeostatic disturbance. More recent studies, based on head-to-head competition, have focused on an improved understanding of how psychophysiology, beyond the gestalt concept of rating of perceived exertion, can be understood as a mediator of pacing and as an explanation for falling behind. More recent approaches to pacing have focused on the elements of decision making during sport and have expanded the role of psychophysiological responses including sensory-discriminatory, affective-motivational, and cognitive-evaluative dimensions. These approaches have expanded the understanding of variations in pacing, particularly during head-to-head competition.
... Running endurance performance has been traditionally associated with several physiological variables, including running economy (RE) (1)(2)(3)(4)(5). Individuals with superior RE, defined as the steady-state oxygen uptake at submaximal running speeds (4), are able to sustain higher exercise intensities and/or maintain the same exercise intensity for a longer period of time compared to their counterparts with poorer RE (6). ...
The present study compared the effects of a footwear designed to enhance energy return (thermoplastic polyurethane, TPU) vs minimalist shoes on running economy (RE) and endurance performance. In this counterbalanced and crossover design study, 11 recreational male runners performed two submaximal constant-speed running tests and two 3-km time-trials with the two shoe models. Oxygen uptake was measured during submaximal constant-speed running tests in order to determine the RE at 12 km/h and oxygen cost of running (CTO2) at individual average speed sustained during the 3-km running time-trials wearing either of the two shoes. Our results revealed that RE was improved (2.4%) with TPU shoes compared with minimalist shoes (P=0.01). However, there was no significant difference for CTO2 (P=0.61) and running performance (P=0.52) comparing the TPU (710±60 s) and the minimalist (718±63 s) shoe models. These novel findings demonstrate that shoes with enhanced mechanical energy return (i.e. TPU) produced a lower energy cost of running at low (i.e., 12 km/h) but not at high speeds (i.e., average speed sustained during the 3-km running time-trial, ∼15 km/h), ultimately resulting in similar running performance compared to the minimalist shoe.
... Studies analyzed running speed during a 10-km race and identified an association between physiological parameters and running speed (Bertuzzi, et al., 2014;Lima-Silva, et al., 2010), by both field methods and laboratory tests. Among the laboratory methods, the anaerobic threshold (AT) seems to be a good predictor of running speed because it represents the moment of transition from the predominance of aerobic energy production to the anaerobic energy production (Faude, Kindermann, & Meyer, 2009) and has been described in some studies with runners (da Silva, et al., 2015;Souza, et al., 2014Souza, et al., , 2011 since AT corresponds to an intensity of effort that can be maintained with a stable state of oxygen and lactate consumption . ...
Knowing running speed, particularly by means of easy-to-apply tests and low cost, is important to the definition of race strategy and of the most appropriate training throughout the preparation period. The aim was to compare the agreement and reproducibility of critical velocity (CV), anaerobic threshold (AT), and the time trial on the track for the determination of the running speed in a 10-km race in amateur runners. A cross-sectional study was conducted with 34 runners of both genders aged 42.4±11.0 years. We measured their CV, assessed their body composition and AT. Participants also performed a simulated trial on a 10-km running track and an official 10-km race. The delta of the comparisons and the standard error of estimate between the running velocities determined by the CV, AT, and the simulated time trial on the track ranged from 0.55 to-0.79 km/h and 0.14 to 0.59 km/h, respectively. Furthermore, CV and AT were compared to the 10-km running speed. Good agreement and reproducibility were observed between the velocities determined by the CV, AT, and the simulated time trial on the track with the real-time of a 10-km official race.
... Fatigue during endurance exercise can be stated as perceived tiredness with concurrent decrements in muscular performance and function [4]. Typically, the body needs to adjust to the growing demand of the activity performed by increasing heart rate [5][6][7], oxygen consumption, [5][6][7] and perceived effort [8] at a given workload. The autonomic nervous system responds to exercise by increasing sympathetic drive and catecholamine secretion [9], while parasympathetic activity diminishes [10]. ...
This study investigated acute responses and post 24-h recovery to four running sessions performed at different intensity zones by supine heart rate variability, countermovement jump, and a submaximal running test. A total of 24 recreationally endurance-trained male subjects performed 90 min low-intensity (LIT), 30 min moderate-intensity (MOD), 6×3 min high-intensity interval (HIIT) and 10×30 s supramaximal-intensity interval (SMIT) exercises on a treadmill. Heart rate variability decreased acutely after all sessions, and the decrease was greater after MOD compared to LIT and SMIT (p<0.001; p<0.01) and HIIT compared to LIT (p<0.01). Countermovement jump decreased only after LIT (p<0.01) and SMIT (p<0.001), and the relative changes were different compared to MOD (p<0.01) and HIIT (p<0.001). Countermovement jump remained decreased at 24 h after SMIT (p<0.05). Heart rate during the submaximal running test rebounded below the baseline 24 h after all sessions (p<0.05), while the rating of perceived exertion during the running test remained elevated after HIIT (p<0.05) and SMIT (p<0.01). The current results highlight differences in the physiological demands of the running sessions, and distinct recovery patterns of the measured aspects of performance. Based on these results, assessments of performance and recovery from multiple perspectives may provide valuable information for endurance athletes, and help to improve the quality of training monitoring.
... A specialist investigator, who was expert in race walking, classified each pacing profile as one of the five possible patterns (positive, negative, even, parabolic, or variable). In accordance with previous study, the pacing strategy (%max) was divided into three phases, start (0-20%), middle (20-80%) and end (80-100%) [14,26]. Data were compared between sexes (female, n = 18; male, n = 16), distances (10-km, n = 11; 20-km, n = 18) and performance levels. ...
Background
The pacing strategy of endurance athletes has been well investigated in previous articles. However, few studies have compared the influence of sex, distance and performance level on the pacing strategy in race walkers.AimsTo compare the influence of sex, distance and performance levels on pacing strategies in race walking competitions.Methods
Thirty-four highly trained athletes (16 male 23.6 ± 7.4, 18 female 23.7 ± 7.0 years old) were recruited. The speed in km.h−1 was calculated, and later, normalized by the percentage of the maximum speed (%max). The pacing strategy (%max) were divided into start, middle and end phases and compared between sexes, distances and performance levels.ResultsThere was no relationship between the phases according to sex (F (2) = 0.06, p = .94, pn2 < 0.01) and distance (F (2) = 1.89, p = 0.16, pn2 = 0.05). There was an effect between phases and performance levels (F (4) = 2.94, p = 0.03, pn2 = 0.16), indicating that the medallists were more able to maintain the starting speed compared to non-medallists. Sex of the race walkers and race distance did not influence the pacing strategy.Conclusions
In summary, medallist athletes maintained their starting speed in the race, which is not performed by non-medallists, that decreased the speed during middle and end phase of the race. Evenly paced pacing strategy, with a careful starting speed can increase the possibility of success during race walking competitions.
... Perhaps our proposed index of PERFI is a concept similar to race economy (14,26). In fact, as suggested by one study, during a 10 km time trial race, the predictors of pacing strategy were the transition behaviour between perception at the start of the muscular and physiological factors during the middle and last stages (2). For example, a runner described this association between perception and physiology: "you have the fatigue that sets in, you've got your legs beginning to be heavy". ...
International Journal of Exercise Science 13(5): 615-632, 2020. The purpose of this study was to better understand the psychological momentum (PM) in varsity crosscountry competitive runners during a 3000 m selection trials. A sequential explanatory mixed methods design was used: recruitment trial race day (quantitative) and interview day (qualitative + maximal aerobic running speed [MARS]). Sample was consisted of fifteen university distance runners (n = six women [25.9 ± 7.0 years old; 22.2 ± 1.8 BMI] and nine men [23.2 ± 2.4 years old; 22.6 ± 1.6 BMI]). During the recruitment trial race, athletes' MARS was measured and used to create a performance index (PERFI) relative to selected moments. Also, the recruitment trial race was filmed. During the interviews, the recorded film was used to support athletes in the identification of key moments of the race, as well as to discuss positive and negative PM. PM was both defined by participants and devised by three themes: psychological, physiological and psychophysiological change. A significant PERFI difference (p < 0.001) was observed between positive (97.04 ± 5.88%) and negative (108.46 ± 7.76%) moments of PM. The results of PERFI for men and women athletes were not significantly different (p = 0.118). The PERFI standard deviation for women was not correlated (r 2 = 0.26, p = 0.30) with the 3000 m time trial performance, but it was significantly correlated for men (r 2 = 0.94, p < 0.001). The results of the present study could help developing interventions to focus on specific elements of the momentum such as race management/strategy, the attentiveness of the runner during the race and other elements of mental and physical preparation of the athletes.
... Lansley et al. [15] showed that nitrate supplementation (6.2 mmol of nitrate in beetroot juice) for six days decreased 7% the oxygen amount required for constant rate moderate work and 15% in severe intensity running. Therefore, the low cost of oxygen in exercises with submaximal intensity, the greater mitochondrial efficiency, and physiological responses of fast twitch fibers (type II fibers), which can reduce NO 3 to NO 2 , improving local perfusion, fatigue resistance, and muscle fiber contraction could improve performance of runners in sprint races [11,16,17]. ...
