Player load in male elite soccer : Comparisons of patterns between matches and positions

Our primary aim was to explore the development of player load throughout match time (i.e., the pattern) using moving 5-min windows in an elite soccer team and our secondary aim was to compare player load patterns between different positions within the same team. The dataset included domestic home matches (n = 34) over three seasons for a Norwegian Elite League team. Player movements (mean ± SD age 25.5 ± 4.2 years, height 183.6 ± 6.6 cm, body mass 78.9 ± 7.4 kg) were recorded at 20 Hz using body-worn sensors. Data for each variable (player load, player load per meter, total distance, accelerations, decelerations, sprint distance, high-intensity running distance) were averaged within positions in each match, converted to z-scores and averaged across all matches, yielding one time series for each variable for each position. Pattern similarity between positions was assessed with cross-correlations. Overall, we observed a distinct pattern in player load throughout match time, which also occurred in the majority of individual matches. The pattern shows peaks at regular intervals (~15 min), each followed by a period of lower load, declining until the next peak. The same pattern was evident in player load per meter. The cross-correlation analyses support the visual evidence, with correlations ranging 0.88–0.97 (p < .001) in all position pairs. In contrast, no specific patterns were discernible in total distance, accelerations, decelerations, sprint distance and high-intensity running distance, with cross-correlations ranging 0.65–0.89 (p < .001), 0.32–0.64 (p < .005), 0.18–0.65 (p < .005 in nine position pairs), 0.02–0.38 (p < .05 in three pairs) and 0.01–0.52 (p < .05 in three pairs), respectively. This study demonstrated similarity in player load patterns between both matches and positions in elite soccer competition, which could indicate a physical “pacing pattern” employed by the team.publishedVersio

Accelerations–a new approach to quantify physical performance decline in male elite soccer?

The aim of the current study was (1) to investigate whether the number of accelerations is a more precise estimate of performance decline in soccer compared to distances with high-speed running (HSR) and (2) to compare changes in the number of accelerations and HSR distances across playing positions in order to examine whether the match profiles of the physical measures are consistent or demonstrate high interposition variability. The dataset includes domestic home games (N = 34) over three full seasons (2012–2014) for a team in the Norwegian Elite League. The change in the number of accelerations throughout the match demonstrates a more clear pattern compared to the distance covered by HSR. In numbers of accelerations, a systematic and linear decrease can be observed throughout the match, with 34% less accelerations from the first to the last 5-minute period of the game (6.7 vs. 4.4 accelerations). This pattern of results captures the change in the number of accelerations across all positions. HSR distance had more variability during the match. All five positions investigated displayed a similar trend in accelerations and HSR profiles after the peak periods in each half. In contrast to the absolute number of accelerations, there were major positional differences in the mean HSR distance during the match. Our data suggest a more visible performance decline in the number of accelerations from the start to the end of the game, than the decline in the distance covered by HSR distance

Acceleration and sprint profiles of a professional elite football team in match play

Abstract: The aim of this study was to characterise the acceleration and sprint profiles of elite football match play in one Norwegian elite football team (Rosenborg FC). Fifteen professional players in five playing positions took part in the study (n = 101 observations). Player movement was recorded during every domestic home game of one full season (n = 15) by an automatic tracking system based on microwave technology. Each player performed 91 ± 21 accelerations per match, with a lower number in the second compared with the first half (47 ± 12 vs. 44 ± 12). Players in lateral positions accelerated more often compared to players in central positions (98.3 ± 20.5 vs. 85.3 ± 19.5, p &lt; 0.05). Average sprint distance was 213 ± 111 m distributed between 16.6 ± 7.9 sprints, with no differences between first (106 ± 60 m, 8.2 ± 4.2 sprints) and second halves (107 ± 72 m, 8.3 ± 4.8 sprints). Players in lateral positions sprinted longer distances (287 ± 211 m vs. 160 ± 76 m, p &lt; 0.05) and tended to sprint more often (21.6 ± 7.8 vs. 13.0 ± 5.7, p = 0.064) compared to players in central positions. We found more walking and less of the more intense activities during the last third of the season compared to the first. The main finding in this study was that Norwegian elite players had substantially less number of accelerations and fewer but longer sprints than previous studies reported for higher-ranked leagues. Also, less high-intensity activity was found towards the end of the season. Ultimately, these data provide useful information for the fitness coach (1) in planning of position-specific football training and (2) to avoid the decline in high-intensity activities the last third of the competitive season.</p

