This study aimed to explore factors associated with medalling in Para judo at the Tokyo 2020 Paralympic Games, focusing on athlete characteristics and technical-tactical variables. Using published competition results, medalling outcomes for men and women were separately modelled using Bayesian penalised regression. Models included age, body weight, sport class, throws, groundwork techniques, and penalties per match. Results are reported as posterior probabilities that the regression coefficient was greater or less than zero, Pr(β > 0) or Pr(β < 0), according to the direction of the posterior mean. In males, age showed a predominantly negative posterior distribution (Pr[β < 0] = .944), whereas body weight (Pr[β > 0] = .972), throws (Pr[β > 0] >.999), groundwork techniques (Pr[β > 0] >.999), and penalties (Pr[β > 0] = .962) showed predominantly positive posterior distributions. In females, throws and groundwork techniques showed positive associations with medalling (both Pr[β > 0] >.999), whereas age (Pr[β < 0] = .818) and penalties (Pr[β < 0] = .801) showed predominantly negative posterior distributions with greater uncertainty. Overall, throws and groundwork techniques showed the most consistent positive associations with medalling across both sex-specific models. These findings may inform technical-tactical priorities and long-term athlete development in Para judo.
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Kons et al. (2026) studied this question.
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