A Feature-Weighting Approach Using Metaheuristic Algorithms to Evaluate the Performance of Handball Goalkeepers

Abstract

Handball experts agree that the most crucial position in a handball match is that of the goalkeeper. Their performance can be a good predictor of a team’s ranking in tournaments. Despite this, few studies have been conducted on the relevance of every elite goalkeeper’s action to their performance in the match. This paper provides the features or criteria for objectively evaluating a handball goalkeeper based on their actions during a match. For this purpose, the feature-weighting problem is formulated as an optimization problem. The problem is solved using eight metaheuristic algorithms to adjust the weights of the features. Computer experiments using real data from the 2020 Women’s and Men’s European Handball Championships are carried out with these algorithms. The algorithms optimize the weights based on three metrics. The first metric is to identify the best goalkeeper; the second metric is to identify the top five goalkeepers, regardless of order; and the third metric is to identify and order the top five goalkeepers. A case study is carried out with real data from the 2021 Women’s and Men’s World Handball Championships, where the best goalkeeper found in both cases with the optimized weights coincide with the best goalkeeper chosen by the International Handball Federation (IHF). Finally, the paper shows the particularities and specific difficulties involved in evaluating handball goalkeepers.

Keywords

• Metaheuristic algorithms
• evaluating handball goalkeepers
• player performance evaluation
• feature weighting