Our purpose was to verify the effects of inorganic nitrate combined to a short training program on 10-km running time-trial (TT) performance, maximum and average power on a Wingate test, and lactate concentration ([La−]) in recreational runners. Sixteen healthy participants were divided randomly into two groups: Nitrate (n = 8) and placebo (n = 8). The experimental group ingested 750 mg/day (~12 mmol) of nitrate plus 5 g of resistant starch, and the control group ingested 6 g of resistant starch, for 30 days. All variables were assessed at baseline and weekly over 30 days. Training took place 3x/week. The time on a 10-km TT decreased significantly (p < 0.001) in all timepoints compared to baseline in both groups, but only the nitrate group was faster in week 2 compared to 1. There was a significant group × time interaction (p < 0.001) with lower [La] in the nitrate group at week 2 (p = 0.032), week 3 (p = 0.002), and week 4 (p = 0.003). There was a significant group time interaction (p = 0.028) for Wingate average power and a main effect of time for maximum power (p < 0.001) and [La−] for the 60-s Wingate test. In conclusion, nitrate ingestion during a four-week running program improved 10-km TT performance and kept blood [La−] steady when compared to placebo in recreational runners.
... It was expected that BRJ supplementation modify the MV of the intermediate part of the test, since studies point to an improvement in the VO 2max and a reduced O 2 cost after BRJ supplementation [1,4]. In addition, VO 2max along with the peak velocity on the treadmill and 1 RM are the variables that best explain the performance in the intermediate phase of the running performance according to Bertuzzi et al. [6], after evaluating the contribution of some physiological and muscular variables to the strategy of run during a performance of 10 km. However, this improvement in velocity was not observed in the intermediate part of the present study. ...
Introduction
The aim of the study was to analyze the acute effect of beetroot juice supplementation in untrained women 30 minutes before a 3-km running performance.
Summary of facts and results
Eight untrained woman (30.1 ± 5.7 years old) performed two 3-km running performances on an official track, supplemented with beetroot juice (S) (500 mL, 8.4 mmol/NO3⁻) ingested 30 minutes before performance and without supplementation (C), in a randomized order. Pre- and post-running, glycemic index (Glycpost and Glycpre) was analyzed and the blood lactate concentration was measured to determine the lactate peak (Lapeak). The maximal rating of perceived exertion (RPEmax), maximal heart rate (HRmax) and time performance were monitored at each trial. The RPEmax was significantly high for the condition S in relation to C (19.3 ± 1.2 vs 18.3 ± 1.7, P = 0.039) whereas, Glycpost was statistically higher in condition C compared to that in condition S (89.4 ± 17.4 vs 80.6 ± 17.4 mg·dL⁻¹, P = 0.036). In addition, the supplementation showed altered test pacing strategy. No statistical differences were found for 3-km running performance; HRmax, Lapeak and Glycpre.
Conclusion
The analysis concluded that untrained women supplemented with 500 mL of beetroot juice 30 minutes before a 3-km running performance presented a modified RPE and Glycpost, with no significant differences in HRmax, Lapeak and Glycpre.
... Although it has been well accepted that aerobic fitness is highly dependent on cardiorespiratory system [17], several studies have also found a strong association between muscle strength and aerobic fitness [18,19]. Individuals with greater muscle strength could generate lower relative force at the same absolute running intensity. ...
... The mechanisms responsible for this greater variation are not clear, but they appear to be related to variable determinants of phase 1. It has been demonstrated that both physiological (Bishop et al., 2002) and psychological (Bertuzzi, Lima-Silva, et al., 2014) factors could influence this phase. As an example, previous works have seen a great influence of different warm up routines and greater power output at the phase 1 during a cycling time trial . ...
The present study proposed two models (visual and mathematical) to determine the three phases of “U”-pacing profile during a cycling time trial. The reliability of visual model was tested and models were compared. Fifteen cyclists performed a maximal incremental test and two 4-km TT. For the visual model, four experienced evaluators analysed twice the pacing, seven days apart. The mathematical model consisted on the mean of power output during phase 2 (1- until 3 km) plus two standard deviations, to distinguish phase 2 change points between phases 1 (CP1) and 3 (CP2). The CP1 occurred at 419 ± 186 and 415 ± 178 m for visual and mathematical model and CP2 occurred at 3646 ± 228 and 3809 ± 213 m, respectively. There was no difference between models for both CP (p >0.05). The within-evaluator visual model reliability for CP1 was ICC >0.87 and CP2 was ICC >0.96 (p <0.05), and between-evaluator reliability was ICC > 0.89 (p <0.05). Bland–Altman plots showed agreement between models, most the difference was <5%. The visual and mathematical models are reliable and produce similar values for determining main phases of the “U”-pacing profile during a cycling TT.
... Previous studies have observed a significant relationship between traditional physiological predictors of endurance performance and running pacing strategy (7)(8)(9). Lima-Silva et al. (9) reported that runners with a higher running economy (RE), peak treadmill speed (PTS), and a faster speed corresponding to onset of blood lactate accumulation (OBLA) presented a more aggressive U-shaped speed curve during a 10-km running race compared with their counterparts. In addition, high-performance athletes ran the first 1200 m of a 10-km race at a speed faster than the average speed of the entire race and above their PTS, while a low-performance group started the race with a less aggressive pacing strategy and slightly below the OBLA speed (9). ...
This study analyzed the influence of a 4-week high-intensity interval training on the pacing strategy adopted by runners during a 5-km running trial. Sixteen male recreational long-distance runners were randomly assigned to a control group (CON, n=8) or a high-intensity interval training group (HIIT, n=8). The HIIT group performed high-intensity interval-training twice per week, while the CON group maintained their regular training program. Before and after the training period, the runners performed an incremental exercise test to exhaustion to measure the onset of blood lactate accumulation, maximal oxygen uptake (VO2max), and peak treadmill speed (PTS). A submaximal constant-speed test to measure the running economy (RE) and a 5-km running trial on an outdoor track to establish pacing strategy and performance were also done. During the 5-km running trial, the rating of perceived exertion (RPE) and time to cover the 5-km trial (T5) were registered. After the training period, there were significant improvements in the HIIT group of ∼7 and 5% for RE (P=0.012) and PTS (P=0.019), respectively. There was no significant difference between the groups for VO2max (P=0.495) or onset of blood lactate accumulation (P=0.101). No difference was found in the parameters measured during the 5-km trial before the training period between HIIT and CON (P>0.05). These findings suggest that 4 weeks of HIIT can improve some traditional physiological variables related to endurance performance (RE and PTS), but it does not alter the perception of effort, pacing strategy, or overall performance during a 5-km running trial.
... Tradicionalmente, as principais variáveis que estão associadas com a desempenho de corredores de resistência, são o consumo máximo de oxigênio, limiar de lactato, limiar anaeróbio e a economia de corrida 1,2 . No entanto, dependendo das distâncias e a duração de uma corrida, o desempenho atlético parece ser influenciado pelas características fisiológicas 1, 2 , parâmetros antropométricos 3,4 , estratégia de corrida 5,6 , além de variáveis, como a idade 7 , sexo 4,7 e nutrição 8 . ...
O objetivo do presente estudo foi analisar o desempenho neuromuscular após a realização de uma corrida de 10.000 metros e examinar a associação entre a composição corporal e as variáveis neuromusculares com desempenho em prova (Pace e tempo de prova) em corredores amadores. Para tanto, 19 militares (28,5±2,3 anos) fizeram avaliação neuromuscular (força estática de pernas e preensão manual; força explosiva e flexibilidade), antropométrica e composição corpora antes e após uma prova de 10.000 metros. Foram observadas redução na força estática de pernas (P=0,034) e aumento da força explosiva (P=0,002) e flexibilidade (P=0,004) após a prova. Na análise de regressão linear múltipla, o somatório de dobras cutâneas foi relacionado ao tempo de prova e o Pace (p<0,05). Os resultados deste estudo indicam qua há alterações no desempenho neuromuscular após uma corrida de 10.000 metros e o desempenho da corrida está associado a composição corporal.
... Maximal strength test 8 The participants were familiarized with all procedures, equipment, and proper exercise techniques prior to data collection. The subjects' settings on the equipment were recorded to guarantee the same positioning across familiarization and testing sessions. ...
Background:
The aim of the present study was to determine whether physiological factors and maximal dynamic strength are able to determine the peak treadmill speed (PTS) in physically active individuals.
Methods:
One hundred and fifty physically active healthy males voluntarily visit the laboratory on three separate occasions and underwent the following activities: first visit: IPAQ (short version), anthropometric measurements, and a maximal incremental test performed for physiological variables (maximal oxygen uptake ( ) and respiratory compensation point (RCP); second visit: constant speed test for running economy (RE) measurement, and familiarization with the maximum dynamic strength (1RM) test in the leg press exercise; third visit: 1RM test.
Results:
The stepwise multiple regression model selected four independent variables to predict PTS (RCP, , RE, and 1RM). RCP explained 59% (p < 0.001) of variance in PTS, whereas , RE and 1RM accounted for additional 8% (p < 0.001), 4% (p < 0.001), and 1.4% (p = 0.038), respectively.
Conclusions:
In conclusion, the results of the present study demonstrate that PTS, an important predictor of endurance performance, is determined by both physiological (i.e., RCP, and RE) and muscular (1RM) parameters in healthy active individuals. These results demonstrate that, during a physical evaluation, PTS is able to represent physiological and muscular parameters of physically active individuals. This has the advantage during aerobic fitness evaluations of not requiring expensive equipment and specialized software.
