Degree distribution of position-dependent ball-passing networks in football games

TL;DR

This paper introduces a stochastic model for football passing networks based on players' positions and intrinsic fitness, successfully matching real data and providing insights into game dynamics.

Contribution

The paper presents a novel position-dependent ball-passing network model with an explicit degree distribution derivation, aligning well with empirical data.

Findings

Derived degree distribution matches real football passing data

Model captures position-dependent passing behavior

Provides a quantitative framework for analyzing football networks

Abstract

We propose a simple stochastic model describing the position-dependent ball-passing network in football games. In this network, a player on a certain area in the divided fields is a node, and a pass between two nodes corresponds to an edge. Our model is characterized by the consecutive choice of a node dependent on its intrinsic fitness. We derive the explicit expression of the degree distribution, and find that the derived distribution reproduces the real data quit well.