Optimal pacing in road cycling using a nonlinear power constraint

In the individual road cycling discipline known as a time-trial, variable power pacing under variable grade conditions leads to improved performance. However, it is unclear whether these power variations result in an optimal finishing time. Typical pacing strategies use an average power constraint, which requires maintaining a constant speed regardless of grade fluctuations; however, this is physiologically infeasible for cyclists. We used an exponentially weighted average (EWA) power constraint in which a nonlinear relationship between the power output and physiological cost was assumed. We defined the optimal pacing (OP) strategy by minimizing the total cycling time subject to the EWA power constraint, and set the EWA of the power output of both the OP and constant power (CP) strategies to the same baseline value. The model showed that the OP strategy outperformed the CP strategy in terms of minimizing the finishing time under variable grade conditions, the power distribution of the OP strategy was identical to that of the CP strategy under constant grade conditions, and the average power output of the OP strategy was always lower than that of the CP strategy under variable grade conditions. Numerical simulations were performed on two hypothetical 40-km courses using both the CP and OP strategies. We found that under variable grade conditions, the time-saving rates of the OP strategy relative to the CP strategy were 2.7 and 2.8% for the two simulated courses.     

Science and cycling: current knowledge and future directions for research

In this holistic review of cycling science, the objectives are: (1) to identify the various human and environmental factors that influence cycling power output and velocity; (2) to discuss, with the aid of a schematic model, the often complex interrelationships between these factors; and (3) to suggest future directions for research to help clarify how cycling performance can be optimized, given different race disciplines, environments and riders. Most successful cyclists, irrespective of the race discipline, have a high maximal aerobic power output measured from an incremental test, and an ability to work at relatively high power outputs for long periods. The relationship between these characteristics and inherent physiological factors such as muscle capilliarization and muscle fibre type is complicated by inter-individual differences in selecting cadence for different race conditions. More research is needed on high-class professional riders, since they probably represent the pinnacle of natural selection for, and physiological adaptation to, endurance exercise. Recent advances in mathematical modelling and bicycle-mounted strain gauges, which can measure power directly in races, are starting to help unravel the interrelationships between the various resistive forces on the bicycle (e.g. air and rolling resistance, gravity). Interventions on rider position to optimize aerodynamics should also consider the impact on power output of the rider. All-terrain bicycle (ATB) racing is a neglected discipline in terms of the characterization of power outputs in race conditions and the modelling of the effects of the different design of bicycle frame and components on the magnitude of resistive forces. A direct application of mathematical models of cycling velocity has been in identifying optimal pacing strategies for different race conditions. Such data should, nevertheless, be considered alongside physiological optimization of power output in a race. An even distribution of power output is both physiologically and biophysically optimal for longer ( > 4 km) time-trials held in conditions of unvarying wind and gradient. For shorter races (e.g. a 1 km time-trial), an 'all out' effort from the start is advised to 'save' time during the initial phase that contributes most to total race time and to optimize the contribution of kinetic energy to race velocity. From a biophysical standpoint, the optimum pacing strategy for road time-trials may involve increasing power in headwinds and uphill sections and decreasing power in tailwinds and when travelling downhill. More research, using models and direct power measurement, is needed to elucidate fully how much such a pacing strategy might save time in a real race and how much a variable power output can be tolerated by a rider. The cyclist's diet is a multifactorial issue in itself and many researchers have tried to examine aspects of cycling nutrition (e.g. timing, amount, composition) in isolation. Only recently have researchers attempted to analyse interrelationships between dietary factors (e.g. the link between pre-race and in-race dietary effects on performance). The thermal environment is a mediating factor in choice of diet, since there may be competing interests of replacing lost fluid and depleted glycogen during and after a race. Given the prevalence of stage racing in professional cycling, more research into the influence of nutrition on repeated bouts of exercise performance and training is required.     

