Characterizing multidimensional worst-case scenarios in elite youth basketball: effects of time window and playing position
Yannis Irid, Julian Hutin, Jean-François Toussaint, Adrien Sedeaud · Frontiers in Sports and Active Living · 2026
This study investigated multidimensional worst-case scenarios (WCS) in elite youth male and female basketball players. Data were collected from 31 players (male: n = 20; female: n = 11) competing at the French National Institute of Sport across 40 official matches over two consecutive seasons. Player activity was monitored using a 20-Hz Local Positioning System and 100-Hz embedded accelerometers. For each player, match, and time window (10, 30, 60, and 120 s), eight external load variables were extracted using rolling-window analyses. Variables were subsequently normalized and combined into a composite score, with WCS defined as the rolling window exhibiting the greatest simultaneous accumulation of external load demands. Linear mixed models were used to examine the effects of time window and playing position (frontcourt vs. backcourt) on WCS characteristics. Across both male and female players, shorter time windows consistently produced greater relative physical demands than longer epochs for most variables. However, jumps and changes of direction demonstrated fewer differences across time windows than locomotor variables. Position-specific differences were also observed, particularly among male players, with backcourt players generally exhibiting greater locomotor demands than frontcourt players during WCS. In female players, positional differences were less pronounced and primarily limited to selected acceleration-, deceleration-, and sprint-related variables. These
Findings: suggest that the most physically demanding passages of basketball competition are highly dependent on the temporal scale considered and vary according to playing position. More importantly, the multidimensional WCS approach highlights periods characterized by the greatest concurrent accumulation of external load demands, providing a more holistic representation of match demands than traditional peak-demand analyses. These
findings may assist practitioners in developing more specific training strategies to prepare athletes for the most challenging passages of play encountered during competition.