The match-to-match variation of match-running in elite female soccer

Trewin, Joshua; Meylan, César; Varley, Matthew C.; Cronin, John

doi:10.1016/j.jsams.2017.05.009

Cited by 86 publications

(161 citation statements)

References 28 publications

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“…Regarding studies exploring the locomotor demands in young soccer players, the most used index was PL TM [1]. In the present study a PL TM of 12.8 a.u./min was found, while other published data reported 10.2 a.u./min in young male soccer players [47], 11.5 a.u./min in elite male soccer players [48], and 10.3-10.9 a.u./min in consecutive matches in elite female players [49] using the same variable. These differences between the values obtained in literature and the present results could be due to the lack of tactical synchronization in U-16 with respect to U-18 and senior players that cause more displacements [50] and shorter periods of time (40 vs. 45 min) that produce less fatigue [51].…”

Section: Discussioncontrasting

confidence: 55%

Accelerometry-Based External Load Indicators in Sport: Too Many Options, Same Practical Outcome?

Gómez-Carmona

Pino-Ortega

Sánchez-Ureña

et al. 2019

IJERPH

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With the development of new microsensor technology to assess load in sports, some indicators of external load through accelerometry-based data have been created by sport technology companies. Thus, the study aim was to analyze the agreement between different accelerometry-based external load indicators (ABELIs) available in sport science. A U-16 male soccer team was assessed during three official matches, divided by periods, to obtain 3-D accelerometry data (x, y and z axes). An average of 1,420,000 data points was analyzed per axis per player. The ABELIs were calculated using this information, and the agreement between them was explored. The following ABELIs were considered after a literature review: AcelT, Player Load RT , PlayerLoad TM , Impulse Load, Player Load RE and Total Load. In order to compare ABELIs, two analyses were performed using:(1) absolute data; and (2) normalized and centered data (Z-scores). In absolute and centered data, very large to nearly perfect correlations (1st period: r > 0.803, p > 0.01; 2nd period: r > 0.919; p > 0.01) were found. Instead, very large differences were found in absolute values (bias = −579,226.6 to 285,931.1; t = −224.66 to 213.91, p < 0.01), and no differences in scaled and centered values (bias = 0; t = 1; p = 1). In conclusion, considering the different output (magnitude and units) among ABELIs, the standardization of a universal index to calculate accelerometer load is needed in order to make possible between-study comparison.(heart rate telemetry, muscle oxygen saturation, internal temperature, power, cadence, among others) with excellent accuracy and reliability [7][8][9][10][11][12].One of these sensors is the accelerometer. Accelerometers were first introduced in sports science in the beginning of the 21st century thanks to the Project 2.5 "Technology of Communication to Athletes Monitoring" carried out by the Australian Centre of Microtechnological Research for designing a unique nonintrusive device for sport monitoring in real time [13]. Since its appearance, there has been enormous technological, technical and methodological development in the use of accelerometry to quantify external workload in sports [14][15][16]. The sensitivity and precision of accelerometry-based variables are higher compared to other tracking systems that underestimate load demands. This phenomenon is due to the fact that static high-intensity actions without covering ground (jumps, collisions, falls, tackles, etc.) cannot be recorded by time-motion systems, but can be measured with high accuracy by accelerometers [6,17].A large quantity of variables has been developed using data recorded by this sensor. The analysis of this information has tended to be more complex because the different companies use different algorithms to classify the actions and this limits comparability among studies [18]. The most used variable is PlayerLoad TM , designed by Catapult Sports company [11]. This variable was created to quantify the total load players are exposed to and is obtained from the acceler...

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Section: Discussioncontrasting

confidence: 55%

Accelerometry-Based External Load Indicators in Sport: Too Many Options, Same Practical Outcome?

Gómez-Carmona

Pino-Ortega

Sánchez-Ureña

et al. 2019

IJERPH

View full text Add to dashboard Cite

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“…Finally, the level of competition should be considered in the comparison between studies; the present study utilized players from a sub-elite Australian academy (under 21 yr), while Rampini et al, (2015) analyzed elite European soccer players. These considerations highlight recommendations previously made [6,10], suggesting it is necessary to establish CVs for each reference athletic population due to the specific characteristics of a given cohort. Nonetheless, despite the aforementioned differences in technology, classification of high-speed running zones and level of competition, the present and previous research shows similar trends of match-to-match variations with increasing running speeds.…”

Section: Discussionmentioning

confidence: 82%

“…While the variability in displacement measures has been investigated extensively [6,8,9,21,22], the determination of variability of these measures over a specific number of data sets is limited. It is common practice to compare data sets in order to assess changes in performance, particularly in the assessment of periodized programs.…”

Section: Discussionmentioning

confidence: 99%

“…Recent rules changes by the Fédération Internationale de Football Association (FIFA) have permitted the use of GPS tracking technologies in official competitive soccer matches [5], allowing the same data capture system to be used in both training and matches. While the variability in total movement distance recorded by GPS was previously shown to be acceptable, high-speed (and sprint-speed) activities were susceptible to greater variability [6][7][8][9]. Therefore, while total distance is a relatively stable outcome variable, high-speed movements are more variable indicators of running performance.…”

Section: Introductionmentioning

confidence: 97%

“…Therefore, while total distance is a relatively stable outcome variable, high-speed movements are more variable indicators of running performance. Despite previous recommendations in rugby [10] and soccer [6] to establish the between-match coefficients of variation in their athlete populations (to quantify variations specific to their cohort), previous analyses of smaller blocks of data points are limited (e. g. 2-10 matches). Understanding such variations over shorter windows may provide more useful understanding of athlete maximal demands, and thus is important for both tracking performance characteristics and understanding data variation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Reduction in Match-to-match Variability Using Maximal Mean Analyses in Sub-elite Soccer

et al. 2020

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The match-to-match variability of external loads in National Premier League soccer competition was determined. Global positioning systems (GPS) data were collected from 20 sub-elite soccer players over 2–10 matches from a single season. Match data were collected from during one season. Twenty-six matches were recorded and 10 were utilised within final match-to-match analysis based on stringent data selection criteria. A symmetric moving average algorithm was applied to GPS data over specific time windows (1, 5, 10, 60, 300 and 600 s), and maximal speed and metabolic power values then calculated at each time interval during each match. Match-to-match coefficients of variation (CV) were greatest for sprint-speed running distance (36.3–43.6%) when comparing 2 vs. 10 matches. CVs for maximal mean speed (4.9–7.0%) and metabolic power (4.4–9.6%) ranged from good to moderate. As the variability of absolute high-speed distance values are greater, and therefore less reliable, their use as indicators of performance is reduced, suggesting that maximal mean analyses could be used as an alternative in the assessment of match running performance during competitive matches.

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An investigation of the sprint performance of senior elite camogie players during competitive play

et al. 2022

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The match-to-match variation of match-running in elite female soccer

Cited by 86 publications

References 28 publications

Accelerometry-Based External Load Indicators in Sport: Too Many Options, Same Practical Outcome?

Accelerometry-Based External Load Indicators in Sport: Too Many Options, Same Practical Outcome?

A Reduction in Match-to-match Variability Using Maximal Mean Analyses in Sub-elite Soccer

An investigation of the sprint performance of senior elite camogie players during competitive play

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