Purpose: In real-life competitive situations, athletes are required to continuously make decisions about how and when to invest their available energy resources. This study attempted to identify how different competitive environments invite elite short-track speed skaters to modify their pacing behavior during head-to-head competition. Methods: Lap times of elite 500-, 1000- and 1500-m short-track speed skating competitions between 2011 and 2016 (N = 34,095 races) were collected. Log-transformed lap and finishing times were analyzed with mixed linear models. The fixed effects in the model were sex, season, stage of competition, start position, competition importance, event number per tournament, number of competitors per race, altitude, and time qualification. The random effects of the model were athlete identity and the residual (within-athlete race-to-race variation). Separate analyses were performed for each event. Results: Several competitive environments, such as the number of competitors in a race (a higher number of competitors evoked most likely a faster initial pace; coefficient of variation [CV] = 1.9–9.3%), the stage of competition (likely to most likely, a slower initial pace was demonstrated in finals; CV = −1.4% to 2.0%), the possibility of time qualification (most likely a faster initial pace; CV = 2.6–5.0%), and competition importance (most likely faster races at the Olympics; CV = 1.3–3.5%), altered the pacing decisions of elite skaters in 1000- and 1500-m events. Stage of competition and start position affected 500-m pacing behavior. Conclusions: As demonstrated in this study, different competitive environments evoked modifications in pacing behavior, in particular in the initial phase of the race, emphasizing the importance of athlete–environment interactions, especially during head-to-head competitions.
Marco J. Konings and Florentina J. Hettinga
Marco J. Konings and Florentina J. Hettinga
Purpose: To objectively capture and understand tactical considerations in a race, the authors explored whether race-to-race variation of an athlete and the variation of competitors within a race could provide insight into how and when athletes modify their pacing decisions in response to other competitors. Methods: Lap times of elite 500-, 1000-, and 1500-m short-track speed-skating competitions from 2011 to 2016 (N = 6965 races) were collected. Log-transformed lap and finishing times were analyzed with mixed linear models. To determine within-athlete race-to-race variability, athlete identity (between-athletes differences) and the residual (within-athlete race-to-race variation) were added as random effects. To determine race variability, race identity (between-races differences) and the residual (within-race variation) were added as random effects. Separate analyses were performed for each event. Results: Within-athlete race-to-race variability of the finishing times increased with prolonged distance of the event (500-m, CV = 1.6%; 1000-m, CV = 2.8%; 1500-m, CV = 4.1%), mainly due to higher within-athlete race-to-race variability in the initial phase of 1000-m (3.3–6.9%) and 1500-m competitions (8.7–12.2%). During these early stages, within-race variability is relatively low in 1000-m (1.1–1.4%) and 1500-m (1.3–2.8%) competitions. Conclusion: The present study demonstrated how analyses of athlete and race variability could provide insight into tactical pacing decisions in sports where finishing position is emphasized over finishing time. The high variability of short-track skaters is a result of the decision to alter initial pacing behavior based on the behavior of other competitors in their race, emphasizing the importance of athlete–environment interactions in the context of pacing.
Marco J. Konings and Florentina J. Hettinga
Purpose: To examine whether preceding high-intensity race efforts in a competitive weekend affect pacing behavior and performance in elite short-track speed skaters. Methods: Finishing and intermediate lap times were gathered from 500-, 1000-, and 1500-m short-track speed skating world cups during the seasons 2011–2016. The effect of preceding races on pacing behavior and performance was explored using 2 studies. Study I: The effect of competing in extra races due to the repechage (Rep) system, leading to an increased number of high-intensity race efforts prior to the subsequent main tournament race, was explored (500-m, n = 32; 1000-m, n = 34; and 1500-m, n = 47). Study II: The performance of skaters over the tournament days was evaluated (500-m, n = 129; 1000-m, n = 54; and 1500-m, n = 114). For both analytic approaches, a 2-way repeated-measures analysis of variance was used to assess differences in pacing and performance within skaters over the races. Results: An additional number of preceding high-intensity race efforts due to the Rep system reduced the qualification percentage in the first main tournament race for the next stage of competition in all events (500-m, direct qualification = 57.3%, Rep = 25.0%; 1000-m, direct = 44.2%, Rep = 28.3%; and 1500-m, direct = 27.1%, Rep = 18.2%) and led to a decreased pace in the initial 2 laps of the 500-m event. By contrast, tournament day (Saturday vs Sunday) only affected the pacing behavior of female skaters during the 1500-m event. Conclusion: High-intensity race efforts earlier in the day affected pacing and performance of elite skaters, whereas the effect of high-intensity race efforts from the previous day seemed to be only marginal.
