Non-linear trends using the generalized additive models in physical and technical performances of the Chinese Super League players.

This study aimed to investigate the non-linear evolution of position-specific physical and technical performance indicators across different tactical formations in the Chinese Super League (CSL) from the 2015 to the 2021 seasons. Match data were collected from 800 games played in six common formations (3-5-2, 4-3-3, 4-2-3-1, 4-4-2, 3-4-3, and 4-1-4-1). Players were classified into five positions: central defenders (CD; match observations = 2,219), fullbacks (FB; match observations = 2,060), central midfielders (CM; match observations = 2,786), wide midfielders (WM; match observations = 1,587), and forwards (FW; match observations = 1,680).

The influence of tactical formation on physical and technical performance across playing positions in the Chinese super league.

This study aimed to investigate the impact of tactical formations on the physical and technical performance of professional football players in the Chinese Super League (CSL). A sample of 800 games from the 2015-2021 CSL was analyzed, and players' physical (total distance covered, distance covered while ball in play, number of sprints, sprint distance, and high/middle/low-speed running) and technical (gain/loss of possession, ball retention percentage, challenges, challenge success percentage, passes, and pass success percentage) performance was assessed across six team formations: 3-5-2 (n = 137), 4-3-3 (n = 77), 4-2-3-1 (n = 391), 4-4-2 (n = 257), 3-4-3 (n = 41), and 4-1-4-1 (n = 107). Linear mixed models were used to assess variations in performance indicators across positions and formations.

An analysis of financial risk assessment of globally listed football clubs.

The global football market has grown in the past three decades, and football clubs' sustainable financial operations have gradually gained attention. This study aims to construct a financial risk assessment model applicable to the football industry, explore globally listed football clubs' overall financial operating characteristics, and analyse the leading causes of the club's financial crisis. We selected a sample of 24 currently listed football clubs worldwide and an exploratory factor analysis (EFA) model to construct the model of financial risk assessment for football clubs.