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量化玩家对反击的贡献

 

在vip威尼斯登录入口的客座博客, Laurynas Raudonius presents his findings from a research project which applied tracking and event data with the objective of quantifying each individual player’s contribution to a team’s counter attacks.

 

: Laurynas Raudonius

Laurynas Raudonius是该博士的首届获奖者. 加里Gelade奖, 它认可数据执行的本科生提交的优秀提案 专业论坛.

获奖后, Laurynas在2021年的虚拟活动上展示了海报演示, which illustrated the findings of a project which applied spatio-temporal data to quantify how individual players contribute to a team’s successful counter attack, 使用Voronoi细胞和其他方法.

点击这里查看他的海报.

评估反击时消除主观性

Why is it important to be able to objectively quantify each player’s contribution to a counter attack?

一个好的开始就是挑战自己, 用你的肉眼, to identify and award player scores to the most important contributions from a single isolated counter attacking scenario.

当你观看下面的视频时, 考虑哪些玩家的贡献是最具影响力的, 为什么.

看了这段视频后, I am sure you will now appreciate the challenge of objectively assigning numerical values to actions performed by footballers. 毫无疑问,这是足球分析的巨大挑战之一.

The benefits of creating a model to achieve that are obvious – having an unbiased comparison of any two players can help enormously in scouting, 球队选拔和足球的许多其他领域.

My model combines four metrics that are calculated using tracking and event data and applies them to place a value on player contributions to counter attacks. Whilst there are many existing football-related studies which focus on attributing value to passes, this model takes things a step further and values all actions by combining them into contributions. 有些类似的模型已经开发出来了, 但它们被训练成机器学习模型,没有包含许多单独的指标.

此外, 这个项目的重点是反击, a subset of attacking scenarios that have received very little attention to date from data scientists and researchers.

定义一个贡献

The model used in this project does not differentiate between different types of attacking actions made by players, 而是把它们全部组合成贡献. A contribution is essentially a pair of in-game possession states (the position of all the players and the ball on the pitch at a moment in time), starting firstly with the moment when a player first touches the ball and secondly the moment a team mate subsequently touches the ball (and, 反过来, 开始他们自己的贡献). The difference between these two in-game possession states answer the question ‘how did a player impact the situation whilst on the ball?’

获得一个贡献的精确分数

The difference between the two possession states won’t tell us a great deal unless we have a way of objectively assigning numerical values to them. 对于这个, 四个指标, 来自跟踪和事件数据, 已设计和实现:

1. 距离

这是四个度量中最直观的. 很明显,如果一个球员从, 例如, 他们自己的第三个对手的禁区, 他们在很大程度上增加了这次袭击的危险性. 因此,他们的贡献应具有很高的价值. 为了准确地测量, the model calculates the Euclidean distance between the ball and the goal when a player first obtains the ball and the same distance when they finish their action (i.e. 尝试通过). The difference between the two tells us how much closer the ball is to the goal as a result of the player’s involvement and therefore is the value of the indicator. Negative values can also be assigned as it is possible that a player can take the ball further away from goal.

2. 危险

建立在距离度量的基础上, vip威尼斯登录入口可以解释球在球场上的确切位置是跟随球员的行动, 而不仅仅是离目标有多远.

评估危险, 球场的不同区域, 丹尼尔·林克等人已经深入研究过这个话题吗. 在他们vip威尼斯登录入口足球进攻中的危险的研究中. Their research proposes to divide the attacking third into 2×2 meter squares and then assign a danger score between 0 and 1 to each square (see Figure 1 below).

为了计算出确切的数值,他们遵循以下五个关键规则:

a)随着与目标的距离减小,中心度增加,危险增加.

b) Moving into the penalty area brings about a sudden increase in the danger because of the risk of the defensive team conceding a penalty kick.

c)在球门前有一个同质区域,在该区域内危险不会进一步增加.

d)与目标的锐角可以减少危险.

e) Areas to the side of the penalty area are dangerous because of the possibility of a cross with little risk of offside.

3. 大玩家

而距离和危险指标则具有丰富的信息, 他们基本上只是基于球的位置.