Marco J. Konings, Jordan Parkinson, Inge Zijdewind and Florentina J. Hettinga
Purpose: Performing against a virtual opponent has been shown to invite a change in pacing and improve time-trial (TT) performance. This study explored how this performance improvement is established by assessing changes in pacing, neuromuscular function, and perceived exertion. Methods: After a peak-power-output test and a familiarization TT, 12 trained cyclists completed two 4-km TTs in randomized order on a Velotron cycle ergometer. TT conditions were riding alone (NO) and riding against a virtual opponent (OP). Knee-extensor performance was quantified before and directly after the TT using maximal voluntary contraction force (MVC), voluntary activation (VA), and potentiated doublet-twitch force (PT). Differences between the experimental conditions were examined using repeated-measures ANOVAs. Linear-regression analyses were conducted to associate changes in pacing to changes in MVC, VA, and PT. Results: OP was completed faster than NO (mean power output OP 289.6 ± 56.1 vs NO 272.2 ± 61.6 W; P = .020), mainly due to a faster initial pace. This was accompanied by a greater decline in MVC (MVC pre vs post −17.5% ± 12.4% vs −11.4% ± 10.9%, P = .032) and PT (PT pre vs post −23.1% ± 14.0% vs −16.2% ±11.4%, P = .041) after OP than after NO. No difference between conditions was found for VA (VA pre vs post −4.9% ± 6.7% vs −3.4% ± 5.0%, P = .274). Rating of perceived exertion did not differ between OP and NO. Conclusion: The improved performance when racing against a virtual opponent was associated with a greater decline in voluntary and evoked muscle force than riding alone, without a change in perceived exertion, highlighting the importance of human–environment interactions in addition to one’s internal state for pacing regulation and performance.
Marco J. Konings, Olaf S. Noorbergen, David Parry and Florentina J. Hettinga
To gain more insight in pacing behavior and tactical positioning in 1500-m short-track speed skating, a sport in which several athletes directly compete in the same race.
Lap times and intermediate rankings of elite 1500-m short-track-skating competitors were collected over the season 2012–13 (N = 510, 85 races). Two statistical approaches were used to assess pacing behavior and tactical positioning. First, lap times were analyzed using a MANOVA, and for each lap differences between sex, race type, final rankings, and stage of competition were determined. Second, Kendall tau b correlations were used to assess relationships between intermediate and final rankings. In addition, intermediate rankings of the winner of each race were examined.
In 1500 m (13.5 laps of 111.12 m), correlations between intermediate and final ranking gradually increased throughout the race (eg, lap 1, r = .05; lap 7, r = .26; lap 13, r = .85). Moreover, the percentage of race winners skating in the leading position was over 50% during the last 3 laps. Top finishers were faster than bottom-place finishers only during the last 5 laps, with on average 0.1- to 1.5-s faster lap times of the race winners compared with the others during the last 5 laps.
Although a fast start led to faster finishing times, top finishers were faster than bottom-placed finishers only during the last 5 laps. Moreover, tactical positioning at 1 of the foremost positions during the latter phase of the race appeared to be a strong determinant of finishing position.
Olaf S. Noorbergen, Marco J. Konings, Dominic Micklewright, Marije T. Elferink-Gemser and Florentina J. Hettinga
To explore pacing behavior and tactical positioning during the shorter 500- and 1000-m short-track competitions.
Lap times and intermediate rankings of elite 500- and 1000-m short-track-skating competitors were collected over the 2012–13 season. First, lap times were analyzed using a MANOVA, and for each lap, differences between sex, race type, final ranking, and stage of competition were determined. Second, Kendall tau-b correlations were used to assess relationships between intermediate and final rankings. In addition, intermediate rankings of the winner of each race were examined.
Top-placed athletes appeared faster than bottom-placed athletes in every lap in the 500-m, while in the 1000-m no differences were found until the final 4 laps (P < .05). Correlations between intermediate and final rankings were already high at the beginning stages of the 50-m (lap 1: r = .59) but not for the 1000-m (lap 1: r = .21).
Although 500- and 1000-m short-track races are both relatively short, fundamental differences in pacing behavior and tactical positioning were found. A fast-start strategy seems to be optimal for 500-m races, while the crucial segment in 1000-m races seems to be from the 6th lap to the finish line (ie, after ± 650 m). These findings provide evidence to suggest that athletes balance between choosing an energetically optimal profile and the tactical and positional benefits that play a role when riding against an opponent, as well as contributing to developing novel insights in exploring athletic behavior when racing against opponents.
Dionne A. Noordhof, Carl Foster, Marco J.M. Hoozemans and Jos J. de Koning
Speed skating posture, or technique, is characterized by the push-off angle or effectiveness (e), determined as the angle between the push-off leg and the ice; the preextension knee angle (θ 0); and the trunk angle (θ 1). Together with muscle-power output and environmental conditions, skating posture, or technique, determines velocity (v).
To gain insight into technical variables that are important to skate efficiently and perform well, e, θ 0, θ 1, and skating v were determined every lap during a 5000-m World Cup. Second, the authors evaluated if changes (Δ) in e, θ 0, and θ 1 are associated with Δv.
One camera filmed the skaters from a frontal view, from which e was determined. Another camera filmed the skaters from a sagittal view, from which θ 0 and θ 1 were determined. Radio-frequency identification tags around the ankles of the skaters measured v.
