evelopment and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai

Abstract

Performance analysis based on artificial intelligence together with game-related statistical models aims to provide relevant information before, during and after a competition. Due to the evaluation of handball performance focusing mainly on the result and not on the analysis of the dynamics of the game pace through artificial intelligence, the aim of this study was to design and validate a specific handball instrument based on real-time observational methodology capable of identifying, quantifying, classifying and relating individual and collective tactical behaviours during the game. First, an instrument validation by an expert panel was performed. Ten experts answered a questionnaire regarding the relevance and appropriateness of each variable presented. Subsequently, data were validated by two observers (1.5 and 2 years of handball observational analysis experience) recruited to analyse a Champions League match. Instrument validity showed a high accordance degree among experts (Cohen’s kappa index (k) = 0.889). For both automatic and manual variables, a very good intra- ((automatic: Cronbach’s alpha (_) = 0.984; intra-class correlation coefficient (ICC) = 0.970; k = 0.917) (manual: _ = 0.959; ICC = 0.923; k = 0.858)) and inter-observer ((automatic: _ = 0.976; ICC = 0.961; k = 0.874) (manual: _ = 0.959; ICC = 0.923; k = 0.831) consistency and reliability was found. These results show a high degree of instrument validity, reliability and accuracy providing handball coaches, analysts, and researchers a novel tool to improve handball performance.