A Pattern Recognition and Performance Index Evaluation Model of Football Team based on Principal Component Analysis and PageRank Algorithm

Abstract

With \u00a0the \u00a0increasing \u00a0knowledge \u00a0integration \u00a0and \u00a0task \u00a0complexity, \u00a0individual \u00a0ability \u00a0demands \u00a0a highly cohesive interdisciplinary team to amplify. To study the elements of successful team cooperation and explore valuable team strategies, this paper present a network pattern recognition model based on PageRank algorithm \u00a0and principal component analysis \u00a0method. Further, a team \u00a0cooperation performance \u00a0model based on \u00a0group \u00a0dynamic \u00a0theory \u00a0is \u00a0built \u00a0to \u00a0capture \u00a0the \u00a0individual \u00a0contribution \u00a0and \u00a0teamwork \u00a0characteristic \u00a0as \u00a0a supplementary evaluation. By applying the model into football competition, we found our model has 73.68% accuracy, \u00a0proving its outstanding adaptability. Based \u00a0on the \u00a0model, \u00a0we \u00a0can \u00a0get the information of the inner network \u00a0structure \u00a0of \u00a0a \u00a0team, \u00a0know \u00a0the \u00a0most \u00a0significant \u00a0contributors \u00a0pertinent \u00a0with \u00a0team \u00a0success, \u00a0and \u00a0make further justification plans and suggestions to achieve teamwork improvement.