  Analyzing defenses in team sports is generally challenging because of the
limited event data. Researchers have previously proposed methods to evaluate
football team defense by predicting the events of ball gain and being attacked
using locations of all players and the ball. However, they did not consider the
importance 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 of
defensive teams by score-scaling the predicted probabilities of the events.
Using the open-source location data of all players in broadcast video frames in
football games of men's Euro 2020 and women's Euro 2022, we investigated the
effect of the number of players on the prediction and validated our approach by
analyzing the games. Results show that for the predictions of being attacked,
scoring, and conceding, all players' information was not necessary, while that
of ball gain required information on three to four offensive and defensive
players. With game analyses we explained the excellence in defense of finalist
teams in Euro 2020. Our approach might be applicable to location data from
broadcast video frames in football games.
