Author(s): DUAN, Y., YUAN, T., WEI, P., HU, B., GUO, Q., Institution: CHINA INSTITUTION OF SPORT SCIENCE, Country: CHINA, Abstract-ID: 1775

INTRODUCTION:
Pacing strategy is a key determinant of performance in endurance sports. However, in race walking, systematic evidence regarding distinct pacing strategy types and their relationship with competitive outcomes remains limited. This study aimed to identify typical pacing strategy profiles in elite women’s 20 km race walking and to examine their predictive value for top-level performance.
METHODS:
Publicly available split-time data from the women’s 20 km race walking events at the Olympic Games and World Athletics Championships between 2019 and 2025 were collected. Athletes with complete 1-km split data across the 20 km distance and valid finishing results were included (n = 237). For each athlete, pacing curves were standardized using within-subject Z-score normalization across the 20 splits. K-means cluster analysis (k = 4) was applied to identify pacing strategy profiles. Differences in finishing positions among pacing types were assessed using the Kruskal–Wallis test. Univariable and multivariable logistic regression analyses were conducted to evaluate the probability of finishing in the top 8, with competition type (Olympic Games vs. World Championships) included as a covariate.
RESULTS:
Four distinct pacing strategy profiles were identified:(1) Progressive reverse J-shaped strategy, characterized by a conservative start, stable mid-race pace, and pronounced end spurt;(2) Positive-split conservative strategy, marked by a relatively fast early pace followed by a substantial decline;(3) Mid-race surge parabolic strategy, showing an increase in speed during the middle phase with subsequent fatigue;(4) High-risk fast-start strategy, characterized by an aggressively fast opening pace followed by a marked slowdown and limited finishing acceleration.
Significant differences in finishing positions were observed among pacing strategies (p < 0.001). The progressive reverse J-shaped strategy demonstrated the best competitive outcomes (median finishing position = 5; 69% of athletes finished within the top 8). Logistic regression analysis revealed that, compared with the positive-split conservative strategy, the progressive reverse J-shaped strategy was associated with a substantially higher likelihood of finishing in the top 8 (OR = 56.53, 95% CI: 17.05–187.41, p < 0.001), and this association remained significant after adjusting for competition type.
CONCLUSION:
Distinct pacing strategy profiles exist in elite women’s 20 km race walking, and these profiles are strongly associated with competitive performance. A progressive reverse J-shaped pacing strategy significantly increases the probability of achieving top-level results, and this advantage remains stable across different world-class competitive contexts.