Purpose: The professional football competitions can be regarded as a highly dynamic and complex systems in which working groups try to keep the stability of their team performance (Vllar, Araujo et al. .2012, Liu, Gomez et al. .2016). In order to explore the team performance trends and styles of play, this study alms to identify the team`s performance variation according to teams` ranking in the Chinese Football Association Super League. Methods: A total number of 1440 matches of season 2012-2017 from the Chinese Football Association Super League were analysed. The statistics were collected by a multiple camera semi-automatic computerised player tracking system (AMISCO. Nice, France). All the teams were divided into four tiers according to their rankings: tier 1 (1-4). tier 2 (5-8). tier3 (9-12). tier 4 (13-16). Also, match location (home and away) was considered within the analysis. The team performance variation was expressed by the coefficient of vanatlon (CV). Meanwhile, general linear model and MANOVA were adapted to investigate the difference between groups. Results: The results showed that the CV of several attacking-related actions changed significantly according to match location for Possession in opponent half (0.138 vs. 0.151). Passes (0.207 vs. 0.224) and Opponent penalty area entries (0.457 vs. 0.505). Regarding physical performance in relation to match location. SDIP (Sprinting distance In ball possession) (0.239 vs. 0.261) and HSD (High-speed running dlstance)(0.151 vs. 0.168) were observed having variability. It also showed that the main variations of pass accuracy were tier-1 vs. tier-4 (0.059 vs. 0.07). tier-2 vs. tier-4 (0.058 vs. 0.07). The discrepancy of OffSide was significant between tier-1 and tier-4 (0.667 vs. 0.784). The results of multivariate tests within 4 tiers of team performance between home and away showed that the observed differences in variation were trivial. Conclusions: The results showed that possession in opponent half, passes, opponent penalty area entries. SDIP and HSD had high variablllty under the influence of match location. Moreover, the variation trends among tiers mainly come from the discrepancies between tier-1. tier-2 and tier-4. The findings may contribute to the further investigation into the variation in teams` performance, considering more contextual variables.
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