Advancing sports analytics through AI research
Advancing sports analytics through AI research
“Game theory plays an important role in the study of sports, enabling theoretical grounding of players’ behavioral strategies. In the case of football, many of its scenarios can actually be modeled as zero-sum games, which have been studied extensively since the inception of game theory. For example, here we model the penalty kick situation as a two-player asymmetric game, where the kicker’s strategies may be neatly categorised as left, center, or right shots. To study this problem, we augment game-theoretic analysis in the penalty kick scenario with Player Vectors, which summarise the playing styles of individual football players. With such representations of individual players, we are able to group kickers with similar playing styles, and then conduct game-theoretic analysis on the group-level (Figure 3). Our results show that the identified shooting strategies of different groups are statistically distinct. For example, we find that one group prefers to shoot to the left corner of the goal mouth, while another tends to shoot to the left and right corners more evenly. Such insights may help goalkeepers diversify their defense strategies when playing against different types of players. Building on this game-theoretic view, one can consider the durative nature of football by analysing it in the form of temporally-extended games, use this to advise tactics to individual players, or even go further to optimise the overall team strategy…”
Source: deepmind.com/blog/article/advancing-sports-analytics-through-ai