During the race, e progressively increased and v progressively decreased, while θ 0 and θ 1 showed a less consistent pattern of change. Generalized estimating equations showed that Δe is significantly associated with Δv over the midsection of the race (β = −0.10, P < .001) and that Δθ 0 and Δθ 1 are not significantly associated with Δv.
The decrease in skating v over the race is not due to increases in power losses to air friction, as knee and trunk angle were not significantly associated with changes in velocity. The decrease in velocity can be partly ascribed to the decrease in effectiveness, which reflects a decrease in power production associated with fatigue.
Dionne A. Noordhof, Carl Foster, Marco J.M. Hoozemans and Jos J. de Koning
A meaningful association between changes (Δ) in push-off angle or effectiveness (e) and changes in skating velocity (v) has been found during 5000-m races, although no significant association was found between changes in knee (θ0) and trunk angle (θ1) and Δv. It might be that speed skating event, sex, and performance level influence these associations.
To study the effect of skating event, sex, and performance level on the association between Δe and Δv and between Δθ0 and Δθ1 and Δv.
Video recordings were made from frontal (e) and sagittal views (θ0 and θ1) during 1500- and 5000-m men’s and women’s World Cup races. Radio-frequency identification tags provided data of v.
Skating event influenced the association between Δe and Δv, which resulted in a significant association between Δe and Δv for the 5000-m (β = –0.069, 95% confidence interval [–0.11, –0.030]) but not for the 1500-m (β = –0.011 [–0.032, 0.010]). The association between Δθ0 and Δθ1 and Δv was not significantly influenced by skating event. Sex and performance level did not substantially affect the association between Δe and Δv and between Δθ0 and Δθ1 and Δv.
Skating event significantly influenced the association between Δe and Δv; a 1° change in e results in a 0.011-m/s decrease in v during the 1500-m and a 0.069-m/s decrease in v during the 5000-m. Thus, it seems especially important to maintain a small e during the 5000-m.
Stein G.P. Menting, Marco J. Konings, Marije T. Elferink-Gemser and Florentina J. Hettinga
Purpose: To gain insight into the development of pacing behavior of youth athletes in 1500-m short-track speed-skating competition. Methods: Lap times and positioning of elite short-track skaters during the seasons 2011/2012–2015/2016 were analyzed (N = 9715). The participants were grouped into age groups: under 17 (U17), under 19 (U19), under 21 (U21), and senior. The difference between age groups, sexes, and stages of competition within each age group were analyzed through a multivariate analysis of variance (P < .05) of the relative section times (lap time as a percentage of total race time) per lap and by analyzing Kendall tau-b correlations between intermediate positioning and final ranking. Results: The velocity distribution over the race differed between all age groups, explicitly during the first 4 laps (U17: 7.68% [0.80%], U19: 7.77% [0.81%], U21: 7.82% [0.81%], and senior: 7.80% [0.82%]) and laps 12, 13, and 14 (U17: 6.92% [0.14%], U19: 6.83% [0.13%], U21: 6.79% [0.14%], and senior: 6.69% [0.12%]). In all age groups, a difference in velocity distribution was found between the sexes and between finalists and nonfinalists. Positioning data demonstrated that youth skaters showed a higher correlation between intermediate position and final ranking in laps 10, 11, and 12 than seniors. Conclusions: Youth skaters displayed less conservative pacing behavior than seniors. The pacing behavior of youths, expressed in relative section times and positioning, changed throughout adolescence and came to resemble that of seniors. Pacing behavior and adequately responding to environmental cues in competition could therefore be seen as a self-regulatory skill that is under development throughout adolescence.
Levi Heimans, Wouter R. Dijkshoorn, Marco J.M. Hoozemans and Jos J. de Koning
Purpose: Since the aim of the men’s team pursuit in time-trial track cycling is to accomplish a distance of 4000 m as fast as possible, optimizing aerodynamic drag can contribute to achieving this goal. The aim of this study was to determine the drafting effect in second, third, and fourth position during the team pursuit in track cycling as a function of the team members’ individual frontal areas in order to minimize the required power. Method: Eight experienced track cyclists of the Dutch national selection performed 39 trials of 3 km in different teams of 4 cyclists at a constant velocity of 15.75 m/s. Frontal projected areas were determined, and together with field-derived drag coefficients for all 4 positions, the relationships between frontal areas of team members and drag fractions were estimated using generalized estimating equations. Results: The frontal area of both the cyclist directly in front of the drafter and the drafter himself turned out to be significant determinants of the drag fraction at the drafter’s position (P < .05) for all 3 drafting positions. Predicted required power for individuals in drafting positions differed up to 35 W depending on team composition. For a team, a maximal difference in team efficiency (1.2%) exists by selecting cyclists in a specific sequence. Conclusion: Estimating required power for a specific team composition gives insight into differences in team efficiency for the team pursuit. Furthermore, required power for individual team members ranges substantially depending on team composition.