Science and cycling: current knowledge and future directions for research

Abstract

In this holistic review of cycling science, the objectives are: (1) to identify the various human and environmental factors that influence cycling power output and velocity; (2) to discuss, with the aid of a schematic model, the often complex interrelationships between these factors; and (3) to suggest future directions for research to help clarify how cycling performance can be optimized, given different race disciplines, environments and riders. Most successful cyclists, irrespective of the race discipline, have a high maximal aerobic power output measured from an incremental test, and an ability to work at relatively high power outputs for long periods. The relationship between these characteristics and inherent physiological factors such as muscle capilliarization and muscle fibre type is complicated by inter-individual differences in selecting cadence for different race conditions. More research is needed on high-class professional riders, since they probably represent the pinnacle of natural selection for, and physiological adaptation to, endurance exercise. Recent advances in mathematical modelling and bicycle-mounted strain gauges, which can measure power directly in races, are starting to help unravel the interrelationships between the various resistive forces on the bicycle (e.g. air and rolling resistance, gravity). Interventions on rider position to optimize aerodynamics should also consider the impact on power output of the rider. All-terrain bicycle (ATB) racing is a neglected discipline in terms of the characterization of power outputs in race conditions and the modelling of the effects of the different design of bicycle frame and components on the magnitude of resistive forces. A direct application of mathematical models of cycling velocity has been in identifying optimal pacing strategies for different race conditions. Such data should, nevertheless, be considered alongside physiological optimization of power output in a race. An even distribution of power output is both physiologically and biophysically optimal for longer ( >4km) time-trials held in conditions of unvarying wind and gradient. For shorter races (e.g. a 1km time-trial), an‘all out’ effort from the start is advised to‘save’ time during the initial phase that contributes most to total race time and to optimize the contribution of kinetic energy to race velocity. From a biophysical standpoint, the optimum pacing strategy for road time-trials may involve increasing power in headwinds and uphill sections and decreasing power in tailwinds and when travelling downhill. More research, using models and direct power measurement, is needed to elucidate fully how much such a pacing strategy might save time in a real race and how much a variable power output can be tolerated by a rider. The cyclist's diet is a multifactorial issue in itself and many researchers have tried to examine aspects of cycling nutrition (e.g. timing, amount, composition) in isolation. Only recently have researchers attempted to analyse interrelationships between dietary factors (e.g. the link between pre-race and in-race dietary effects on performance). The thermal environment is a mediating factor in choice of diet, since there may be competing interests of replacing lost fluid and depleted glycogen during and after a race. Given the prevalence of stage racing in professional cycling, more research into the influence of nutrition on repeated bouts of exercise performance and training is required.     

Comparing bioenergetic models for the optimisation of pacing strategy in road cycling

Road cycling performance is dependent on race tactics and pacing strategy. To optimise the pacing strategy for any race performed with no drafting, a numerical model was introduced, one that solves equations of motion while minimising the finishing time by varying the power output along the course. The power output was constrained by two different hydraulic models: the simpler critical power model for intermittent exercise (CPIE) and the more sophisticated Margaria–Morton model (M–M). These were compared with a constant power strategy (CPS). The simulation of the three different models was carried out on a fictional 75 kg cyclist, riding a 2,000 m course. This resulted in finishing times of 162.4, 155.8 and 159.3 s and speed variances of 0.58, 0.26 and 0.29 % for the CPS, CPIE and M–M simulations, respectively. Furthermore, the average power output was 469.7, 469.7 and 469.1 W for the CPS, CPIE and M–M simulations, respectively. The M–M model takes more physiological phenomena into consideration compared to the CPIE model and, therefore, contributes to an optimised pacing strategy that is more realistic. Therefore, the M–M model might be more suitable for future studies on optimal pacing strategy, despite the relatively slower finishing time.     

Power variation strategies for cycling time trials: a differential equation model

In cycling time trials, competitors aim to ride a course in the fastest possible time and the implementation of a pacing strategy is therefore essential. In this study, a differential equation model of a cyclist incorporating continuous changes in velocity is formulated and applied to a selection of theoretical courses and athletes. The model is augmented with a constraint corresponding to a mean work rate and various pacing strategies are considered. The inclusion of continuous accelerations experienced by the cyclist forms an essential component in a model for courses comprising many changes of gradient, and a steady-state approximation, which has previously been used to assess pacing strategies, is not suitable. In addition to formulating a result on the mathematically optimal solution of the model equations subject to the mean power constraint, it is also shown that substantial time savings can be realized by cyclists increasing their work rates on uphill sections and suitably reducing their work rates elsewhere. However, the amount of time saved is highly course- and athlete-dependent with the greatest gains arising on courses with the longest continuous ascents by cyclists of greatest mass.     

