Elite Soccer Players Do Not Cover Less Distance in the Second Half of the Matches When Game Interruptions Are Considered

Rey, Ezequiel; Kalén, Antón; Lorenzo-Martínez, Miguel; Campo, Roberto López-Del; Nevado-Garrosa, Fabio; Lago‐Peñas, Carlos

doi:10.1519/jsc.0000000000003935

Cited by 19 publications

(23 citation statements)

References 31 publications

(49 reference statements)

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“…However, this general statement that the defensive or non-ball-possession phase is more physically demanding is affected by certain contextual variables, such as Score and Place, but especially by strategic variables such as the time of possession and the time in which the ball is in play during a match [ 1 ]. The study of physical demand during EPT is not new [ 1 ], although it has recently received some attention again [ 21 , 22 ]. As might be expected, in competition most of the distance is covered players at the moments when the ball is in play [ 1 ], accumulating a higher percentage of the total as the speed ranges increase (e.g., > 21 km·h -1 ).…”

Section: Discussionmentioning

confidence: 99%

Tell me how and where you play football and I’ll tell you how much you have to run

Castellano¹,

Errekagorri²,

Arcos³

et al. 2022

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The aim of this study was to describe the team accumulated physical response per minute considering only the effective playing time (EPT) attending to different contextual and strategic variables in the Spanish Football First Division ( LaLiga Santander ). A sample of 2,959 performances was included in the analysis, considering a 4-year period of analysis (from 2016–17 to 2019–20). The physical variables were: total distance covered with (DTminPOS) and without (DTminNOpos) possession of the ball, and distance covered at > 21 km·h -1 with possession (DT21minPOS) and without (DT21minNOpos). Two contextual variables, i.e. Place (Home/Away) and Score (Lost/Draw/Win), and two strategic variables, i.e. level of effective playing time (LevelETP) and level of possession of the ball (LevelPOS), were analysed. The teams ran more without possession of the ball than with possession; nevertheless, the teams that had less possession of the ball had higher values in the distance covered at > 21 km·h -1 with possession of the ball and vice versa. Furthermore, the strategic variables also had influence on the physical response (DT and DT21) of the teams,LevelETP and LevelPOS, although with interactive effects: longer playing time, less accumulated distance, and greater possession, greater accumulated distance in the defensive phase, both per min. The findings of this study may offer important practical implications to practitioners in order to assess physical performances of the players in matches, because it is crucial to integrate in the analysis the different contextual and strategic variables where the match has taken place to assess performances of the teams.

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Section: Discussionmentioning

confidence: 99%

Tell me how and where you play football and I’ll tell you how much you have to run

Castellano¹,

Errekagorri²,

Arcos³

et al. 2022

Self Cite

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“…The review by Alghannam ( 2012 ) shows how physical performance decreases throughout the match due to accumulated fatigue. However, a recent study shows that if we consider effective time (i.e., not counting interruptions) rather than total playing time, the differences in terms of distances traveled at different speeds are much smaller between the first and second half of the match (Rey et al, 2020 ). In addition, the distance traveled at a high intensity (21–24 km/h) and sprint (>24 km/h) between the first and second part of the match depends on the demarcation, with midfielders and attackers decreasing their performance in the second half.…”

Section: Discussionmentioning

confidence: 99%

Perceptions of Football Analysts Goal-Scoring Opportunity Predictions: A Qualitative Case Study

et al. 2021

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This study aimed to understand the way tactical football analysts perceive the general match analysis issues and to analyze their tactical interpretation of the predictive models of conceded goal-scoring opportunities. Nine tactical analysts responded to the semi-structured interviews that included a general section on the match analysis and a specific one on the results of a study on goal-scoring opportunities conceded by a Spanish La Liga team. Following their transcription, the interviews were codified into categories by the two researchers using Atlas Ti® software. Subsequently, frequency count and co-occurrence analysis were performed based on the encodings. The content analysis reflected that analysts play a crucial role in the analysis of their own team and that of the opponent, the essential skills to exercise as a tactical analyst being “understanding of the game” and “clear observation methodology.” Based on the case study of the conceded goal-scoring opportunities, the major causes and/or solutions attributed by analysts in some of the predictive models were the adaptability of the “style of play” itself according to the “opponent” and “pressure after losing.”

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“…Similarly, recent research has used the TRACAB system to explore physical performance according to age groups [22] and half variations [24], offensive performance in football [25], how the quality of opposition impact the spatial-temporal features of individual ball possessions [26], or even to understand the risk of contact exposure during football matches in the context of the COVID-19 pandemic [27]. This system has also provided reliable results compared with other reference systems (VICON motion capture system) [23].…”

Section: Methodsmentioning

confidence: 99%

Match Analysis of Soccer Refereeing Using Spatiotemporal Data: A Case Study

Gonçalves

Coutinho

Travassos

et al. 2021

Sensors

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This case study explored how spatiotemporal data can develop key metrics to evaluate and understand elite soccer referees’ performance during one elite soccer match. The dynamic position of players from both teams, the ball and three elite referees allowed to capture the following performance metrics: (i) assistant referees: alignment with the second last defender; (ii) referee: referee diagonal movement—a position density was computed and a principal component analysis was carried to identify the directions of greatest variability; and (iii) referee: assessing the distance from the referee to the ball. All computations were processed when the ball was in-play and separated by 1st and 2nd halves. The first metric showed an alignment lower than 1 m between the assistant referee and the second last defender. The second metric showed that in the 1st half, the referee position ellipsis area was 548 m2, which increased during the 2nd half (671 m2). The third metric showed an increase in the distance from the referee to the ball and >80% of the distance between 5–30 m during the 2nd half. The findings may be used as a starting point to elaborate normative behavior models from the referee’s movement performance in soccer.

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Elite Soccer Players Do Not Cover Less Distance in the Second Half of the Matches When Game Interruptions Are Considered

Cited by 19 publications

References 31 publications

Tell me how and where you play football and I’ll tell you how much you have to run

Tell me how and where you play football and I’ll tell you how much you have to run

Perceptions of Football Analysts Goal-Scoring Opportunity Predictions: A Qualitative Case Study

Match Analysis of Soccer Refereeing Using Spatiotemporal Data: A Case Study

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