... Aerobic fitness has been traditionally evaluated during incremental exercise tests, through the determination of some physiological parameters, such as the maximal oxygen consumption (), the Ventilatory Threshold (VT), and the Respiratory Compensation Point (RCP) [1][2][3]. As exercise intensity increases, oxidative metabolism alone cannot maintain the rate of ATP resynthesis, enhancing the anaerobic metabolism contribution at high [4]. ...
The purpose of this study was to verify the association between MCT1 polymorphism with physiological parameters related to aerobic fitness. A hundred fifty healthy male volunteers performed a maximal incremental running test to determine the speeds corresponding to Ventilatory Threshold (VT) and Respiratory Compensation Point (RCP). Participants were genotyped and divided in terciles based on the analyzed variables. Genotype frequencies were compared through chi-square test between lower (LT) and higher terciles (HT), with the lowest or highest values of each analyzed variable. MCT1 TT genotype was overrepresented in HT only for VT and showed a significantly higher odds ratio of belong to HT for VT compared only to AA (5.1). These results suggest that TT individuals could attain the VT and RCP at higher speeds, being able to sustain higher running speeds in lower exercise intensity domains. In other words, it is possible that individuals carrying the MCT1 TT genotype might run at higher speeds with lower fatigue signals, mimicking an inner aerobic fitness adaptation.
Objective: To find out the effect of 15 days of beetroot juice (BRJ) supplementation on 10 km time trial performance in trained distance runners of University level.Methods: Thirty trained athletes,15 males age = 26.3 y ± 1.52, height 170.5 ± 0.2 cm, and 15 females, age = 25.2 y ± 1.30, height 157.8 ± 0.3 cm were selected for the present study. Two experimental and two control groups were made consisting of males and females separately. The first group of male and female (Experimental Group) consumed the BRJdaily 250 ml/dayand the second group (Control Group) did not consume beetroot juice. Both groups underwent a regular athletics training programme. All the subjects were tested on Ten Km Time Trial (TT)performance before supplementation of BRJ and after 15 days of supplementation of BRJ. Results: The significant effect of BRJ supplementationwas observed (p < 0.05) between pre and post measures of 10 km TT in experimental group. BRJ supplementation significantly improved performance in 10 km TT in both groups (respectively male; P< 0.006; F=11.09, ES = .480, female; P < 0.000, F=40.45, ES = .771.Conclusion: Consumption of BRJ250 ml/day in improved 10 km time trial performance in traineddistance runners.
We investigated the effects of different performance goals (best time vs. beat the opponent) on pacing behaviour during a 10-km cycling race and explored the influence of different performance level of opponents on ratings of perceived exertion (RPE), affective feelings and self-efficacy. Thirteen cyclists performed two time-trials (TT) and two races against a faster (FAST +6%) or a slower (SLOW –3%) virtual opponent. Power output (PO), RPE, affective feelings and self-efficacy were recorded at each kilometre point. Race average and race phases [starting (P1 = first kilometre); first half (P2 = 2nd–5th kilometre); second half (P3 = 6th–9th kilometre) and final sprint (FS = last kilometre)] were analysed. There was no difference in performance, assessed by race time between conditions (p = .84). PO during TT was lower in P3 compared to FS (p = .03; ES 0.6; 90%CI 0.4–0.7). In SLOW and FAST, PO was higher in P1 compared to other phases (p < .05). PO in FS was higher in TT compared to FAST (p = .01; ES −0.97; 90%IC −1.4 to −0.5). RPE increased and affective feelings decreased during all conditions. Self-efficacy was stable through TT and SLOW, but decreased during FAST with higher values in P1 compared to P2 (p = .01; ES −1.1; 90%IC −1.6 to −0.6), P3 (p < .001; ES −2.2; 90%IC −2.8 to −1.6) and FS (p < .001; ES −2.6; 90%IC −3.3 to −1.8). Pacing behaviour, specifically starting and final sprint, was affected by virtual opponents independent of performance level, demonstrating the importance of goal orientation.
Highlights
• Adjustments in exercise intensity result from a complex decision-making process involving physiological, psychological, environmental and tactical information.
• Goal pursuit is an important determinant of pacing behaviour since athletes must balance their efforts with expectations of success.
• A competitive environment may be included to motivate participants to maintain their effort and at the same time to improve their self-confidence.
• The presence of a final sprint seems to be related to the goal orientation and perceived outcomes of success or failure.
O desempenho de corredores de longa-distância é estabelecido por uma complexa interação entre variáveis físicas, tais como consumo máximo de oxigênio, economia de corrida e limiares metabólicos. Sabe-se que o treinamento pliométrico e de longa-distância podem modificar a interação entre estas variáveis, porém, investigações adicionais sobre como ocorrem estas adaptações, bem como sua transferência para o desempenho são necessárias. Portanto, o presente estudo teve como objetivo investigar o efeito combinado do treinamento pliométrico e de longa-distância em variáveis constituintes do desempenho de corredores fundistas. A amostra foi composta por 23 corredores do sexo masculino, com idade entre 18 e 50 anos, especialistas em provas de 10-km, e divididos em dois grupos experimentais de treinamento: I) treinamento combinado (TP: pliométrico + longa-distância; n = 11); II) treinamento de longa-distância (TC: longa-distância; n = 12). Todos os atletas foram submetidos a três sessões de avaliações (momento 1 - pré), correspondentes as mensurações de parâmetros antropométricos, neuromusculares, cardiorrespiratórios (sessão 1 e 2), e de desempenho nos 10-km em pista (sessão 3). Após o término das avaliações iniciais, os atletas foram divididos de forma pareada nos grupos de treinamento combinado (TP) ou de longa-distância (TC) a partir do teste de desempenho obtido nos 10-km antes do início do treinamento, e em seguida, iniciaram as 8 semanas de treinamento. Ao final do protocolo experimental, os atletas foram reavaliados (momento 2 - pós), e os testes aplicados foram os mesmos da avaliação inicial. Os resultados do presente estudo demonstraram que não houve alterações nas variáveis antropométricas e de flexibilidade, com exceção do ângulo de fase. Em relação aos testes neuromusculares, foi encontrado aumento significativo nos saltos counter movement jump, squat jump e drop jump após o treinamento, independente do grupo analisado. A altura do drop jump 50cm foi menor no grupo pliométrico, quando comparado ao grupo de treinamento de longa-distância, independente do momento de avaliação. Quando analisado as variáveis biomecânicas, encontramos aumento do tempo de contato com o solo e da oscilação vertical (apenas 18 km.h-1), além de diminuição da frequência de passada (12, 16 e 18 km.h-1) e da rigidez da perna (10 a 18 km.h-1) após o treinamento, independente do grupo analisado. O grupo pliométrico apresentou aumento do tempo de contato com o solo (14 km.h-1), porém, apresentou reduções significativas na força relativa máxima (16 km.h-1) e na rigidez da perna (14 km.h-1). Nas variáveis fisiológicas, houve aumento da economia de corrida, do ponto de compensação respiratória e do pico de velocidade em esteira, porém, o consumo máximo de oxigênio manteve-se estável, nos dois grupos de treinamento investigados. O desempenho final e a percepção subjetiva de esforço no teste de 10-km também não foram alterados significativamente, porém, a estratégia de prova (trecho inicial e parciais) e pico de velocidade nos 10-km aumentaram após o período experimental. Em resumo, após o protocolo experimental, o grupo de treinamento combinado apresentou alterações semelhantes em variáveis constituintes do desempenho em corredores de 10-km, quando comparado ao grupo de treinamento de longa-distância.
Purpose
The purpose of this study was to investigate the effects of mental fatigue, characterized by a subjective feeling of tiredness, on the development of neuromuscular fatigue during a 4-km cycling time trial (4-km TT).
Methods
Eight recreationally trained male cyclists performed a 4-km TT after either performing a prolonged cognitive task (mental fatigue) or after viewing emotionally neutral documentaries (control). The neuromuscular function of the knee extensors was assessed using electrical nerve stimulation at baseline, before (pre-TT), and after (post-TT) the 4-km TT. Rating of perceived exertion (RPE) and physiological variables were periodically measured during 4-km TT.
Results
Subjective ratings of fatigue increased significantly only after a prolonged cognitive task (P = 0.022). Neuromuscular function at baseline was similar between conditions and remained unchanged at pre-TT. Time to complete the 4-km TT was similar between control (376 ± 27 s) and mental fatigue (376 ± 26 s). There was no significant difference between conditions for RPE, \(~\dot {V}{{\text{O}}_2}\), \(\dot {V}{\text{E}}\), and HR throughout the exercise. The 4-km TT-induced similar decrease (from baseline to post-TT) in maximal voluntary contraction (mental fatigue − 11 ± 10%, control − 16 ± 12%), twitch force (mental fatigue − 26 ± 16%, control − 24 ± 17%), and voluntary activation (mental fatigue − 5 ± 7%, control − 3 ± 2%) for both conditions.
Conclusion
Mental fatigue induced by prolonged cognitive task does not impair performance nor alter the degree of central and peripheral fatigue development during self-paced exercise in recreationally trained cyclists.
