Sprint cycling: physiological and motivational considerations for performance and recovery

The Match Sprint is a highly tactical track cycling discipline that requires athletes to race on multiple occasions each day and over consecutive days. The time between races varies depending on the competition schedule, but when the recovery period is brief (10 – 30 minutes) the current practice undertaken by elite riders consists of a mixture of light cycling and passive rest, although this is not evidence based. The aim of this PhD thesis was, therefore, to investigate motivational and physiological factors that could affect sprint cycling performance over repeated efforts. Performance was primarily evaluated as mean power output (MPO) during each sprint, with peak power output (PPO) being assessed as a secondary variable. In the first study (Chapter 4), fifteen strength-trained men (age: 24 ± 6 years; height: 1.81 ± 0.08 m; body mass: 83.4 ± 8.4 kg) visited the laboratory on eight occasions. During the first trial, the participants were familiarised with the performance measure, an 18 s cycling sprint, before a ramp test was performed to exhaustion for the determination of maximal oxygen uptake. The second trial was the baseline trial. In addition to performing an 18 s sprint, blood lactate concentration, tissue saturation index, and oxygen uptake were monitored during 12 minutes of passive recovery after the sprint. In the remaining trials, the recovery duration was varied (45, 90, 135, 180, 360, and 720 s) between two 18 s sprints, facilitating the mathematical modelling of performance recovery. One- and two-phase exponential functions were used to model the recovery time-course of MPO, as well as the recovery of the physiological variables. Correlation analyses were then conducted to assess the relationships between the recovery time constant for MPO and the physiological variables. The strength of these relationships ranged from trivial (r = -0.026) to moderate (ρ = -0.342), but was on all occasions not significant. Effects of sprint number (MPO: F(1,14) = 66.901, p < 0.001, ƞ_p^2 =0.827; PPO: F(1,14) = 73.177, p < 0.001, ƞ_p^2 = 0.839), recovery time (MPO: F(5,70) = 36.294, p < 0.001, ƞ_p^2 = 0.722; PPO: F(5,70) = 4.975, p = 0.001, ƞ_p^2 = 0.262), and a sprint number × recovery time interaction were found on both MPO and PPO (MPO: F(2.160,30.242) = 52.095, p < 0.001, ƞ_p^2 = 0.788; PPO: F(2.617,36.639) = 10.553, p < 0.001, ƞ_p^2 = 0.430), with post hoc tests revealing significant differences between sprints at all time-points for both variables. The main finding from the study was, therefore, that performance recovery was not complete over a recovery duration that may occur during a competition. One limitation with the methodological design in Chapter 4 was the requirement for the participants to remain stationary on the ergometer between sprints. A strict passive recovery was used to limit the movements of the participants and to facilitate the controlled measurement of the physiological variables in recovery. A strict passive recovery would not, however, reflect a real-world scenario. Therefore, in Study 2 (Chapter 5), the performance effects of a mixture of active and passive recovery, a protocol that is currently used by elite track cyclists, was contrasted with passive recovery. In addition, to explore the consideration that the reduction in second sprint performance that was found in Chapter 4 was as a result of a change in motivation, an alteration in second sprint duration was also included in the investigation. Sprint duration has been found to affect the effort provided by participants during sprint and repeated-sprint tasks. Twenty-four strength trained men (age: 26 ± 5 years; height: 180.3 ± 6.1 cm; body-mass: 82.3 ± 6.9 kg) participated. During each of the four experimental trials, two sprints were performed 12 minutes apart. The recovery activity between sprints was either a mixture of active and passive recovery or was just passive recovery. The first sprint was always 18 s, but the second sprint was either 9 s or 18 s. In addition to MPO and PPO, lactate concentration, ratings of sprint preparation, ratings of sprint performance, and perceptions of recovery, were measured. Post-trial and post-study questionnaires were also completed, exploring factors that may have influenced performance that day. A sprint number × recovery method interaction (F(1,23) = 28.791, p < 0.001, ƞ_p^2 = 0.556) was found on PPO, with a significantly lower PPO in sprint 2 following passive recovery. A sprint number × recovery method interaction was not, however, found on MPO (F(1,23) = 2.513, p = 0.127, ƞ_p^2 = 0.098). Sprint number × second sprint duration interaction effects were found on both PPO (F(1,23) = 9.867, p = 0.005, ƞ_p^2 = 0.300) and MPO over the first 9 s of the sprint (F(1,23) = 8.922, p = 0.007, ƞ_p^2 = 0.279), although post hoc tests were unable to identify the cause of either effect. Nonetheless, the existence of these sprint number × second sprint duration interaction effects, combined with responses provided to the questionnaires, provided some evidence of a change in effort depending on the duration of the task. Pre-testing data collection was then conducted (Chapter 6) to evaluate whether a greater performance loss effect size would be generated between two sprints if longer sprints (27 s compared to 18 s) were undertaken. A larger performance loss effect size could increase the probability of identifying an effect of a change in effort on repeated-sprint performance. Eight strength-trained men (25 ± 6 years; 180.4 ± 6.6 cm; 84.5 ± 8.4 kg) that had participated in Chapter 5 visited the laboratory on a single occasion. During the visit, two 27 s sprints were undertaken 12 minutes apart, with a mixture of active and passive recovery performed between sprints. The performance loss effect size was then calculated using Hedges g. Whilst the size of the effect did remain small, the effect size was found to be greater when longer sprints were undertaken (27 s sprints: Hedges g = 0.20; 18 s sprints: Hedges g = 0.13). Therefore, 27 s sprints were used in the final study. The aim of the final study (Chapter 7) was to examine whether a simulated competition would affect repeated-sprint performance. It was proposed that the motivational effect of competition could affect performance as a result of a stress response, heightening readiness to perform. Sixteen resistance-trained men (age: 25 ± 4 years; height: 1.80 ± 0.07 m; body-mass: 83.3 ± 10.9 kg) participated. In both the control and simulated competition conditions, two 27 s sprints were undertaken 12 minutes apart. Recordings of the R-wave to R-wave (R-R) interval duration were taken at rest, after the warm-up, and at the end of the trial for the measurement of heart rate variability (HRV), with saliva samples being taken at the same time-points for the assessment of alpha amylase (AA) activity and AA output. Five motivational components (crowd presence, financial reward, leaderboard, performance feedback, and verbal encouragement) were included in the simulated competition. Both MPO (F(1,15) = 12.419, p = 0.003, ƞ_p^2 = 0.453) and PPO (F(1,15) = 23.760, p < 0.001, ƞ_p^2 = 0.613) were found to be higher in the simulated competition. Alterations were also found in several HRV metrics (mean heart rate, mean R-R, the root mean square of successive differences, low frequency normalised (nu) power, high-frequency (HF) power, HFnu, and the Poincaré plot standard deviation perpendicular to the line of identity and the Poincaré plot standard deviation along the line of identity), as well as in AA activity (F(1,10) = 6.401, p = 0.030, ƞ_p^2 = 0.390) and AA output (F(1,10) = 5.342, p = 0.043, ƞ_p^2 = 0.348), suggesting that greater levels of physiological stress were experienced during the competition. Overall, the findings from this PhD highlighted sprint performance and recovery considerations for athletes competing in the Match Sprint, with MPO and PPO being consistently reduced when a second sprint was performed with a recovery duration that may occur during a competition. The current practice of performing a mixture of active and passive recovery was found to aid with the recovery of PPO, although the effect on MPO was not apparent. Further investigation may, therefore, be required to guide best practice. Competition may also improve sprint cycling performance. The performance changes that were found in the simulated competition mean that competition could be used as a motivational training tool. The effect of competition on performance also generated methodological questions for researchers investigating sprint cycling performance, when the aim is for the performance to provide a better representation of a true maximal effort or in instances when researchers are seeking to generalise their findings to sports competitions.