Effects of Experience and Opponents on Pacing Behavior and 2-km Cycling Performance of Novice Youths

ABSTRACT

Purpose: To study the pacing behavior and performance of novice youth exercisers in a controlled laboratory setting. Method: Ten healthy participants (seven male, three female, 15.8 ± 1.0 years) completed four, 2-km trials on a Velotron cycling ergometer. Visit 1 was a familiarization trial. Visits 2 to 4 involved the following conditions, in randomized order: no opponent (NO), a virtual opponent (starting slow and finishing fast) (OP-SLOWFAST), and a virtual opponent (starting fast and finishing slow) (OP-FASTSLOW). Repeated measurement ANOVAs (p < .05) were used to examine differences in both pacing behavior and also performance related to power output, finishing- and split times, and RPE between the four successive visits and the three conditions. Expected performance outcome was measured using a questionnaire. Results: Power output increased (F_3,27 = 5.651, p = .004, η²_p = .386) and finishing time decreased (F_3,27 = 9.972, p < .001, η²_p = .526) between visit 1 and visits 2, 3 and 4. In comparison of the first and second visit, the difference between expected finish time and actual finishing time decreased by 66.2%, regardless of condition. The only significant difference observed in RPE score was reported at the 500 m point, where RPE was higher during visit 1 compared to visits 3 and 4, and during visit 2 compared to visit 4 (p < .05). No differences in pacing behavior, performance, or RPE were found between conditions (p > .05). Conclusion: Performance was improved by an increase in experience after one visit, parallel with the ability to anticipate future workload.     

Variable versus constant power strategies during cycling time-trials: prediction of time savings using an up-to-date mathematical model

Swain (1997) employed the mathematical model of Di Prampero et al. (1979) to predict that, for cycling time-trials, the optimal pacing strategy is to vary power in parallel with the changes experienced in gradient and wind speed. We used a more up-to-date mathematical model with validated coefficients (Martin et al., 1998) to quantify the time savings that would result from such optimization of pacing strategy. A hypothetical cyclist (mass = 70 kg) and bicycle (mass = 10 kg) were studied under varying hypothetical wind velocities (-10 to 10 m x s(-1)), gradients (-10 to 10%), and pacing strategies. Mean rider power outputs of 164, 289, and 394 W were chosen to mirror baseline performances studied previously. The three race scenarios were: (i) a 10-km time-trial with alternating 1-km sections of 10% and -10% gradient; (ii) a 40-km time-trial with alternating 5-km sections of 4.4 and -4.4 m x s(-1) wind (Swain, 1997); and (iii) the 40-km time-trial delimited by Jeukendrup and Martin (2001). Varying a mean power of 289 W by +/- 10% during Swain's (1997) hilly and windy courses resulted in time savings of 126 and 51 s, respectively. Time savings for most race scenarios were greater than those suggested by Swain (1997). For a mean power of 289 W over the "standard" 40-km time-trial, a time saving of 26 s was observed with a power variability of 10%. The largest time savings were found for the hypothetical riders with the lowest mean power output who could vary power to the greatest extent. Our findings confirm that time savings are possible in cycling time-trials if the rider varies power in parallel with hill gradient and wind direction. With a more recent mathematical model, we found slightly greater time savings than those reported by Swain (1997). These time savings compared favourably with the predicted benefits of interventions such as altitude training or ingestion of carbohydrate-electrolyte drinks. Nevertheless, the extent to which such power output variations can be tolerated by a cyclist during a time-trial is still unclear.     

