Estreich Harry, Bullock Nicola, Osborne Mark, Santos-Fernandez Edgar, Wu Paul Pao-Yen
School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia.
PLoS One. 2025 Jul 2;20(7):e0326375. doi: 10.1371/journal.pone.0326375. eCollection 2025.
This study analysed sprint kayak pacing profiles in order to categorise and compare an athlete's race profile throughout their career. We used functional principal component analysis of normalised velocity data for 500m and 1000m races to quantify pacing. The first four principal components explained 90.77% of the variation over 500m and 78.80% over 1000m. These principal components were then associated with unique pacing characteristics with the first component defined as a dropoff in velocity and the second component defined as a kick. All other defined characteristics were a variation of these two, i.e., late kick. We then applied a Hidden Markov model to categorise each profile over an athlete's career, using the PC scores, into different types of race profiles. This model included age and event type and identified a trend for a higher dropoff in development pathway athletes. Using the four different race profile types, four athletes had all their race profiles throughout their careers analysed. It was identified that an athlete's pacing profile changes throughout their career as an athlete matures. This information provides coaches, practitioners and athletes with expectations as to how pacing profiles change across the course of an athlete's career.
本研究分析了短距离皮划艇的配速概况，以便对运动员整个职业生涯中的比赛概况进行分类和比较。我们对500米和1000米比赛的标准化速度数据进行功能主成分分析，以量化配速。前四个主成分解释了500米比赛中90.77%的变化以及1000米比赛中78.80%的变化。这些主成分随后与独特的配速特征相关联，第一个成分定义为速度下降，第二个成分定义为冲刺。所有其他定义的特征都是这两种特征的变体，即后程冲刺。然后，我们应用隐马尔可夫模型，利用主成分得分，将运动员职业生涯中的每个概况分类为不同类型的比赛概况。该模型包括年龄和赛事类型，并确定了发展路径运动员中速度下降更高的趋势。利用四种不同的比赛概况类型，对四名运动员整个职业生涯中的所有比赛概况进行了分析。研究发现，随着运动员的成熟，其配速概况在整个职业生涯中会发生变化。这些信息为教练、从业者和运动员提供了关于配速概况在运动员职业生涯中如何变化的预期。
