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Analyzing defenses in team sports is generally challenging because of thelimited event data. Researchers have previously proposed methods to evaluatefootball team defense by predicting the events of ball gain and being attackedusing locations of all players and the ball. However, they did not consider theimportance of the events, assumed the perfect observation of all 22 players,and did not fully investigated the influence of the diversity (e.g.,nationality and sex). Here, we propose a generalized valuation method ofdefensive teams by score-scaling the predicted probabilities of the events.Using the open-source location data of all players in broadcast video frames infootball games of men's Euro 2020 and women's Euro 2022, we investigated theeffect of the number of players on the prediction and validated our approach byanalyzing the games. Results show that for the predictions of being attacked,scoring, and conceding, all players' information was not necessary, while thatof ball gain required information on three to four offensive and defensiveplayers. With game analyses we explained the excellence in defense of finalistteams in Euro 2020. Our approach might be applicable to location data frombroadcast video frames in football games.

Location analysis of players in UEFA EURO 2020 and 2022 using generalized valuation of defense by estimating probabilities