The purpose of this study was to investigate the effects of chronic beetroot juice (BRJ) supplementation on 10-km running performance in recreational runners. In a double-blind, placebo-controlled, crossover-designed study, fourteen male recreational runners (age: 27.8 ± 3.4 y) performed three 10-km running tests at baseline, under the conditions of BRJ supplementation and placebo (PLA). Supplementation was administered for three days, and on the day of the assessments, the ingestion occurred two hours before each test and consisted of a dose of 420 mL of BRJ in natura (8.4 mmol NO3-/day) or PLA with depleted NO3- (0.01 mmol NO3-/day). The mean velocity (MV) was calculated and the following variables were determined: maximum heart rate (HRmax), maximal rating of perceived exertion (RPEmax), and determined at pre and post test glucose concentrations (Glycpre, Glycpost), and lactate peak. There was no main effect between conditions regarding to 10-km running time performance (BRJ: 50.1 ± 5.3; PLA: 51.0 ± 5.1 min, p = 0.391) and total MV (BRJ: 12.1 ± 1.3; PLA: 11.9 ± 1.2 km·h-1, p = 0.321), as well as in the other analyzed variables. The time to complete the first half of the test (5 km) was statistically lower in the BRJ compared to that in the PLA (P = 0.027). In conclusion, chronic supplementation with BRJ increasing MV in the first half of the test and improves the final test time of ten of the fourteen runners, although we did not find a statistically significant difference in the performance of 10-km.
Pacing can impact competitive endurance performance. The objective of this study was to determine relationships between pacing parameters and competitive performance of elite female 400-m freestyle swimmers. Publicly available websites provided 50-m split and final times for 381 swims of 20 elite female swimmers in over 150 national and international competitions between 2004 and 2016. Most pacing profiles displayed negative quadratic curvature, with the fifth of the eight laps being the median slowest. The mean times for the first and last laps were faster than predicted by the quadratic by 5.6% and 1.9% respectively, and lap-to-lap variability was 0.65%. Scatter plots of each swimmer's final time often showed no obvious relationships with their pacing parameters, suggesting that swimmers compensated for changes in one parameter with changes in another. However, some plots showed a U shape or linear trend that allowed tentative identification of optimum values of the pacing parameters. In these plots it was apparent that about half the swimmers might make small to moderate improvements (up to ∼1%) by changing the slope or curvature of their pacing profile or by changing time in the first or last laps. This approach for characterizing pacing profiles to identify possible improvements might be appropriate to assess pacing in other sports with multiple laps, frequent competitions and relatively constant environmental conditions.
En situation de compétition l’état psychologique peut changer rapidement la performance. La compréhension et les connexions entre eux conduisent à adapter les entrainements et les suivis faits avec les athlètes. Le but de la présente étude est de déterminer le lien entre les paramètres cardiorespiratoires et les composantes du momentum psychologique lors d'une compétition simulée avec des coureurs de haut niveau. Des coureurs de fond (10H : 23,2 ± 2,4 ans; 10F : 25,9 ± 7,0 ans), en vague de cinq, ont participé à une sélection pour faire partie d’une équipe universitaire. Une course de 3000m constitue la séance 1 qui débute avec les mesures anthropométriques comportant la mesure du poids et de la taille. Il s’en suit la mesure durant la course de la fréquence cardiaque (FC), le cycle respiratoire (CR) et la vitesse de course à l’aide d’une ceinture à la poitrine. À la séance 1, la course fut filmée afin de tenir, à la séance 2, une entrevue individuelle de type semi-structurée avec autoconfrontation. Une 3e séance a permis aux athlètes de compléter en laboratoire un test progressif de vitesse aérobie maximale (VAM) sur tapis roulant. Les résultats indiquent que la durée moyenne de la course de 3000m pour les hommes et les femmes était de 639,8 ± 43,3 et 828,9 ± 79,3 secondes, respectivement. Des indices de rendement exprimés en pourcentage furent créés avec la FC et la vitesse de course ajustée à celle obtenue pour la VAM (191±10 bpm; 17,2±1,1km/h) afin d'identifier les situations de momentum positives et négatives. Une différence significative (p<0,001) est notée entre les éléments positifs (97,04±5,88%) et négatifs (108,46±7,76%). Une variation des capacités physiologiques semble être présente en situation de momentum. En conclusion, il y aurait une différence significative entre les sexes dans la manière de vivre une compétition pour des athlètes de niveau élite.
RESUMO: O objetivo deste estudo foi verificar se a taxa de elevação (slope) da percepção subjetiva de esforço (PSE) poderia ser dissociada da taxa de modificação de variáveis cardiopulmonares e nas concentrações de lactato sanguíneo (Lac) durante exercício aeróbio realizado após a execução de um exercício prévio de força muscular. Onze homens (23,1 ± 0,9 anos, 174,5 ± 7,1 cm, 70,5 ± 8,8 kg, 58,8 ± 8,3 ml.min-1 .kg-1) foram submetidos a duas sessões de testes (controle e experimental), de forma aleatória. Em ambas as condições os sujeitos realizaram uma corrida aeróbia constante, de cinco quilômetros (5-km), com intensidade igual a 50% da diferença entre o primeiro e segundo limiares de lactato (∆50%L1-L2). Na condição experimental os sujeitos realizaram um exercício prévio de resistência muscular (ERM), constituído de duas séries de 15 repetições máximas (15RM). Parâmetros cardiopulmonares, as Lac e a PSE foram medidos em intervalos regulares de distância. Antes do início da corrida de 5-km, as Lac foram 0,5 ± 0,2 e 3,1 ± 0,9 mmol·L-1 , na condição controle e experimental, respectivamente (p = 0,001). Apesar do menor slope das Lac (p = 0,001), e maiores slopes do volume de dióxido de carbono (VCO2) (p = 0,037) e quociente respiratório (QR) (p = 0,001) na condição experimental, não foi observada diferença no slope da PSE entre as duas condições (p = 0,905). Correlações significantes foram observadas entre os slopes da PSE e do QR (r = 0,66, p = 0,026) na condição controle, e entre os slopes da PSE e da frequência respiratória (FR) (r = 0,65; p = 0,028) na condição experimental. Os resultados do presente estudo mostram que um ERM prévio não afeta o slope da PSE durante corrida aeróbia, apesar das alterações nos slopes de variáveis cardiopulmonares e das Lac.
The purpose of this study was to verify the association between ACTN3 polymorphism and physiological parameters related to endurance performance. A total of 150 healthy male volunteers performed a maximal incremental running test to determine the speeds corresponding to ventilatory threshold (VT) and respiratory compensation point (RCP). Participants were genotyped and divided into terciles based on the analysed variables. Genotype frequencies were compared through χ(2) test between lower and higher terciles, with the lowest or highest values of each analysed variable. ACTN3 XX genotype was over-represented in higher tercile for VT and RCP. Odds ratio also showed significantly higher chances of XX individuals to be in higher tercile compared to RR (7.3) and RR + RX (3.5) for VT and compared to RR genotype (8.1) and RR + RX (3.4) for RCP. Thus, XX individuals could attain the VT and RCP at higher speeds, suggesting that they are able to sustain higher running speeds in lower exercise intensity domains. It could result in higher lipid acids oxidation, saving muscle glycogen and delaying the fatigue during prolonged exercises, which could be the advantage mechanism of this genotype to endurance performance.
ABSTRACT: The objective of this study was to verify if rate of increase (slopes) in the ratings of
perceived exertion (RPE) could be dissociated from the rate of change in cardiopulmonary variables and
blood lactate concentrations (Lac) during aerobic exercise performed after a prior strength exercise.
Eleven man (23.1 ± 0.9 years, 174.5 ± 7.1 cm, 70.5 ± 8.8 kg, 58.8 ± 8.3 ml.min-1.kg-1) underwent two
different test sessions, control and experimental. In both the conditions the subjects performed a 5-km
constant running bout set at 50% of the difference between the first and second lactate threshold
(∆50%LT1-LT2). In the experimental condition the subjects performed a strength endurance exercise (ERM)
consisted of two sets of 15 repetitions maximum (15RM) prior to the running bout. Cardiopulmonary
parameters, Lac and RPE were measured at regular intervals of distance. Before the beginning of the 5-
km running the Lac were 0.5 ± 0.2 and 3.1 ± 0.9 mmol • L-1 in the control and experimental condition (p
= 0.001), respectively. Although the lower slope of Lac (p = 0.001) and greater slopes of carbon dioxide
volume (VCO2) (p = 0.037) and respiratory rate (RR) (p = 0.001), there was no difference in slope of RPE
between conditions (p = 0.905). Significant correlations were observed between RPESLOPE and RRSLOPE (r
= 0.66, p = 0.026) in control condition, and between RPE and respiratory frequency (RF) slopes in ERM
condition (r = 0.65, p = 0.028). The results of the present study showed that a prior ERM did not alter the
slope of RPE during aerobic running bout, although the alterations in slopes of cardiopulmonary variables
and Lac.
Key Words: Lactate; Central Nervous System; Training; Aerobic Exercise; Perceived Exertion.