Step-to-step spatiotemporal variables and ground reaction forces of intra-individual fastest sprinting in a single session

We aimed to investigate the step-to-step spatiotemporal variables and ground reaction forces during the acceleration phase for characterising intra-individual fastest sprinting within a single session. Step-to-step spatiotemporal variables and ground reaction forces produced by 15 male athletes were measured over a 50-m distance during repeated (three to five) 60-m sprints using a long force platform system. Differences in measured variables between the fastest and slowest trials were examined at each step until the 22nd step using a magnitude-based inferences approach. There were possibly–most likely higher running speed and step frequency (2nd to 22nd steps) and shorter support time (all steps) in the fastest trial than in the slowest trial. Moreover, for the fastest trial there were likely–very likely greater mean propulsive force during the initial four steps and possibly–very likely larger mean net anterior–posterior force until the 17th step. The current results demonstrate that better sprinting performance within a single session is probably achieved by 1) a high step frequency (except the initial step) with short support time at all steps, 2) exerting a greater mean propulsive force during initial acceleration, and 3) producing a greater mean net anterior–posterior force during initial and middle acceleration.     

A mathematical model for simulating cycling: applied to track cycling

A review of existing mathematical models for velodrome cycling suggests that cyclists and cycling coaches could benefit from an improved simulation tool. A continuous mathematical model for cycling has been developed that includes calculated slip and steering angles and, therefore, allows for resulting variation in rolling resistance. The model focuses on aspects that are particular, but not unique, to velodrome cycling but could be used for any cycling event. Validation of the model is provided by power meter, wheel speed and timing data obtained from two different studies and eight different athletes. The model is shown to predict the lap by lap performance of six elite female athletes to an average accuracy of 0.36% and the finishing times of two elite athletes competing in a 3-km individual pursuit track cycling event to an average accuracy of 0.20%. Possible reasons for these errors are presented. The impact of speed on steering input is discussed as an example application of the model.     

Effects of magnitude and frequency of variations in external power output on simulated cycling time-trial performance

Abstract

Mechanical models of cycling time-trial performance have indicated adverse effects of variations in external power output on overall performance times. Nevertheless, the precise influences of the magnitude and number of these variations over different distances of time trial are unclear. A hypothetical cyclist (body mass 70 kg, bicycle mass 10 kg) was studied using a mathematical model of cycling, which included the effects of acceleration. Performance times were modelled over distances of 4–40 km, mean power outputs of 200–600 W, power variation amplitudes of 5–15% and variation frequencies of 2–32 per time-trial. Effects of a “fast-start” strategy were compared with those of a constant-power strategy. Varying power improved 4-km performance at all power outputs, with the greatest improvement being 0.90 s for ± 15% power variation. For distances of 16.1, 20 and 40 km, varying power by ± 15% increased times by 3.29, 4.46 and 10.43 s respectively, suggesting that in long-duration cycling in constant environmental conditions, cyclists should strive to reduce power variation to maximise performance. The novel finding of the present study is that these effects are augmented with increasing event distance, amplitude and period of variation. These two latter factors reflect a poor adherence to a constant speed.     

Effects of power variation on cycle performance during simulated hilly time-trials

It has previously been shown that cyclists are unable to maintain a constant power output during cycle time-trials on hilly courses. The purpose of the present study is therefore to quantify these effects of power variation using a mathematical model of cycling performance. A hypothetical cyclist (body mass: 70?kg, bicycle mass: 10?kg) was studied using a mathematical model of cycling, which included the effects of acceleration. Performance was modelled over three hypothetical 40-km courses, comprising repeated 2.5-km sections of uphill and downhill with gradients of 1%, 3%, and 6%, respectively. Amplitude (5–15%) and distance (0.31–20.00?km) of variation were modelled over a range of mean power outputs (200–600?W) and compared to sustaining a constant power. Power variation was typically detrimental to performance; these effects were augmented as the amplitude of variation and severity of gradient increased. Varying power every 1.25?km was most detrimental to performance; at a mean power of 200?W, performance was impaired by 43.90?s (±15% variation, 6% gradient). However at the steepest gradients, the effect of power variation was relatively independent of the distance of variation. In contrast, varying power in parallel with changes in gradient improved performance by 188.89?s (±15% variation, 6% gradient) at 200?W. The present data demonstrate that during hilly time-trials, power variation that does not occur in parallel with changes in gradient is detrimental to performance, especially at steeper gradients. These adverse effects are substantially larger than those previously observed during flat, windless time-trials.     

