Skill importance in women’s soccer

Abstract

Soccer analytics often follow one of two approaches: 1) regression models on number of shots taken or goals scored to predict match winners, or 2) spatial and/or temporal analysis of plays for evaluation of strategy. We propose a new model to evaluate skill importance in soccer. Play by play data were collected on 22 NCAA Division I Women's Soccer matches with a new skill notation system. Using a Bayesian approach, we model play sequences as discrete absorbing Markov chains. Using posterior distributions, we estimate the probability of 35 distinct offensive skills leading to a shot during a single possession.

Strategy Optimization in Sports via Markov Decision Problems

“…The calculated winning probabilities and set durations were close to real data estimates. A similar MC approach as in [13] has been used by Heiner et al [7] for women's soccer.…”

Position importance in NCAA football

“…Page et al (2007) rated every position in the National Basketball Association (NBA) based on the effect they had on the point margin at the end of the game. There is a relatively large literature on skill importance (Florence, et al 2008;Heiner, et al 2014;Miskin, et al 2010;Thomas, et al 2009) that leads naturally to a consideration of position importance. Conversely, once position importance is explored in football, a natural extension is to consider various football skills and their importance, which would lead to a more efficient partitioning of practice time.…”

No-gi Brazilian jiu-jitsu: A Markovian analysis of elite-level combat dynamics

“…9 Indeed, these studies are in line with previous studies in which Markovian analysis has been applied to assess tactical dynamics in opposition sports. 6,10,11 The Bayesian approach to analysis enables the use of posterior distributions to perform both estimation and probabilistic assessment of hypotheses relating distinct events to possible outcomes in no-gi BJJ (NGJJ). Practical advantages of the Bayesian paradigm have been advocated for some time, and include the enrichment of statistical models with prior knowledge, allowing the models to make meaningful predictions about data.…”

“…9 Indeed, these studies are in line with previous studies in which Markovian analysis has been applied to assess tactical dynamics in opposition sports. 6,10,11…”