Within-Match Performance Dynamics – Momentary Strength in Handball

Abstract

Handball is an Olympic team sport characterized by changes of ball possession, where teams either play on offense or defense. In this paper, we model momentary strength in handball as scoring probabilities based on a double moving average. In this cross-sectional observational study, the aim was to describe the dynamics of momentary strength in handball from both theoretical and practical perspectives. Momentary strength can be used to further characterize the nuances of the sport by identifying different phases in a match. The momentary strength model was applied to the 2019 International Handball Federation (IHF) Men's World Championship. Ninety-six games were analyzed. The results showed that momentary strength could be used to better understand the dynamic interaction process between two teams. The Spearman correlation between the teams' median momentary strength and their final ranks at the Championship was -0.830. Virtually each team faced phases in its matches with a momentary scoring probability lower than 0.10 and with 4 exceptions also higher than 0.90. Twelve out of the 24 teams showed phases with a momentary scoring probability of exactly 0 as well as exactly 1

Variability in performance indicators of the Netherlands women’s national handball team at the 2019 world championship

“…However, the picture was diff erent when analysing each match individually: main attacks were activated from the right in the preliminary round matches, Netherlands-Serbia and Netherlands-Norway; from the centre in the main round match Netherlands-Denmark and the semi-fi nal Netherlands-Russia; while main attacks were activated from the left in the fi nal Netherlands-Spain. These results prove that each match had its own play dynamics, in line with the fi ndings of Lames (2006) and Russomanno et al (2021).…”

“…Differently, the dynamic approach pays more attention to game context (Prieto, et al, 2015), studying some elements that decisively condition actions such as systems of play (Lozano, Camerino, & Hileno, 2016), players on the court at a particular time (Flores & Anguera, 2018) or the result and playing time. Behaviours of players are also studied in chronological order to ascertain changes in game dynamics during a match (Lames, 2006;Lames & McGarry, 2007;Russomanno, et al, 2021). Research conducted according to the dynamic approach has used different tools: sequential analysis, polar coordinates analysis, probabilistic analysis and even neural networks.…”

Analyzing Handball Techniques Using A Biomechanical Approach: A Systematic Literature Review

“…Due to its comparatively quick mastery based on natural human movements, handball has become very popular very quickly (Śliż et al, 2022). In order to enhance technical processes during games and minimise injuries, the sport mandates that players follow particular physical training regimens depending on their position and level on the pitch (Russomanno et al, 2021). Handball is a dynamic and difficult sport that integrates motor skills, physical conditioning, and strategic decision-making.…”

“…Finding Method (Fathalla et al, 2023) Observasional Study Joint Angle (Müller et al, 2022) Observasional Study Distance traveled, velocity, and changes in direction. (Lijewski et al, 2021) Observasional Study Segmental bioelectrical impedance analysis (SBIA)/Angle (Wilczyński et al, 2022) Non RCT Trial Postural stability and angle (Russomanno et al, 2021) Observasional Study Movement (Guignard et al, 2022) Observasional Study Movement (van den Tillaar et al, 2021) Non RCT Trial Handball throws and predict ball velocity, offering a practical and automated method for quantifying throw counts and classifying approach and throw types. (Sánchez-Sáez et al, 2021) Observasional Study Movement patterns and physical demands during an official competition.…”

Analysis of Spatial Offensive Performance in Handball: Differences between Men's and Women's Senior World Championships

“…In handball, for example, numerous variables have been used in different studies aimed at determining performance indicators that influence the final results of competitions ( Antúnez et al, 2013 ; Gómez et al, 2014 ; Skarbalius et al, 2013 ; Vuleta et al, 2012 ). It should be stressed that the identification of these performance indicators in team sports is quite complex because of the speed of the game, constant changes of ball possession and phases of the game, the oppositional component and the difficulty of measuring the heterogeneity of elements that interact to achieve sporting success ( Blecharz et al, 2022 ; Daza et al, 2017 ; Krawczyk, 2020 ; Milanović et al, 2018 ; Russomanno et al, 2021 ).…”