Performance determinants of fixed gear cycling during criteriums

Nowadays, fixed gear competitions on outdoor circuits such as criteriums are regularly organized worldwide. To date, no study has investigated this alternative form of cycling. The purpose of the present study was to examine fixed gear performance indexes and to characterize physiological determinants of fixed gear cyclists. This study was carried out in two parts. Part 1 (n?=?36) examined correlations between performance indexes obtained during a real fixed gear criterium (time trial, fastest laps, averaged lap time during races, fatigue indexes) and during a sprint track time trial. Part 2 (n?=?9) examined correlations between the recorded performance indexes and some aerobic and anaerobic performance outputs (VO_2max, maximal aerobic power, knee extensor and knee flexor maximal voluntary torque, vertical jump height and performance during a modified Wingate test). Results from Part 1 indicated significant correlations between fixed gear final performance (i.e. average lap time during the finals) and single lap time (time trial, fastest lap during races and sprint track time trial). In addition, results from Part 2 revealed significant correlations between fixed gear performance and aerobic indicators (VO_2max and maximal aerobic power). However, no significant relationship was obtained between fixed gear cycling and anaerobic qualities such as strength. Similarly to traditional cycling disciplines, we concluded that fixed gear cycling is mainly limited by aerobic capacity, particularly criteriums final performance. However, specific skills including technical competency should be considered.     

Freestyle race pacing strategies (400 m) of elite able-bodied swimmers and swimmers with disability at major international championships

Freestyle race pacing strategies (400 m) were compared between elite able-bodied swimmers and those with minimal physical (International Paralympic Committee S10 classification) and visual disabilities (International Paralympic Committee S13 classification). Data comprised 50-m lap splits and overall race times from 1176 400-m freestyle swims from World Championships, European Championships and Olympic/Paralympic Games between 2006 and 2012. Five pacing strategies were identified across groups (even, fast start, negative, parabolic and parabolic fast start), with negative and even strategies the most commonly adopted. The negative pacing strategy produced the fastest race times for all groups except for female S13 swimmers where an even strategy was most effective. Able-bodied groups swam faster than their S10 and S13 counterparts, with no differences between S10 and S13 groups. The results suggest adoption of multiple pacing strategies across groups, and even where impairments are considered minimal they are still associated with performance detriments in comparison to their able-bodied counterparts. The findings have implications for the planning and implementation of training related to pacing strategies to ensure optimal swimmer preparation for competition. Analogous performance levels in S10 and S13 swimmers also suggest a case for integrated competition of these classifications in 400-m freestyle swimming.     

Effects of radiant heat exposure on pacing pattern during a 15-km cycling time trial

Abstract

The goal of this study was to investigate the effects of different durations of skin temperature manipulation on pacing patterns and performance during a 15-km cycling time trial. Nineteen well-trained men completed three 15-km cycling time trials in 18°C and 50% relative humidity with 4.5-km (short-heat), 9.0-km (long-heat) or without (control) radiant heat exposure applied by infrared heaters after 1.5 km in the time trial. During the time trials, power output, mean skin temperature, rectal temperature, heart rate and rating of perceived exertion were assessed. The radiant heat exposure resulted in higher mean skin temperature during the time trial for short-heat (35.0 ± 0.6°C) and long-heat (35.3 ± 0.5°C) than for control (32.5 ± 1.0°C; P < 0.001), whereas rectal temperature was similar (P = 0.55). The mean power output was less for short-heat (273 ± 8 W; P = 0.001) and long-heat (271 ± 9 W; P = 0.02) than for control (287 ± 7 W), but pacing patterns did not differ (P = 0.55). Heart rate was greatest in control (177 ± 9 beats · min^?1; P < 0.001), whereas the rating of perceived exertion remained similar. We concluded that a radiant heat exposure and associated higher skin temperature reduced overall performance, but did not modify pacing pattern during a 15-km cycling time trial, regardless of the duration of the exposure.     

Exercise, plasma catecholamine concentrations and decision-making performance of soccer players on a soccer-specific test.

