The success of a football team depends on various individual skills and performances of the selected players as well as how cohesively they perform. We propose a two-stage process for selecting optimal playing eleven of a football team from its pool of available players. In the first stage a LASSO-induced modified multinomial logistic regression model is derived to analyse the probabilities of the three possible outcomes. The model considers strengths of the players in the team as well as those of the opponent, home advantage, and also the effects of individual players and player combinations beyond the recorded performances of these players. In the second stage, a GRASP-type meta-heuristic is implemented for the team selection which maximises its probability of winning. The work is illustrated with English Premier League data from 2008/09 to 2015/16. The application demonstrates that the model in the first stage furnishes valuable insights about the deciding factors for different teams whereas the optimisation steps can be effectively used to determine the best possible starting lineup under various circumstances. We propose a measure of efficiency in team selection by the team management and analyse the performance of the teams on this front.

翻译：足球团队的成功取决于所选球员的各项个人技能与表现，以及他们协同作战的默契程度。我们提出一个两阶段流程，用于从球队现有球员池中选出最优的十一人首发阵容。第一阶段推导出一个基于LASSO的修正多项逻辑回归模型，用以分析三种可能比赛结果的概率。该模型综合考虑了本队球员实力、对手实力、主场优势，以及超出球员已记录表现的个人效应与组合效应。第二阶段采用GRASP型元启发式算法进行阵容选择，以最大化球队获胜概率。本研究基于2008/09赛季至2015/16赛季的英格兰超级联赛数据进行实证分析。应用结果表明，第一阶段模型能够为不同球队的决胜因素提供有价值的洞察，而优化步骤可有效用于确定各种情境下的最佳首发阵容。我们提出衡量球队管理层阵容选择效率的指标，并据此分析了各球队的表现。