Self-paced time trials have long been used as an indicator of running performance. The purpose of this study was to examine if potential physiological and thermoregulatory differences between treadmill and track running would alter performance in a self-paced 10 km time trial. Ten (n = 10) recreationally-trained male distance runners (32 ± 6 y, 177 ± 6 cm, 76 ± 11 kg, 14.4 ± 4.5% body fat, 62.2 ± 9.5 mL · kg · min VO2 peak) completed two 10 km time trials in a randomized, counter-balanced order on separate days: one on a treadmill at 1% grade (TM), and one on a 200 m indoor track (IT). Core temperature, skin temperature, and heart rate were continuously monitored during the run. 10 km run time was longer during the IT trial (41.66 ± 5.86 min) than the TM trial (40.10 ± 6.06 min; p < 0.001), despite a faster first km in IT (p = 0.029). There were no differences between TM and IT trials in HR (174 ± 13 and 178 ± 13 bpm, respectively; p = 0.846) or body core temperature (38.6 ± 0.5 and 38.9 ± 0.5 °C, respectively, p = 0.218). Skin temperature was higher in TM (35.1 ± 2.5 °C) than IT (32.7 ± 3.0 °C; p = 0.002). These data indicate that performance differences exist between a 10 km time trial performed on a treadmill versus an indoor track, potentially due to differences in pacing strategy or metabolic cost between the two conditions.
A parallel group randomized trial was designed to analyze the impact of 6 weeks of strength training programs performed with or without whole-body vibration on muscular and endurance performance parameters in long-distance runners. 22 endurance runners were allocated into strength with whole-body vibration (n=8), without (n=8), and control (n=6) groups. Before and after the experimental period the subjects performed the following tests: a) maximum dynamic strength test, b) maximal incremental treadmill test, and c) time to exhaustion at velocity corresponding to maximal oxygen uptake. The fractions of the aerobic and anaerobic contribution in time to exhaustion test were also calculated. Both strength trained groups showed a similar increase in maximum dynamic strength (~18%). The aerobic contribution was enhanced for strength training group without whole-body vibration (~25%) after experimental period. No statistical differences were observed in any other variable. These results suggest that 6 weeks of strength training performed with or without whole-body vibration improve similarly the maximum dynamic strength in long-distance runners. In addition, both training modes studied had no deleterious effects on the traditional parameters of endurance performance, traditional strength training program results in increased aerobic contribution during high-intensity aerobic exercise.
The content of this manuscript is intended to assist the reader in collecting valid and reliable data for quantifying muscular strength and power. Various drawbacks and pitfalls of specific tests, as well as recommendations for the practitioner are also provided. The content is divided into sections covering isometric, isotonic, field tests, and isokinetic modes of exercise. Inherent in these modes are both concentric and eccentric muscle actions as well as both open and closed kinetic chain activities. For Isometric testing, contractions should occur over a four to five seconds duration with a one second transition period at the start of the contraction. At least one minute of rest should be provided between contractions. For each muscle tested at each position, at least three contractions should be performed although more may be performed if deemed necessary by the tester. For isotonic testing, the 1-RM test should be performed. After the general warm-up, the subject should perform a specific warm-up set of 8 repetitions at approximately 50% of the estimated 1-RM followed by another set of 3 repetitions at 70% of the estimated 1-RM. Subsequent lifts are single repetitions of progressively heavier weights until failure. Repeat until the 1-RM is determined to the desired level of precision. The rest interval between sets should be not less than one and not more than five minutes. The optimal number of single repetitions ranges from three to five. Data and guidelines of the following field tests are also provided; vertical jump, bench press, Wingate anaerobic cycle test (WAT), and the Margaria stair-run test. For isokinetic testing, details are provided for testing peak torque, work, power, endurance, and estimation of fiber type percentages.
This article examines how pacing strategies during exercise are controlled by information processing between the brain and peripheral physiological systems. It is suggested that, although several different pacing strategies can be used by athletes for events of different distance or duration, the underlying principle of how these different overall pacing strategies are controlled is similar. Perhaps the most important factor allowing the establishment of a pacing strategy is knowledge of the endpoint of a particular event. The brain centre controlling pace incorporates knowledge of the endpoint into an algorithm, together with memory of prior events of similar distance or duration, and knowledge of external (environmental) and internal (metabolic) conditions to set a particular optimal pacing strategy for a particular exercise bout. It is proposed that an internal clock, which appears to use scalar rather than absolute time scales, is used by the brain to generate knowledge of the duration or distance still to be covered, so that power output and metabolic rate can be altered appropriately throughout an event of a particular duration or distance. Although the initial pace is set at the beginning of an event in a feedforward manner, no event or internal physiological state will be identical to what has occurred previously. Therefore, continuous adjustments to the power output in the context of the overall pacing strategy occur throughout the exercise bout using feedback information from internal and external receptors. These continuous adjustments in power output require a specific length of time for afferent information to be assessed by the brain's pace control algorithm, and for efferent neural commands to be generated, and we suggest that it is this time lag that crates the fluctuations in power output that occur during an exercise bout. These non-monotonic changes in power output during exercise, associated with information processing between the brain and peripheral physiological systems, are crucial to maintain the overall pacing strategy chosen by the brain algorithm of each athlete at the start of the exercise bout.
The purpose of this study was to assess the effects of heavy resistance, explosive resistance, and muscle endurance training on neuromuscular, endurance, and high-intensity running performance in recreational endurance runners. Twenty-seven male runners were divided into one of three groups: heavy resistance, explosive resistance or muscle endurance training. After 6 weeks of preparatory training, the groups underwent an 8-week resistance training programme as a supplement to endurance training. Before and after the 8-week training period, maximal strength (one-repetition maximum), electromyographic activity of the leg extensors, countermovement jump height, maximal speed in the maximal anaerobic running test, maximal endurance performance, maximal oxygen uptake ([V·]O(₂max)), and running economy were assessed. Maximal strength improved in the heavy (P = 0.034, effect size ES = 0.38) and explosive resistance training groups (P = 0.003, ES = 0.67) with increases in leg muscle activation (heavy: P = 0.032, ES = 0.38; explosive: P = 0.002, ES = 0.77). Only the heavy resistance training group improved maximal running speed in the maximal anaerobic running test (P = 0.012, ES = 0.52) and jump height (P = 0.006, ES = 0.59). Maximal endurance running performance was improved in all groups (heavy: P = 0.005, ES = 0.56; explosive: P = 0.034, ES = 0.39; muscle endurance: P = 0.001, ES = 0.94), with small though not statistically significant improvements in [V·]O(₂max) (heavy: ES = 0.08; explosive: ES = 0.29; muscle endurance: ES = 0.65) and running economy (ES in all groups < 0.08). All three modes of strength training used concurrently with endurance training were effective in improving treadmill running endurance performance. However, both heavy and explosive strength training were beneficial in improving neuromuscular characteristics, and heavy resistance training in particular contributed to improvements in high-intensity running characteristics. Thus, endurance runners should include heavy resistance training in their training programmes to enhance endurance performance, such as improving sprinting ability at the end of a race.
The aim of this study was to determine which physiological variables predict excellence in middle- and long-distance runners. Forty middle-distance runners (age 23 ± 4 years, body mass 67.2 ± 5.9 kg, stature 1.80 ± 0.05 m, VO(2max) 65.9 ± 4.5 ml · kg(-1) · min(-1)) and 32 long-distance runners (age 25 ± 4 years, body mass 59.8 ± 5.1 kg, stature 1.73 ± 0.06 m, VO(2max) 71.6 ± 5.0 ml · kg(-1) · min(-1)) competing at international standard performed an incremental running test to exhaustion. Expired gas analysis was performed breath-by-breath and maximum oxygen uptake (VO(2max)) and two ventilatory thresholds (VT(1) and VT(2)) were calculated. Long-distance runners presented a higher VO(2max) than middle-distance runners when expressed relative to body mass (P < 0.001, d = 1.18, 95% CI [0.68, 1.68]). At the intensities corresponding to VT(1) and VT(2), long-distance runners showed higher values for VO(2) expressed relative to body mass or %VO(2max), speed and oxygen cost of running (P < 0.05). When oxygen uptake was adjusted for body mass, differences between groups were consistent. Logistic binary regression analysis showed that VO(2max) (expressed as l · min(-1) and ml · kg(-1) · min(-1)), VO(2VT2) (expressed as ml · kg(-0.94) · min(-1)), and speed at VT(2) (v(VT2)) categorized long-distance runners. In addition, the multivariate model correctly classified 84.7% of the athletes. Thus, VO(2max), VO(2VT2), and v(VT2) discriminate between elite middle-distance and long-distance runners.
This study examined effects of periodized maximal versus explosive strength training and reduced strength training, combined with endurance training, on neuromuscular and endurance performance in recreational endurance runners. Subjects first completed 6 weeks of preparatory strength training. Then, groups of maximal strength (MAX, n=11), explosive strength (EXP, n=10) and circuit training (C, n=7) completed an 8-week strength training intervention, followed by 14 weeks of reduced strength training. Maximal strength (1RM) and muscle activation (EMG) of leg extensors, countermovement jump (CMJ), maximal oxygen uptake (VO(2MAX)), velocity at VO(2MAX) (vVO(2MAX)) running economy (RE) and basal serum hormones were measured. 1RM and CMJ improved (p<0.05) in all groups accompanied by increased EMG in MAX and EXP (p<0.05) during strength training. Minor changes occurred in VO(2MAX), but vVO(2MAX) improved in all groups (p<0.05) and RE in EXP (p<0.05). During reduced strength training 1RM and EMG decreased in MAX (p<0.05) while vVO(2MAX) in MAX and EXP (p<0.05) and RE in MAX (p<0.01) improved. Serum testosterone and cortisol remained unaltered. Maximal or explosive strength training performed concurrently with endurance training was more effective in improving strength and neuromuscular performance and in enhancing vVO (2MAX) and RE in recreational endurance runners than concurrent circuit and endurance training.