The main aim of this study was to compare the decision-making performance of college soccer players on a soccer-specific, tachistoscopically presented test, at rest and while exercising at their adrenaline threshold and at their maximum power output. These were determined following an incremental test to exhaustion on a cycle ergometer. After the initial maximum power test, participants (n = 9) were allowed 10 habituation trials on the soccer decision-making test. Participants' decision-making performance was tested at rest, while cycling at a power output that had previously been determined to elicit their adrenaline threshold and while cycling at maximum power output. Accuracy and speed of decision were the dependent variables. A one-way repeated-measures analysis of variance showed no significant effect of exercise on accuracy, and showed speed of decision to be significantly affected by exercise. Tukey post-hoc tests showed that speed of decision at rest was significantly slower than in the other two conditions, which did not differ significantly from one another. Based on allocatable resources theories of arousal and performance, we conclude that the adrenaline threshold may be indicative of increases in the resources available to the individual. Furthermore, we considered that exercise at maximum power output may only induce a moderate rather than a high level of arousal.     

Seated versus standing position for maximization of performance during intense uphill cycling

It is not known whether the seated or standing position favours performance during intensive bouts of uphill cycling. The following hypotheses were therefore tested: (1) the standing position results in better performance at a high power output, while (2) the seated position is best at a moderate power output. We also assessed the seated-standing transition intensity, above which seated cycling should be superseded by standing cycling for maximization of performance. Ten male cyclists (mean age 27 years, s = 3; height 1.82 m, s = 0.07; body mass 75.2 kg, s = 7.0; VO2max 70.0 ml.kg(-1).min(-1), s = 5.2) performed seated and standing treadmill cycling to exhaustion at 10% grade and at four power outputs ranging from 86% to 165% of their power output at maximal oxygen uptake (Wmax). Power output at maximal oxygen uptake was obtained during determination of VO2max. There was no difference in time to exhaustion between the two cycling positions at 86% of Wmax (P = 0.29). All participants performed best at the highest power output (165% of Wmax) when standing (P = 0.002). An overall seated-standing transition intensity of 94% of Wmax was identified. Thus, in general, cyclists may choose either the standing or seated position for maximization of performance at a submaximal intensity of 86% of Wmax, while the standing position should be used at intensities above 94% of Wmax and approaching 165% of Wmax.     

Exercise,plasma catecholamine concentrations and decision-making performance of soccer players on a soccer-specific test

The main aim of this study was to compare the decision-making performance of college soccer players on a soccer-specific, tachistoscopically presented test, at rest and while exercising at their adrenaline threshold and at their maximum power output. These were determined following an incremental test to exhaustion on a cycle ergometer. After the initial maximum power test, participants (n= 9) were allowed 10 habituation trials on the soccer decision-making test. Participants' decision-making performance was tested at rest, while cycling at a power output that had previously been determined to elicit their adrenaline threshold and while cycling at maximum power output. Accuracy and speed of decision were the dependent variables. A one-way repeated measures analysis of variance showed no significant effect of exercise on accuracy, and showed speed of decision to be significantly affected by exercise. Tukey post-hoc tests showed that speed of decision at rest was significantly slower than in the other two conditions, which did not differ significantly from one another. Based on allocatable resources theories of arousal and performance, we conclude that the adrenaline threshold may be indicative of increases in the resources available to the individual. Furthermore, we considered that exercise at maximum power output may only induce a moderate rather than a high level of arousal.     

Laboratory predictors of uphill cycling performance in trained cyclists

ABSTRACT

This study aimed to assess the relationship between an uphill time-trial (TT) performance and both aerobic and anaerobic parameters obtained from laboratory tests. Fifteen cyclists performed a Wingate anaerobic test, a graded exercise test (GXT) and a field-based 20-min TT with 2.7% mean gradient. After a 5-week non-supervised training period, 10 of them performed a second TT for analysis of pacing reproducibility. Stepwise multiple regressions demonstrated that 91% of TT mean power output variation (W kg^?1) could be explained by peak oxygen uptake (ml kg^?1.min^?1) and the respiratory compensation point (W kg^?1), with standardised beta coefficients of 0.64 and 0.39, respectively. The agreement between mean power output and power at respiratory compensation point showed a bias ± random error of 16.2 ± 51.8 W or 5.7 ± 19.7%. One-way repeated-measures analysis of variance revealed a significant effect of the time interval (123.1 ± 8.7; 97.8 ± 1.2 and 94.0 ± 7.2% of mean power output, for epochs 0–2, 2–18 and 18–20 min, respectively; P < 0.001), characterising a positive pacing profile. This study indicates that an uphill, 20-min TT-type performance is correlated to aerobic physiological GXT variables and that cyclists adopt reproducible pacing strategies when they are tested 5 weeks apart (coefficients of variation of 6.3; 1 and 4%, for 0–2, 2–18 and 18–20 min, respectively).     