Player load in male elite soccer: Comparisons of patterns between matches and positions

Our primary aim was to explore the development of player load throughout match time (i.e., the pattern) using moving 5-min windows in an elite soccer team and our secondary aim was to compare player load patterns between different positions within the same team. The dataset included domestic home matches (n = 34) over three seasons for a Norwegian Elite League team. Player movements (mean ± SD age 25.5 ± 4.2 years, height 183.6 ± 6.6 cm, body mass 78.9 ± 7.4 kg) were recorded at 20 Hz using body-worn sensors. Data for each variable (player load, player load per meter, total distance, accelerations, decelerations, sprint distance, high-intensity running distance) were averaged within positions in each match, converted to z-scores and averaged across all matches, yielding one time series for each variable for each position. Pattern similarity between positions was assessed with cross-correlations. Overall, we observed a distinct pattern in player load throughout match time, which also occurred in the majority of individual matches. The pattern shows peaks at regular intervals (~15 min), each followed by a period of lower load, declining until the next peak. The same pattern was evident in player load per meter. The cross-correlation analyses support the visual evidence, with correlations ranging 0.88–0.97 (p < .001) in all position pairs. In contrast, no specific patterns were discernible in total distance, accelerations, decelerations, sprint distance and high-intensity running distance, with cross-correlations ranging 0.65–0.89 (p < .001), 0.32–0.64 (p < .005), 0.18–0.65 (p < .005 in nine position pairs), 0.02–0.38 (p < .05 in three pairs) and 0.01–0.52 (p < .05 in three pairs), respectively. This study demonstrated similarity in player load patterns between both matches and positions in elite soccer competition, which could indicate a physical “pacing pattern” employed by the team

Player load in male elite soccer : Comparisons of patterns between matches and positions

Our primary aim was to explore the development of player load throughout match time (i.e., the pattern) using moving 5-min windows in an elite soccer team and our secondary aim was to compare player load patterns between different positions within the same team. The dataset included domestic home matches (n = 34) over three seasons for a Norwegian Elite League team. Player movements (mean ± SD age 25.5 ± 4.2 years, height 183.6 ± 6.6 cm, body mass 78.9 ± 7.4 kg) were recorded at 20 Hz using body-worn sensors. Data for each variable (player load, player load per meter, total distance, accelerations, decelerations, sprint distance, high-intensity running distance) were averaged within positions in each match, converted to z-scores and averaged across all matches, yielding one time series for each variable for each position. Pattern similarity between positions was assessed with cross-correlations. Overall, we observed a distinct pattern in player load throughout match time, which also occurred in the majority of individual matches. The pattern shows peaks at regular intervals (~15 min), each followed by a period of lower load, declining until the next peak. The same pattern was evident in player load per meter. The cross-correlation analyses support the visual evidence, with correlations ranging 0.88–0.97 (p < .001) in all position pairs. In contrast, no specific patterns were discernible in total distance, accelerations, decelerations, sprint distance and high-intensity running distance, with cross-correlations ranging 0.65–0.89 (p < .001), 0.32–0.64 (p < .005), 0.18–0.65 (p < .005 in nine position pairs), 0.02–0.38 (p < .05 in three pairs) and 0.01–0.52 (p < .05 in three pairs), respectively. This study demonstrated similarity in player load patterns between both matches and positions in elite soccer competition, which could indicate a physical “pacing pattern” employed by the team