Tell me the match context, and I’ll tell you how much the team will run, or should have run: an update and divisional extension of a predictive running model for Spanish professional football
Year: 2026
Type: article
Abstract: To update the predictive model of a team's total distance (TotDisTea) proposed by Castellano et al. (2024) for the Spanish First Division (LaLiga1), using five seasons (2021-22 to 2025-26), and to extend it to the Second Division (LaLiga2), from a dual perspective: a retrospective (evaluative) approach to assess performance already produced, and a prospective (predictive) approach usable before a match.Team physical performances from official matches were analysed (LaLiga1: 2,894 team-match records from 1,447 matches; LaLiga2: 3,542 from 1,771), recorded with a multi-camera system.For each division, an all-possible-regressions procedure selected the best linear model for TotDisTea from seven situational predictors: match location, match outcome, team and opponent level, effective-playing-time (EffPlaTim), ball-possession (BalPos) and the opponent's total distance (TotDisOpp).A reduced model excluding TotDisOpp was additionally estimated for prospective use.Models were cross-validated at the match level and fitted with cluster-robust standard errors.In both divisions TotDisOpp was the strongest predictor (b= 0.72 and 0.79).The LaLiga1 model additionally retained team and opponent levels, EffPlaTim and BalPos (R 2 adj= 0.86); the more parsimonious LaLiga2 model retained TotDisOpp, EffPlaTim and BalPos (R 2 adj= 0.85).Match location and match outcome were not selected in either league.The reduced models retained EffPlaTim and BalPos, with lower accuracy (R 2 adj= 0.71 and 0.61).Opponent running is the most stable predictor in both divisions, but the predictive structure is league-specific and coefficients may change over time, warranting periodic updating.The equations let practitioners evaluate a team's response after a match, and enable anticipation beforehand.
Source: Biology of Sport
Language: English
Subfield: Orthopedics and Sports Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $480
OpenAlex ID: W7212272685