Worst-case scenario analysis of physical demands in elite men handball players by playing position through big data analytics.

The physical demands of intermittent sports require a preparation based, by definition, on high-intensity actions and variable recovery periods. Innovative local positioning systems make it possible to track players during matches and collect their distance, speed, and acceleration data. The purpose of this study was to describe the worst-case scenarios of high-performance handball players within 5-minute periods and per playing position. The sample was composed of 180 players (27 goalkeepers, 44 wings, 56 backs, 23 centre backs and 30 line players) belonging to the first eight highest ranked teams participating in the European Men's Handball Championship held in January 2022. They were followed during the 28 matches they played through a local positioning system worn on their upper bodies. Total and high-speed distance covered (m), pace (m/min), player load (a.u.) and high-intensity accelerations and decelerations (n) were recorded for the twelve 5-min periods of each match. Data on full-time player average and peak demands were included in the analysis according to each playing position. A systematic three-phase analysis process was designed: 1) information capture of match activities and context through sensor networks, the LPS system, and WebScraping techniques; 2) information processing based on big data analytics; 3) extraction of results based on a descriptive analytics approach. The descriptive cross-sectional study of worst-case scenarios revealed an ~17% increment in total distance covered and pace, with a distinct ~51% spike in high-intensity actions. Significant differences between playing positions were found, with effect sizes ranging from moderate to very large (0.7-5.1). Line players, in particular, showed a lower running pace peak (~10 m/min) and wings ran longer distances at high speed (> 4.4 m/s) than the rest of the field players (~76 m). The worst-case scenario assessment of handball player locomotion demands will help handball coaches and physical trainers to design tasks that replicate these crucial match moments, thus improving performance based on a position-specific approach.

Time-Motion Analysis by Playing Positions of Male Handball Players during the European Championship 2020.

The aim of this study was to analyze time-motion characteristics of elite male handball players during the last European Championship 2020. A total of 414 players from 24 national teams were analyzed during 65 matches using a local positioning system (LPS) for the first time in a European Championship. Players (n = 1865) covered significantly (p < 0.001; ES = 0.48) more total distance in offense (1217.48 ± 699.33 m) and in all locomotion categories (p < 0.001) than in defense (900.96 ± 538.95 m), with a similar average total time on court (13.40 ± 8.19 min in offense and 13.27 ± 8.59 min; p > 0.05). The running pace was significantly higher in offense 96.53 ± 22.57 m/min than in defense 82.72 ± 43.28 m/min (p < 0.001; ES = 0.47). By playing positions, the Left Wing players covered significantly (p < 0.001) higher distances (2547.14 ± 1309.52) and showed longer playing time (32.08 ± 17.01). Center Back was the playing position that showed the highest global running pace (98.34 m/min). Players with higher running pace in offense (p < 0.001) were Left Backs (105.95 ± 25.20) and the Center Backs in defense (95.76 ± 48.90). There were no significant differences between winners and losers or between top ranked and lower ranked teams in terms of time played, distance covered, and running pace. Specific physical conditioning is necessary to maximize performance and minimize fatigue when performing in long tournaments.

High-Performance Handball Player's Time-Motion Analysis by Playing Positions.

The purpose of this study was to analyze the on-court demands of handball players during the European Handball Federation Champions League Final Four (VELUX EHF FINAL4) 2019 to define time-motion characteristics (played time; covered distances) both in offense and defense. Furthermore; we aimed to define position-specific demands and differences among them. Forty players from three teams were analyzed during the tournament using a local positioning system (LPS) for the first time in top handball. Players covered similar distances both in offense (1388.28 ± 2627.08 m), and in defense (1305.47 ± 5059.64 m) and remained on court for a similar average time (15.69 ± 8.02 min and 15.40 ± 8.94 min respectively). When locomotion activities were normalized according to the time they spent on court; significant differences were found for defense compared to offense in walking (+20%; p < 0.000; Cohen's effect size (ES) = 1.01) and jogging (-29.6%; p = 0.000; ES = 0.90), as well as a tendency for high-intensity running (+ 25.2%; p = 0.077; ES = 0.31). Per playing position; center and left back (CB = 94.86 ± 10.98 m·min-1; LB = 96.55 ± 24.65 m·min-1) showed the highest running pace in offense and mid-left; front center defender and outside right for the defense (ML = 90.38 ± 30.16 m·min-1; FCD = 87.04 ± 14.94 m·min-1; OR = 89.64 ± 34.93 m·min-1). In conclusion; profile differences existed among players' position activity; both in offense and defense; which should be taken into account when designing specific physical training programs.

ProjectRun21: Do running experience and running pace influence the risk of running injury-A 14-week prospective cohort study.

OBJECTIVES: The health benefits from participation in half-marathon is challenged by a yearly running-related injury (RRI) incidence proportion exceeding 30%. Research in injury etiology is needed to successfully prevent injuries. The body's load capacity is believed to play an essential role for injury development. Therefore, the purpose of ProjectRun21 was to investigate the association between load capacity defined as running experience and running pace, and RRI when following a specific half-marathon running schedule. DESIGN: A 14-week prospective cohort study. METHODS: A cohort of 784 healthy runners followed a specific half-marathon running schedule. Data on running activity was collected objectively using a Global-Positioning-System watch or smartphone. RRI were collected using e-mail-based weekly questionnaires. Primary exposures were running experience and running pace, dichotomized into a high and a low group for runners running less or more than 15km/week and faster or slower than 6min/km, respectively. Data was analyses through time-to-event models with cumulative risk difference (RD) as measure of association. RESULTS: A total of 136 participants sustained a RRI during follow-up. Although not statistically significant, all estimates indicate a tendency toward fewer injuries amongst runners categorized as having high experience (RD=-11.3% (-27.2% to 4.6%)) or high pace (RD=-17.4% (-39.0% to 4.5%)), and a combination of both high experience and high pace (RD=-8.1% (-22.3% to 6.1%)) compared with their counterpart peers. CONCLUSIONS: Runners covering less than 15km per week, and/or runs slower than 6min/km, may sustain more RRI than their counterpart runners.

Classifying running-related injuries based upon etiology, with emphasis on volume and pace.

BACKGROUND AND PURPOSE: Many researchers acknowledge the importance of "training errors" as the main cause of running-related injuries. The purpose of this clinical commentary is to present a theoretical framework for the assumption that some running-related injuries among rear-foot strikers develop due to rapidly changing running volume, while others develop due to rapidly changing running pace. DESCRIPTION OF TOPIC WITH RELATED EVIDENCE: Evidence from clinical and experimental studies is presented to support the assertion that rapid change in running volume may lead to the development of patellofemoral pain syndrome, iliotibial band syndrome, and patellar tendinopathy, while change in running pace may be associated with the development of achilles tendinopathy, gastrocnemius injuries, and plantar fasciitis. DISCUSSIONRELATION TO CLINICAL PRACTICE: If this assertion is correct, bias may be prevented in future studies by categorizing injuries into volume or pacing injuries. However, more work is needed to provide further evidence in support of this approach. Future investigations of the link between training patterns and injury development should be designed as large-scale prospective studies using objective methods to quantify training patterns. LEVEL OF EVIDENCE: 5.