Lamas Leonardo, Drezner Rene, Otranto Guilherme, Barrera Junior
Faculty of Physical Education, University of Brasilia, Brasilia, Federal District, Brazil.
School of Physical Education and Sport, University of São Paulo, São Paulo, São Paulo, Brazil.
PLoS One. 2018 Feb 6;13(2):e0191431. doi: 10.1371/journal.pone.0191431. eCollection 2018.
The aim of this study was to define a method for evaluating a player's decisions during a game based on the success probability of his actions and for analyzing the player strategy inferred from game actions. There were developed formal definitions of i) the stochastic process of player decisions in game situations and ii) the inference process of player strategy based on his game decisions. The method was applied to the context of soccer goalkeepers. A model of goalkeeper positioning, with geometric parameters and solutions to optimize his position based on the ball position and trajectory, was developed. The model was tested with a sample of 65 professional goalkeepers (28.8 ± 4.1 years old) playing for their national teams in 2010 and 2014 World Cups. The goalkeeper's decisions were compared to decisions from a large dataset of other goalkeepers, defining the probability of success in each game circumstance. There were assessed i) performance in a defined set of classes of game plays; ii) entropy of goalkeepers' decisions; and iii) the effect of goalkeepers' positioning updates on the outcome (save or goal). Goalkeepers' decisions were similar to the ones with the lowest probability of goal on the dataset. Goalkeepers' entropy varied between 24% and 71% of the maximum possible entropy. Positioning dynamics in the instants that preceded the shot indicated that, in goals and saves, goalkeepers optimized their position before the shot in 21.87% and 83.33% of the situations, respectively. These results validate a method to discriminate successful performance. In conclusion, this method enables a more precise assessment of a player's decision-making ability by consulting a representative dataset of equivalent actions to define the probability of his success. Therefore, it supports the evaluation of the player's decision separately from his technical skill execution, which overcomes the scientific challenge of discriminating the evaluation of a player's decision performance from the action result.
本研究的目的是定义一种基于球员行动成功概率来评估其在比赛中决策的方法，并分析从比赛行动中推断出的球员策略。开发了以下正式定义：i）比赛情境中球员决策的随机过程；ii）基于球员比赛决策的策略推断过程。该方法应用于足球守门员的情境。开发了一个守门员定位模型，该模型具有几何参数以及根据球的位置和轨迹优化其位置的解决方案。该模型在65名职业守门员（年龄28.8±4.1岁）的样本上进行了测试，这些守门员在2010年和2014年世界杯上代表各自国家队参赛。将守门员的决策与来自其他守门员的大型数据集的决策进行比较，确定每种比赛情况下的成功概率。评估了：i）在一组定义的比赛类型中的表现；ii）守门员决策的熵；iii）守门员定位更新对结果（扑救或进球）的影响。守门员的决策与数据集中进球概率最低的决策相似。守门员的熵在最大可能熵的24%至71%之间变化。射门之前瞬间的定位动态表明，在进球和扑救情况中，守门员分别在21.87%和83.33%的情况下在射门之前优化了他们的位置。这些结果验证了一种区分成功表现的方法。总之，该方法通过参考等效行动的代表性数据集来定义球员成功的概率，从而能够更精确地评估球员的决策能力。因此，它支持将球员的决策评估与他的技术技能执行分开，这克服了将球员决策表现评估与行动结果区分开来的科学挑战。
