Leveraging Minute-by-Minute Soccer Match Data to Adjust Team Offensive Performance for Game Context

Music City Center 

In soccer, game context can skew offensive statistics, potentially misrepresenting a team's performance. For example, the score often dictates tactical decisions (e.g., teams may adopt a more defensive approach when leading to limit the opponent's scoring opportunities). Additionally, extenuating circumstances such as red cards can disrupt the balance of play. We analyze minute-by-minute event-sequenced match data from 15 seasons across five major European leagues to examine how game context influences offensive performance in various statistical categories, including shot attempts, corner kicks, shots on goal, and expected goals (xG). Our analysis incorporates Generalized Additive Modeling (GAM) techniques with explanatory variables such as score differential, red card differential, home/away status, prematch win probabilities, and game minute. The chosen model is applied to project offensive numerical outputs onto a "common denominator" scenario: a tied home game played at even strength. This approach provides a more contextualized evaluation of teams' offensive performances, potentially yielding alternative insights into game dynamics.

Generalized Additive Models

Model Selection

Negative Binomial

Sports Analytics

Zero-Inflated Poisson 

Section on Statistics in Sports