Optimizing Soccer Strategies: A Statistical Approach to Analyzing Goal Differences

Analyzing features contributing to sports match outcomes isa challenging yet fascinating task. Identifying suitableplaying styles that influence the final score of a soccermatch is pivotal for tailoring training processes towardsspecific objectives. This article employs a model based onthe Skellam distribution to forecast the goal differencebetween two teams, accounting for each team’s quality level.The dataset comprises match records from the ۲۰۲۱-۲۲ and۲۰۲۲-۲۳ seasons of the Italian Serie A league. The resultsreveal that certain factors exert positive or negative effectson augmenting a team’s goal difference in various scenarios.This research provides valuable insights for coaches andsports analysts to understand which aspects of a team’sperformance necessitate improvement and align with theteams’ qualities and preferred playing styles

کلیدواژه ها:

skellam distribution ، sports analytics ، soccer strategies ، machine learning