The aim of this study was to examine the influence of the performance level of athletes on pacing strategy during a simulated 10-km running race, and the relationship between physiological variables and pacing strategy. Twenty-four male runners performed an incremental exercise test on a treadmill, three 6-min bouts of running at 9, 12 and 15 km h(-1), and a self-paced, 10-km running performance trial; at least 48 h separated each test. Based on 10-km running performance, subjects were divided into terziles, with the lower terzile designated the low-performing (LP) and the upper terzile designated the high-performing (HP) group. For the HP group, the velocity peaked at 18.8 +/- 1.4 km h(-1) in the first 400 m and was higher than the average race velocity (P < 0.05). The velocity then decreased gradually until 2,000 m (P < 0.05), remaining constant until 9,600 m, when it increased again (P < 0.05). The LP group ran the first 400 m at a significantly lower velocity than the HP group (15.6 +/- 1.6 km h(-1); P > 0.05) and this initial velocity was not different from LP average racing velocity (14.5 +/- 0.7 km h(-1)). The velocity then decreased non-significantly until 9,600 m (P > 0.05), followed by an increase at the end (P < 0.05). The peak treadmill running velocity (PV), running economy (RE), lactate threshold (LT) and net blood lactate accumulation at 15 km h(-1) were significantly correlated with the start, middle, last and average velocities during the 10-km race. These results demonstrate that high and low performance runners adopt different pacing strategies during a 10-km race. Furthermore, it appears that important determinants of the chosen pacing strategy include PV, LT and RE.
Mental fatigue is a psychobiological state caused by prolonged periods of demanding cognitive activity. Although the impact of mental fatigue on cognitive and skilled performance is well known, its effect on physical performance has not been thoroughly investigated. In this randomized crossover study, 16 subjects cycled to exhaustion at 80% of their peak power output after 90 min of a demanding cognitive task (mental fatigue) or 90 min of watching emotionally neutral documentaries (control). After experimental treatment, a mood questionnaire revealed a state of mental fatigue (P = 0.005) that significantly reduced time to exhaustion (640 +/- 316 s) compared with the control condition (754 +/- 339 s) (P = 0.003). This negative effect was not mediated by cardiorespiratory and musculoenergetic factors as physiological responses to intense exercise remained largely unaffected. Self-reported success and intrinsic motivation related to the physical task were also unaffected by prior cognitive activity. However, mentally fatigued subjects rated perception of effort during exercise to be significantly higher compared with the control condition (P = 0.007). As ratings of perceived exertion increased similarly over time in both conditions (P < 0.001), mentally fatigued subjects reached their maximal level of perceived exertion and disengaged from the physical task earlier than in the control condition. In conclusion, our study provides experimental evidence that mental fatigue limits exercise tolerance in humans through higher perception of effort rather than cardiorespiratory and musculoenergetic mechanisms. Future research in this area should investigate the common neurocognitive resources shared by physical and mental activity.
This study assessed the relationship of the rating of perceived exertion (RPE) with heart rate and pacing strategy during competitive running races of differing distance and course elevation. Nine men and women competed in a 7-mile road race (7-MR) and the Great West Run half marathon (GWR; 13.1 miles). Heart rate, split mile time, and RPE were recorded throughout the races. The RPE was regressed against time and %time to complete the 7-MR and GWR. Although the rate of increase in RPE was greater in the 7-MR, there were no differences when expressed against %time (inferring that the brain uses a scalar timing mechanism). As the course elevation, distance, pacing strategy, and heart rate response varied between conditions, this study has provided evidence that the perceptual response may have distinct temporal characteristics during distance running. The results provide further evidence that RPE scales with the proportion of exercise time that remains.
The first part of this article intends to give an applicable framework for the evaluation of endurance capacity as well as for the derivation of exercise prescription by the use of two gas exchange thresholds: aerobic (AerTGE) and anaerobic (AnTGE). AerT GE corresponds to the first increase in blood lactate during incremental exercise whereas AnTGE approximates the maximal lactate steady state. With very few constraints, they are valid in competitive athletes, sedentary subjects, and patients. In the second part of the paper, the practical application of gas exchange thresholds in cross-sectional and longitudinal studies is described, thereby further validating the 2-threshold model. It is shown that AerTGE and AnTGE can reliably distinguish between different states of endurance capacity and that they can well detect training-induced changes. Factors influencing their relationship to the maximal oxygen uptake are discussed. Finally, some approaches of using gas exchange thresholds for exercise prescription in athletes, healthy subjects, and chronically diseased patients are addressed.
We hypothesized that a freely paced 10,000 m running race would induce a smaller physiological strain (heart rate and oxygen uptake) compared with one performed at the same average speed but with an imposed constant pace. Furthermore, we analyzed the scaling properties with a wavelet transform algorithm computed log2 (wavelet transform energy) vs. log2 (scale) to get slope alpha, which is the scaling exponent, a measure of the irregularity of a time series. HR was sampled beat by beat and V2O, breath by breath. The enforced constant pace run elicited a significantly higher mean VO2 value (53 +/- 4 vs. 48 +/- 5 ml kg(-1) min(-1), P < 0.001), HR (169 +/- 13 vs. 165 +/- 14 bpm, P < 0.01), and blood lactate concentration (6.6 +/- 0.9 vs. 7.5 +/- 1 mM, P < 0.001) than the freely paced run. HR and VO2 signals showed a scaling behavior, which means that the signals have a similar irregularity (a self-similarity) whatever the scale of analysis may be, in both constant and free-paced 10,000 m runs. The scaling exponent was not significantly different according to the type of run (free vs. constant, P > 0.05) and the signal (HR vs. VO2, P > 0.05). The higher metabolic cost of constant vs. free paced run did not affect the self-similarity of HR and VO2, in either run. The HR signal only kept its scaling behavior only with a distance run, no matter the type of run (free or constant). The results suggest that the larger degree of pace variation in freely paced races may be an intentionally chosen strategy designed to minimize the physiological strain during severe exercise and to prevent a premature termination of effort, even if the variability of the heart rate and VO2, are comparable in an enforced constant vs. a freely paced run and if HR keeps the same variability until the arrival.
It is widely recognized that an athlete's 'pacing strategy', or how an athlete distributes work and energy throughout an exercise task, can have a significant impact on performance. By applying mathematical modelling (i.e. power/velocity and force/time relationships) to athletic performances, coaches and researchers have observed a variety of pacing strategies. These include the negative, all-out, positive, even, parabolic-shaped and variable pacing strategies. Research suggests that extremely short-duration events (< or =30 seconds) may benefit from an explosive 'all-out' strategy, whereas during prolonged events (>2 minutes), performance times may be improved if athletes distribute their pace more evenly. Knowledge pertaining to optimal pacing strategies during middle-distance (1.5-2 minutes) and ultra-endurance (>4 hours) events is currently lacking. However, evidence suggests that during these events well trained athletes tend to adopt a positive pacing strategy, whereby after peak speed is reached, the athlete progressively slows. The underlying mechanisms influencing the regulation of pace during exercise are currently unclear. It has been suggested, however, that self-selected exercise intensity is regulated within the brain based on a complex algorithm involving peripheral sensory feedback and the anticipated workload remaining. Furthermore, it seems that the rate and capacity limitations of anaerobic and aerobic energy supply/utilization are particularly influential in dictating the optimal pacing strategy during exercise. This article outlines the various pacing profiles that have previously been observed and discusses possible factors influencing the self-selection of such strategies.
It is thought that perception of effort during physical tasks is the conscious awareness of the central motor command sent to the active muscles. The aim of this study was to directly test this hypothesis by experimentally varying perception of effort and measuring movement-related cortical potential (MRCP). Sixteen healthy, recreationally active men made unilateral dynamic elbow flexions to lift a light (20% one repetition maximum, 1RM) and a heavier (35% 1RM) weight with a fatigued arm and a nonfatigued arm while rating of perceived effort (RPE), biceps brachii electromyogram (EMG), and MRCP were recorded. RPE, EMG amplitude, and MRCP amplitude at Cz during weight raising increased with weight and with muscle fatigue. There was a significant correlation between RPE and MRCP amplitude at the vertex during the weight raising epoch. This study provides direct neurophysiological evidence that perception of effort correlates with central motor command during movement execution.
The purpose of this study was to investigate the main bioenergetics and neuromuscular determinants of the time to exhaustion (T(lim)) at the velocity corresponding to maximal oxygen uptake in recreational long-distance runners. Twenty runners performed the following tests on 5 different days: (a) maximal incremental treadmill test, (b) 2 submaximal tests to determine running economy and vertical stiffness, (c) exhaustive test to measured the T(lim), (d) maximum dynamic strength test, and (e) muscle power production test. Aerobic and anaerobic energy contributions during the T(lim) test were also estimated. The stepwise multiple regression method selected 3 independent variables to explain T(lim) variance. Total energy production explained 84.1% of the shared variance (p = 0.001), whereas peak oxygen uptake (V(O2)peak) measured during T(lim)and lower limb muscle power ability accounted for the additional 10% of the shared variance (p = 0.014). These data suggest that the total energy production, V(O2)peak, and lower limb muscle power ability are the main physiological and neuromuscular determinants of T(lim)in recreational long-distance runners.
