Development of 1500m Pacing Behavior in Junior Speed Skaters: A Longitudinal Study.

Providing insight in the development of pacing behavior in junior speed skaters and analyse possible differences between elite, sub-elite, and non-elite juniors.1500m season best times (SBT) and corresponding pacing behavior were obtained longitudinally for 104 Dutch male speed skaters at age 13-14(U15), 15-16(U17), and 17-18(U19) years. Based on their U19 SBT, skaters were divided into elite(n=17), sub-elite(n=64), and non-elite(n=23) groups. Pacing behavior was analysed using the 0-300m, 300-700m, 700-1100m and 1100-1500m times, expressed as a percentage of final time. Mixed analyses of variance were used for statistical analyses.With age, pacing behavior generally developed towards a slower 0-300m and 1100-1500m and a faster mid-section relative to final time. While being faster on all sections, the elite were relatively slower on 0-300m (22.1±0.27%) than the sub-elite and non-elite (21.5±0.44%)(p<0.01), but relatively faster on 300-700m (24.6±0.30%) than the non-elite (24.9±0.58%)(p=0.002). On 700-1100m, the elite and sub-elite (26.2±0.25%) were relatively faster than the non-elite (26.5±0.41%)(p=0.008). Differences in the development of pacing behavior were found from U17-U19 with relative 700-1100m times decreasing for the elite and sub-elite (26.2±0.31% to 26.1±0.27%), but increasing for the non-elite (26.3±0.29% to 26.5±0.41%)(p=0.014).Maintaining high speed into 700-1100m, accompanied by a relatively slower start, appears crucial for high performance on the 1500m speed skating. Generally, juniors develop towards this profile, with a more pronounced development towards a relative faster 700-1100m from U17-U19 for elite junior speed skaters. The results of the present study indicate the relevance of pacing behavior for talent development

Predicting the Personal-Best Times of Speed Skaters Using Case-Based Reasoning

Speed skating is a form of ice skating in which the skaters race each other over a variety of standardised distances. Races take place on specialised ice-rinks and the type of track and ice conditions can have a significant impact on race-times. As race distances increase, pacing also plays an important role. In this paper we seek to extend recent work on the application of case-based reasoning to marathon-time prediction by predicting race-times for speed skaters. In particular, we propose and evaluate a number of case-based reasoning variants based on different case and feature representations to generate track-specific race predictions. We show it is possible to improve upon state-of-the-art prediction accuracy by harnessing richer case representations using shorter races and track-adjusted finish and lap-times.</p