PurposeGiven the important role of the brain in regulating endurance performance, this comparative study sought to determine whether professional road cyclists have superior inhibitory control and resistance to mental fatigue compared to recreational road cyclists.MethodsAfter preliminary testing and familiarization, eleven professional and nine recreational road cyclists visited the lab on two occasions to complete a modified incongruent colour-word Stroop task (a cognitive task requiring inhibitory control) for 30 min (mental exertion condition), or an easy cognitive task for 10 min (control condition) in a randomized, counterbalanced cross-over order. After each cognitive task, participants completed a 20-min time trial on a cycle ergometer. During the time trial, heart rate, blood lactate concentration, and rating of perceived exertion (RPE) were recorded.ResultsThe professional cyclists completed more correct responses during the Stroop task than the recreational cyclists (705±68 vs 576±74, p = 0.001). During the time trial, the recreational cyclists produced a lower mean power output in the mental exertion condition compared to the control condition (216±33 vs 226±25 W, p = 0.014). There was no difference between conditions for the professional cyclists (323±42 vs 326±35 W, p = 0.502). Heart rate, blood lactate concentration, and RPE were not significantly different between the mental exertion and control conditions in both groups.ConclusionThe professional cyclists exhibited superior performance during the Stroop task which is indicative of stronger inhibitory control than the recreational cyclists. The professional cyclists also displayed a greater resistance to the negative effects of mental fatigue as demonstrated by no significant differences in perception of effort and time trial performance between the mental exertion and control conditions. These findings suggest that inhibitory control and resistance to mental fatigue may contribute to successful road cycling performance. These psychobiological characteristics may be either genetic and/or developed through the training and lifestyle of professional road cyclists.

The physiological determinants of performance in two Yo-Yo intermittent recovery tests (Yo-YoIR1 and Yo-YoIR2) were examined in 25 professional (n = 13) and amateur (n = 12) soccer players. The aims of the study were (1) to examine the differences in physiological responses to Yo-YoIR1 and Yo-YoIR2, (2) to determine the relationship between the aerobic and physiological responses to standardized high-intensity intermittent exercise (HIT) and Yo-Yo performance, and (3) to investigate the differences between professional and amateur players in performance and responses to these tests. All players performed six tests: two versions of the Yo-Yo tests, a test for the determination of maximum oxygen uptake (V(O)(2)(max)), a double test to determine V(O)(2) kinetics and a HIT evaluation during which several physiological responses were measured. The anaerobic contribution was greatest during Yo-YoIR2. V(O)(2)(max) was strongly correlated with Yo-YoIR1 (r = 0.74) but only moderately related to Yo-YoIR2 (r = 0.47). The time constant (tau) of V(O)(2) kinetics was largely related to both Yo-Yo tests (Yo-YoIR1: r = 0.60 and Yo-YoIR2: r = 0.65). The relationships between physiological variables measured during HIT (blood La(-), H(+), HCO(3) (-) and the rate of La(-) accumulation) and Yo-Yo performance (in both versions) were very large (r > 0.70). The physiological responses to HIT and the tau of the V(O)(2) kinetics were significantly different between professional and amateur soccer players, whilst V(O)(2)(max) was not significantly different between the two groups. In conclusion, V(O)(2)(max) is more important for Yo-YoIR1 performance, whilst tau of the V(O)(2) kinetics and the ability to maintain acid-base balance are important physiological factors for both Yo-Yo tests.

The aim of this study was to quantify the demands of road competitions ending with sprints in male professional cycling. 17 races finished with top-5 results from 6 male road professional cyclists (age, 27.0±3.8 years; height, 1.76±0.03 m; weight, 71.7±1.1 kg) were analysed. SRM power meters were used to monitor power output, cadence and speed. Data were averaged over the entire race, different durations prior to the sprint (60, 10, 5 and 1 min) and during the actual sprint. Variations in power during the final 10 min of the race were quantified using exposure variation analysis. This observational study was conducted in the field to maximize the ecological validity of the results. Power, cadence and speed were statistically different between various phases of the race (p<0.001), increasing from 316±43 W, 95±4 rpm and 50.5±3.3 km·h(-1) in the last 10 min, to 487±58 W, 102±6 rpm and 55.4±4.7 km·h(-1) in the last min prior to the sprint. Peak power during the sprint was 17.4±1.7 W·kg(-1). Exposure variation analysis revealed a significantly greater number of short-duration high-intensity efforts in the final 5 min of the race, compared with the penultimate 5 min (p=0.010). These findings quantify the power output requirements associated with high-level sprinting in men's professional road cycling and highlight the need for both aerobic and anaerobic fitness.

The purpose of this 2-part commentary series is† to explain why we believe our ability to control injury risk by manipulating training load (TL) in its current state is an illusion and why the foundations of this illusion are weak and unreliable. In part 1, we introduce the training process framework and contextualize the role of TL monitoring in the injury-prevention paradigm. In part 2, we describe the conceptual and methodologic pitfalls of previous authors who associated TL and injury in ways that limited their suitability for the derivation of practical recommendations. The first important step in the training process is developing the training program: the practitioner develops a strategy based on available evidence, professional knowledge, and experience. For decades, exercise strategies have been based on the fundamental training principles of overload and progression. Training-load monitoring allows the practitioner to determine whether athletes have completed training as planned and how they have coped with the physical stress. Training load and its associated metrics cannot provide a quantitative indication of whether particular load progressions will increase or decrease the injury risk, given the nature of previous studies (descriptive and at best predictive) and their methodologic weaknesses. The overreliance on TL has moved the attention away from the multifactorial nature of injury and the roles of other important contextual factors. We argue that no evidence supports the quantitative use of TL data to manipulate future training with the purpose of preventing injury. Therefore, determining “how much is too much” and how to properly manipulate and progress TL are currently subjective decisions based on generic training principles and our experience of adjusting training according to an individual athlete's response. Our message to practitioners is to stop seeking overly simplistic solutions to complex problems and instead embrace the risks and uncertainty inherent in the training process and injury prevention.

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