To compare the classic physiological variables linked to endurance performance (VO2max, %VO2max at lactate threshold (LT), and running economy (RE)) with peak treadmill velocity (PTV) as predictors of performance in a 16-km time trial.
Seventeen healthy, well-trained distance runners (10 males and 7 females) underwent laboratory testing to determine maximal oxygen uptake (VO2max), RE, percentage of maximal oxygen uptake at the LT (%VO2max at LT), running velocity at LT, and PTV. Velocity at VO2max (vVO2max) was calculated from RE and VO2max. Three stepwise regression models were used to determine the best predictors (classic vs treadmill performance protocols) for the 16-km running time trial.
Simple Pearson correlations of the variables with 16-km performance showed vVO2max to have the highest correlation (r = -0.972) and %VO2max at the LT the lowest (r = 0.136). The correlation coefficients for LT, VO2max, and PTV were very similar in magnitude (r = -0.903 to r = -0.892). When VO2max, %VO2max at LT, RE, and PTV were entered into SPSS stepwise analysis, VO2max explained 81.3% of the total variance, and RE accounted for an additional 10.7%. vVO2max was shown to be the best predictor of the 16-km performance, accounting for 94.4% of the total variance. The measured velocity at VO2max (PTV) was highly correlated with the estimated velocity at vVO2max (r = 0.8867).
Among well-trained subjects heterogeneous in VO2max and running performance, vVO2max is the best predictor of running performance because it integrates both maximal aerobic power and the economy of running. The PTV is linked to the same physiological variables that determine vVO2max.
To investigate pacing strategy during the 1-km time trial (TT) and 3- and 4-km individual pursuit (IP), in elite cyclists.
Total times and intermediate times were obtained from the 2007 and 2008 cycling World Championships in the 1-km TT and 2006, 2007, and 2008 World Championships in the 3- and 4-km IP. Data were analyzed to examine the pacing-profiles employed and pacing strategies of "slow" and "fast" performances.
Similar pacing-profiles were evident in each event, which were characterized by an initial acceleration followed by a progressive decay in split times. In the 1-km TT, the first 250-m split time was a primary determinant of total time, whereas the rate of fatigue over the remainder of the race did not discriminate between performances. The first 250-m split time was also related to total time in the 3- and 4-km IP, although to a lesser extent than in the 1-km TT, whereas the ability to maintain a consistent pacing-profile was of increased importance. There were differences in the pacing strategies of slow and fast performances in the 3- and 4-km IP, with slow performances characterized by an overly quick start with a concomitant slowing at the finish.
The pacing profiles adopted were similar to the optimal pacing strategies proposed in simulation models of cycling performance. However, in the 3-km and 4-km IP small alterations in pacing strategy appear to be important, at the elite level.
To analyze pacing strategies employed during men's world-record performances for 800-m, 5000-m, and 10,000-m races.
In the 800-m event, lap times were analyzed for 26 world-record performances from 1912 to 1997. In the 5000-m and 10,000-m events, times for each kilometer were analyzed for 32 (1922 to 2004) and 34 (1921 to 2004) world records.
The second lap in the 800-m event was significantly slower than the first lap (52.0 + or - 1.7 vs 54.4 + or - 4.9 seconds, P < .00005). In only 2 world records was the second lap faster than the first lap. In the 5000-m and 10,000-m events, the first and final kilometers were significantly faster than the middle kilometer intervals, resulting in an overall even pace with an end spurt at the end.
The optimal pacing strategy during world-record performances differs for the 800-m event compared with the 5000-m and 10,000-m events. In the 800-m event, greater running speeds are achieved in the first lap, and the ability to increase running speed on the second lap is limited. In the 5000-m and 10,000-m events, an end spurt occurs because of the maintenance of a reserve during the middle part of the race. In all events, pacing strategy is regulated in a complex system that balances the demand for optimal performance with the requirement to defend homeostasis during exercise.
Twenty specialist marathon runners and 23 specialist ultra-marathon runners underwent maximal exercise testing to determine the relative value of maximum oxygen consumption (VO2max), peak treadmill running velocity, running velocity at the lactate turnpoint, VO2 at 16 km h-1, % VO2max at 16 km h-1, and running time in other races, for predicting performance in races of 10-90 km. Race time at 10 or 21.1 km was the best predictor of performance at 42.2 km in specialist marathon runners and at 42.2 and 90 km in specialist ultra-marathon runners (r = 0.91-0.97). Peak treadmill running velocity was the best laboratory-measured predictor of performance (r = -0.88(-)-0.94) at all distances in ultra-marathon specialists and at all distances except 42.2 km in marathon specialists. Other predictive variables were running velocity at the lactate turnpoint (r = -0.80(-)-0.92); % VO2max at 16 km h-1 (r = 0.76-0.90) and VO2max (r = 0.55(-)-0.86). Peak blood lactate concentrations (r = 0.68-0.71) and VO2 at 16 km h-1 (r = 0.10-0.61) were less good predictors. These data indicate: (i) that in groups of trained long distance runners, the physiological factors that determine success in races of 10-90 km are the same; thus there may not be variables that predict success uniquely in either 10 km, marathon or ultra-marathon runners, and (ii) that peak treadmill running velocity is at least as good a predictor of running performance as is the lactate turnpoint. Factors that determine the peak treadmill running velocity are not known but are not likely to be related to maximum rates of muscle oxygen utilization.
There is a great demand for perceptual effort ratings in order to better understand man at work. Such ratings are important complements to behavioral and physiological measurements of physical performance and work capacity. This is true for both theoretical analysis and application in medicine, human factors, and sports. Perceptual estimates, obtained by psychophysical ratio-scaling methods, are valid when describing general perceptual variation, but category methods are more useful in several applied situations when differences between individuals are described. A presentation is made of ratio-scaling methods, category methods, especially the Borg Scale for ratings of perceived exertion, and a new method that combines the category method with ratio properties. Some of the advantages and disadvantages of the different methods are discussed in both theoretical-psychophysical and psychophysiological frames of reference.
Historically, the achievement of maximal oxygen uptake (VO2max) has been based on objective criteria such as a leveling off of oxygen uptake with an increase in work rate, high levels of lactic acid in the blood in the minutes following the exercise test, elevated respiratory exchange ratio, and achievement of some percentage of an age-adjusted estimate of maximal heart rate. These criteria are reviewed relative to their history, the degree to which they have been achieved in published research, and how investigators and reviewers follow them in current practice. The majority of the criteria were based on discontinuous protocols, often carried out over several days. Questions are raised about the applicability of these criteria to modern continuous graded exercise test protocols, and our lack of consistency in the terminology we use relative to the measurement of maximal oxygen uptake.
Efferent motor signals to skeletal muscles concern not only the space/ time pattern of motion, but also the setting of muscular performance and through this the control of the current metabolic rate. For an optimal adjustment of metabolic rate during heavy exercise-e.g. in athletic competitions-a feedback control system must exist, including a programmer that takes into consideration a finishing point (teleoanticipation). The presented experiments, using Borg's scale, indicate the existence and functioning of a system for optimal adjustment of performance during heavy exercise and the relevance of teleoanticipatory effects. Thus motor learning includes not only somatosensory control, but also metabolic control. With regard to migratory birds, such metabolic control would have to operate in the individual as well as in the migrating flock as a whole.
The characteristics of oxygen uptake (V̇O2) kinetics differ with exercise intensity. When exercise is performed at a given work rate which is below lactate threshold (LT), V̇O2 increases exponentially to a steady-state level. Neither the slope of the increase in V̇O2 with respect to work rate nor the time constant of V̇O2 responses has been found to be a function of work rate within this domain, indicating a linear dynamic relationship between the V̇O2 and the work rate. However, some factors, such as physical training, age and pathological conditions can alter the V̇O2 kinetic responses at the onset of exercise. Regarding the control mechanism for exercise V̇O2 kinetics, 2 opposing hypotheses have been proposed. One of them suggests that the rate of the increase in V̇O2 at the onset of exercise is limited by the capacity of oxygen delivery to active muscle. The other suggests that the ability of the oxygen utilisation in exercising muscle acts as the rate-limiting step. This issue is still being debated.
When exercise is performed at a work rate above LT, the V̇O2 kinetics become more complex. An additional component is developed after a few minutes of exercise. The slow component either delays the attainment of the steady-state V̇O2 or drives the V̇O2 to the maximum level, depending on exercise intensity. The magnitude of this slow component also depends on the duration of the exercise. The possible causes for the slow component of V̇O2 during heavy exercise include: (i) increases in blood lactate levels; (ii) increases in plasma epinephrine (adrenaline) levels; (iii) increased ventilatory work; (iv) elevation of body temperature; and (v) recruitment of type IIb fibres. Since 86% of the V̇O2 slow component is attributed to the exercising limbs, the major contributor is likely within the exercising muscle itself. During high intensity exercise an increase in the recruitment of low-efficiency type IIb fibres (the fibres involved in the slow component) can cause an increase in the oxygen cost of exercise. A change in the pattern of motor unit recruitment, and thus less activation of type IIb fibres, may also account for a large part of the reduction in the slow component of V̇O2 observed after physical training.