Pacing profiles and tactical behaviors of elite runners

The pacing behaviors used by elite athletes differ among individual sports, necessitating the study of sport-specific pacing profiles. Additionally, pacing behaviors adopted by elite runners differ depending on race distance. An “all-out” strategy, characterized by initial rapid acceleration and reduction in speed in the later stages, is observed during 100 m and 200 m events; 400 m runners also display positive pacing patterns, which is characterized by a reduction in speed throughout the race. Similarly, 800 m runners typically adopt a positive pacing strategy during paced “meet” races. However, during championship races, depending on the tactical approaches used by dominant athletes, pacing can be either positive or negative (characterized by an increase in speed throughout). A U-shaped pacing strategy (characterized by a faster start and end than during the middle part of the race) is evident during world record performances at meet races in 1500 m, 5000 m, and 10,000 m events. Although a parabolic J-shaped pacing profile (in which the start is faster than the middle part of the race but is slower than the endspurt) can be observed during championship 1500 m races, a negative pacing strategy with microvariations of pace is adopted by 5000 m and 10,000 m runners in championship races. Major cross country and marathon championship races are characterized by a positive pacing strategy; whereas a U-shaped pacing strategy, which is the result of a fast endspurt, is adopted by 3000 m steeplechasers and half marathoners. In contrast, recent world record marathon performances have been characterized by even pacing, which emphasizes the differences between championship and meet races at distances longer than 800 m. Studies reviewed suggest further recommendations for athletes. Throughout the whole race, 800 m runners should avoid running wide on the bends. In turn, during major championship events, 1500 m, 5000 m, and 10,000 m runners should try to run close to the inside of the track as much as possible during the decisive stages of the race when the speed is high. Staying within the leading positions during the last lap is recommended to optimize finishing position during 1500 m and 5000 m major championship races. Athletes with more modest aims than winning a medal at major championships are advised to adopt a realistic pace during the initial stages of long-distance races and stay within a pack of runners. Coaches of elite athletes should take into account the observed difference in pacing profiles adopted in meet races vs. those used in championship races: fast times achieved during races with the help of one or more pacemakers are not necessarily replicated in winner-takes-all championship races, where pace varies substantially. Although existing studies examining pacing characteristics in elite runners through an observational approach provide highly ecologically valid performance data, they provide little information regarding the underpinning mechanisms that explain the behaviors shown. Therefore, further research is needed in order to make a meaningful impact on the discipline. Researchers should design and conduct interventions that enable athletes to carefully choose strategies that are not influenced by poor decisions made by other competitors, allowing these athletes to develop more optimal and successful behaviors.     

Influence of upright versus time trial cycling position on determination of critical power and W′ in trained cyclists

Body position is known to alter power production and affect cycling performance. The aim of this study was to compare mechanical power output in two riding positions, and to calculate the effects on critical power (CP) and W′ estimates. Seven trained cyclists completed three peak power output efforts and three fixed-duration trial (3-, 5- and 12-min) riding with their hands on the brake lever hoods (BLH), or in a time trial position (TTP). A repeated-measures analysis of variance showed that mean power output during the 5-min trial was significantly different between BLH and TTP positions, resulting in a significantly lower estimate of CP, but not W′, for the TTP trial. In addition, TTP decreased the performance during each trial and increased the percentage difference between BLH and TTP with greater trial duration. There were no differences in pedal cadence or heart rate during the 3-min trial; however, TTP results for the 12-min trial showed a significant fall in pedal cadence and a significant rise in heart rate. The findings suggest that cycling position affects power output and influences consequent CP values. Therefore, cyclists and coaches should consider the cycling position used when calculating CP.