Estimation of football players' skills is one of the key tasks in sports
analytics. This paper introduces multiple extensions to a widely used model,
expected possession value (EPV), to address some key challenges such as
selection problem. First, we assign greater weights to events occurring
immediately prior to the shot rather than those preceding them (decay effect).
Second, our model incorporates possession risk more accurately by considering
the decay effect and effective playing time. Third, we integrate the assessment
of individual player ability to win aerial and ground duels. Using the extended
EPV model, we predict this metric for various football players for the upcoming
season, particularly taking into account the strength of their opponents.

估计足球运动员技能是体育分析中的一个关键任务。本文介绍了对广泛使用的期望控球价值模型进行多次扩展，以解决选择问题等关键挑战。首先，我们赋予射门前紧密发生的事件比其之前发生的事件更大的权重（衰减效应）。其次，我们的模型通过考虑衰减效应和有效比赛时间更准确地融入控球风险评估。第三，我们整合了个体球员在空中和地面的交锋中胜利的能力评估。使用扩展的期望控球价值模型，我们预测了即将到来赛季各种足球运动员的这一度量，特别考虑了对手的实力。

足球球员技能估计的控制与对抗动作的预期控制价值

Expected Possession Value of Control and Duel Actions for Soccer  Player's Skills Estimation

Given a monocular video of a soccer match, this paper presents a
computational model to estimate the most feasible pass at any given time. The
method leverages offensive player's orientation (plus their location) and
opponents' spatial configuration to compute the feasibility of pass events
within players of the same team. Orientation data is gathered from body pose
estimations that are properly projected onto the 2D game field; moreover, a
geometrical solution is provided, through the definition of a feasibility
measure, to determine which players are better oriented towards each other.
Once analyzed more than 6000 pass events, results show that, by including
orientation as a feasibility measure, a robust computational model can be
built, reaching more than 0.7 Top-3 accuracy. Finally, the combination of the
orientation feasibility measure with the recently introduced Expected
Possession Value metric is studied; promising results are obtained, thus
showing that existing models can be refined by using orientation as a key
feature. These models could help both coaches and analysts to have a better
understanding of the game and to improve the players' decision-making process.

本文提出了一种计算模型，利用进攻球员的方向和对手的空间配置来计算在同一团队的玩家之间的传球事件的可行性，结果表明通过引入方向作为可行性度量，可以构建一个强健的计算模型，并结合预期控球价值指标，有望改善现有模型，从而更好地帮助教练和分析员了解比赛，提高球员的决策过程。

利用球员身体定向对足球传球可行性建模

Using Player's Body-Orientation to Model Pass Feasibility in Soccer

Basketball games evolve continuously in space and time as players constantly
interact with their teammates, the opposing team, and the ball. However,
current analyses of basketball outcomes rely on discretized summaries of the
game that reduce such interactions to tallies of points, assists, and similar
events. In this paper, we propose a framework for using optical player tracking
data to estimate, in real time, the expected number of points obtained by the
end of a possession. This quantity, called \textit{expected possession value}
(EPV), derives from a stochastic process model for the evolution of a
basketball possession; we model this process at multiple levels of resolution,
differentiating between continuous, infinitesimal movements of players, and
discrete events such as shot attempts and turnovers. Transition kernels are
estimated using hierarchical spatiotemporal models that share information
across players while remaining computationally tractable on very large data
sets. In addition to estimating EPV, these models reveal novel insights on
players' decision-making tendencies as a function of their spatial strategy.

本文提出了一种框架，利用运动员运动跟踪数据实时估计篮球进攻结束时实现预期得分数量，并通过分层时空模型估计转换核函数，以分享跨运动员的信息。