如果一名球员在中线有一条明确的进球路线会怎么样? 仅基于前两个指标, 这个球员的贡献将会得到极大的重视, 尽管他们几乎没有受到对手球员的压力. 因此,重要的是要考虑, 当评估玩家行动时, 他们如何影响对手的防守.

这正是第三个指标所衡量的. 更具体地说, 它可以计算出在球员动作过程中有多少对手球员在球后. Since goalkeepers stay behind the ball most of the time, they are not accounted for in this metric.

4. 空间控制

A study has explored the relationship between a team’s success and how much space they controlled in the opponent’s half, 离球门30米. 研究发现,两者之间存在某种程度的直接关联:许多成功的团队, 比如巴塞罗那和多特蒙德, 在对手的半场控制较大的空间, so it only makes sense to award a higher valuation to players whose contributions increase the controlled space.

对于这个项目,使用Voronoi单元来测量控制空间. 一个球员的Voronoi单元是指他在球场上比其他任何球员都更接近的点集合.

计算整个场地的空间并不能提供足够的信息, because a player who increases the space in their own half does not necessarily contribute to a counter attack. 因此选择了基音上的阈值(区域), 确定何时对空间进行控制.

Experimentation with different areas in front of the goal indicated that if controlled space is measured within the final quarter of the pitch only, 那么所有玩家在空间控制上的差异就会更大, 这让vip威尼斯登录入口能够更好地区分玩家贡献的重要性. 因此,这在模型中被设置为一个阈值.

结合指标

In order to produce a single score per player contribution, the four indicators have been combined. 第一步是将它们归一化到相同的范围内:这里选择了[-1;1]. 然后把捐款的分数加起来乘以2.5,使可得的分数在-10到10之间. 这将导致vip威尼斯登录入口最终的分数分配给一个贡献.

应用程序

在建立了方法论之后, we now need to demonstrate how the model can be applied to an arbitrary passage of play in a match.

如果一篇文章相对简单(如 加雷斯·贝尔在2014年国王杯的反攻中攻入制胜一球)分配贡献分数的挑战相当简单, 但是当每一个新玩家加入游戏时,游戏便会变得更加困难.

这个模型能够解决那个问题.

vip威尼斯登录入口回到这篇文章开始时展示的视频例子. 在这个新版本的视频里, vip威尼斯登录入口在每个贡献的结尾暂停镜头,并显示模型如何评估它.

The bar chart below summarises the values that were assigned to contributions during this counter attack.

When you initially considered what player contributions were the most impactful in this specific counter attack, 如果知道您的值是否与由该模型导出的值相似,那将是很有趣的.

既然我已经向你们解释了我的方法, 为了好玩,让vip威尼斯登录入口再做一次同样的练习,但是这次, 当你为每个贡献分配分数时,试着考虑这四个指标.

一旦你看了这个视频, click on the video below to see the contribution values attributed by the model and compare them to your own.

同样,下面的条形图总结了每个反击的价值.

在这个例子中,玩家6的贡献是值得强调的. 根据该模型,他的贡献最大,总分接近5分. 然而,当我在Pro论坛上向代表们展示这段视频时, 人们倾向于认为玩家8或9的贡献最大. This reinforces the subjectivity of trying to quantify a player’s contribution to counter attacking phases using just the naked eye.

It also further highlights the potential of this type of research to try and reduce bias when assessing recurring match scenarios, 哪些可以潜在地增强匹配分析的过程和通知招聘档案.



参考文献

塔瓦雷斯,里卡多. (2019). 在足球中使用Voronoi图.

链接,维.,郎朗年代., Seidenschwarz P. 2016. 基于时空跟踪数据的足球危险性实时量化研究.

控制,R.拉伯维.,以及Memmert D. (2017). “哪个通过更好。?“评估精英足球传球效率的新方法. 人体运动科学55.

Perl, J. & Memmert D. (2017). A Pilot Study on Offensive Success in Soccer Based on Space and Ball Control – Key Performance Indicators and Key to Understand Game Dynamics.


来自立陶宛, Laurynas Raudonius graduated in Computer Science at The University of Manchester earlier this year. 现总部位于瑞士, 他曾担任立陶宛顶级联赛kuno Žalgiris的比赛分析师.