This study was carried out to investigate the importance of maximal oxygen uptake (VO2max) and so-called muscle power factors relating to neuromuscular and anaerobic characteristics as determinants of peak horizontal and uphill treadmill running velocity (Vmax). Muscle power factors were measured as peak velocity (VMART) and blood lactate concentration (BlaMART) in a maximal anaerobic running test and as maximal 30-m run velocity (V30m). Seven middle-distance runners, eight triathletes and eight cross-country skiers performed an incremental VO2max-test at horizontal (subscript max0) and 7 degrees uphill (subscript max7) and the MART at 3 degrees uphill on a treadmill and V30m-test on a track. The MART consisted of n x 20-s runs with a 100-s recovery between the runs and the velocity was increased by 0.41 m x s(-1) for each consecutive run until exhaustion. At 0 degrees Vmax was significantly higher but VO2max, ventilation and Bla were significantly lower than at 7 degrees inclination. Vmax0 correlated with VMART (r=0.85, P<0.001), Blamax0 (r=0.49, P<0.05) and V30m (r=0.78, P<0.001) but not with VO2max0. Vmax7 correlated with VO2max7 (r=0.78, P<0.001), VMART (r=0.61, P<0.01) and V30m (r=0.53, P<0.05). VMART correlated with BlaMART (r=0.71, P<0.01) and V30m (r=0.96, P<0.001) but not with VO2max0 or VO2max7. Middle-distance runners had a significantly (P<0.001) higher Vmax0, VMART BlaMART and V30m than triathletes and cross-country skiers, but no significant differences were found between the three groups in VO2max0, VO2max7 or Vmax7. We conclude that so-called muscle power factors, e.g. VMART, V30m and BlaMART, contribute to peak treadmill running performance and especially to horizontal running performance and that VO2max contributes more to uphill than horizontal running performance.
To analyze the limits of agreement between exercise ventilatory threshold values (VT1 and VT2) estimated from a combination of pulmonary gas exchange and ventilatory variables (cardiopulmonary exercise testing) and those derived from an alternative approach based on the ventilatory response only (V(E), ventilometry).
Forty-two nontrained subjects (24 males, aged 18-48, peak VO(2) = 33.1 +/- 8.6 mL.min(-1).kg(-1)) performed a maximum incremental cardiopulmonary exercise testing on an electromagnetically braked cycle ergometer. The participants breathed through a Pitot tube (Cardio2 System, MGC) and a fixed-resistance ventilometer (Micromed, Brazil), which were connected in series. HR values at the estimated VT (VTHR1 and VTHR2) were obtained by the conventional method (ventilatory equivalents, end-expiratory pressures for O(2) and CO(2), and the V-slope procedure) and an experimental approach (V(E) vs time, V(E)/time vs time, and breathing frequency vs time).
There were no significant between-method differences on VT(HR1), VT(HR2), VT(VE1), VT(VE2), and peak V(E) (P > 0.05). After certification of data normality, a Bland-Altman analysis revealed that the mean bias +/- 95% confidence interval of the between-method differences were lower for VT(HR2) than VT(HR1) (2 +/- 9 and 0 +/- 17 bpm, respectively). VT(HR2) according to ventilometry differed more than 10 bpm from the standard procedure in 3 out of 42 subjects (9%). Between-method differences were independent of the level of fitness, as estimated from peak VO(2) (P > 0.05).
: A simplified approach, based on the ventilatory response as a function of time, can provide acceptable estimates of the exercise ventilatory thresholds--especially VT2--during ramp-incremental cycle ergometry. This new strategy might prove to be useful for exercise training prescription in nontrained adults.
The present study was designed to examine the role of central and peripheral fatigue on 4000-m cycling time trial performance by comparing changes in power output and integrated electromyography (iEMG) in differently paced maximal efforts.
Eight well-trained men performed three randomly ordered time trials with different pacing strategies, in which the first 2000 m were manipulated to evoke an increasing, even, and decreasing power output profile (SUB, EVEN, and SUPRA, respectively). Subjects were instructed to finish the last 2000 m of all trials in the shortest time possible. iEMG of the rectus femoris (RF), vastus lateralis (VL), and biceps femoris (BF) muscle, mechanical power output, and gas exchange variables were measured. Anaerobic and aerobic contributions to mechanical power output were calculated from gas exchange data.
The increase in mechanical power output during the SUB time trials was always associated with an increase in iEMG in all muscles. A decrease in mechanical power output near the end of the time trials was also marked by an increase in iEMG for all muscles, except for the RF. Comparing the last 2000-m interval with the first, aerobic power output increased for all strategies. Anaerobic power output increased in SUB and decreased in EVEN and SUPRA.
The relationship between iEMG and mechanical power output pattern was consistent with peripheral fatigue rather than central downregulation of mechanical power output. Specifically, anaerobic energy resources seem to be important in regulating pacing strategy.
Seven male subjects completed cycle exercise bouts to the limit of tolerance on three occasions: (1) at a constant work rate (340+/-57 W; even-pace strategy; ES); (2) at a work rate that was initially 10% lower than that in the ES trial but which then increased with time such that it was 10% above that in the ES trial after 120 s of exercise (slow-start strategy; SS); and, (3) at a work rate that was initially 10% higher than that in the ES trial but which then decreased with time such that it was 10% below that in the ES trial after 120 s of exercise (fast-start strategy; FS). The expected time to exhaustion predicted from the pre-established power-time relationship was 120 s in all three conditions. However, the time to exhaustion was significantly greater (P<0.05) for the FS (174+/-56 s) compared with the ES (128+/-21 s) and SS (128+/-30 s) conditions. In the FS condition, (.)VO2 increased more rapidly toward its peak such that the total O2 consumed in the first 120 s of exercise was greater (ES: 5.15+/-0.78; SS: 5.07+/-0.83; FS: 5.36+/-0.84 L; P<0.05 for FS vs ES and SS). These results suggest that a fast-start pacing strategy might enhance exercise tolerance by increasing the oxidative contribution to energy turnover and hence "sparing" some of the finite anaerobic capacity across the transition to high-intensity exercise.
This study investigated fatigue-induced changes in neuromuscular and stride characteristics during and immediately after the 5-km running time trial. Eighteen well-trained male distance runners performed a maximal 20-m sprint test and maximal voluntary contraction (MVC) in a leg press machine before and immediately after the 5-km running time trial. In all the tests the EMG of five lower limb muscles was measured. The results of the present study showed that muscle fatigue measured in maximal exercises like 20-m sprint and MVC are not related to the fatigue induced changes during the 5-km time trial. The fatigue in the 20-m sprint test was related to the maximal 20-m pretest velocity (r=0.58, p<0.05), but the velocity loss during the 5-km time trial was inversely related to 5-km performance (r= - 0.60, p<0.05) and training volume (r= - 0.58, p<0.05). It was concluded that the fatigue in 5-km running measured pre- and postexercise at maximal effort is more related to sprint performance rather than endurance performance, but the fatigue measured during the 5-km running is related to endurance performance and factors affecting pacing strategy.
The present study investigated the effect of maximal strength training on running economy (RE) at 70% of maximal oxygen consumption (V[spacing dot above]O2max) and time to exhaustion at maximal aerobic speed (MAS). Responses in one repetition maximum (1RM) and rate of force development (RFD) in half-squats, maximal oxygen consumption, RE, and time to exhaustion at MAS were examined.
Seventeen well-trained (nine male and eight female) runners were randomly assigned into either an intervention or a control group. The intervention group (four males and four females) performed half-squats, four sets of four repetitions maximum, three times per week for 8 wk, as a supplement to their normal endurance training. The control group continued their normal endurance training during the same period.
The intervention manifested significant improvements in 1RM (33.2%), RFD (26.0%), RE (5.0%), and time to exhaustion at MAS (21.3%). No changes were found in V[spacing dot above]O2max or body weight. The control group exhibited no changes from pre to post values in any of the parameters.
Maximal strength training for 8 wk improved RE and increased time to exhaustion at MAS among well-trained, long-distance runners, without change in maximal oxygen uptake or body weight.
Physiological determinants of speciality of elite middle-and long-distance runners
- M Rabadá N
- V Díaz
- Calderó N Fj
- Benito
- Pj
- A B Peinado
- N Maffulli
Rabadá n, M, Díaz, V, Calderó n, FJ, Benito, PJ, Peinado, AB, and
Maffulli, N. Physiological determinants of speciality of elite
middle-and long-distance runners. J Sports Sci 29: 975-982,
2011.
Determinants of the Pacing Strategy During a 10-km Running Race 22 Fatigue during a 5-km running time trial
- At Nummela
- Ka Heath
- Paavolainen
- Lm
- Mi Lambert
- Clair St
- A Gibson
- Hk Rusko
- Td Noakes
Determinants of the Pacing Strategy During a 10-km Running Race
22. Nummela, AT, Heath, KA, Paavolainen, LM, Lambert, MI, St Clair
Gibson, A, Rusko, HK, and Noakes, TD. Fatigue during a 5-km
running time trial. Int J Sports Med 29: 738-745, 2008.