The inter-unit and inter-model reliability of GNSS STATSports Apex and Viper units in measuring peak speed over 5, 10, 15, 20 and 30 meters

Beato, Marco; Keijzer, Kevin L de

doi:10.5114/biolsport.2019.88754

Cited by 56 publications

(76 citation statements)

References 20 publications

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Section: Methodsmentioning

confidence: 99%

“…During all the training sessions, Apex 10 Hz GNSS (STATSports, Northern Ireland) units were used to collect data [4]. Apex units' validity and reliability were previously reported both for team sports and peak speed monitoring [4]. The Apex units were turned on 15 min before the beginning of the data recording to guarantee synchronization between the Apex units and GNSS [4].…”

Section: Methodsmentioning

confidence: 99%

“…Apex units' validity and reliability were previously reported both for team sports and peak speed monitoring [4]. The Apex units were turned on 15 min before the beginning of the data recording to guarantee synchronization between the Apex units and GNSS [4]. GNSS data recorded by the units were downloaded and further analyzed with STATSports Software (Apex version 3.0.02011).…”

Section: Methodsmentioning

confidence: 99%

“…The most common technology utilized to quantify external WL parameters are global navigation satellite systems (GNSS) [3]. GNSS are used to monitor sport-specific metrics, such as total distance covered (TD) and high-speed running, during training sessions and matches [3,4]. Additionally, external WL can be integrated with internal load (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, external WL can be integrated with internal load (e.g. rating of perceived exertion [RPE]) that might guarantee a better comprehension of the players' WL in soccer [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Workload Monitoring in Top-level Soccer Players During Congested Fixture Periods

Gualtieri

Rampinini²,

Sassi

et al. 2020

Int J Sports Med

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This study assessed the internal and external workload of starters and non-starters in a professional top-level soccer team during a congested fixture period. Twenty Serie A soccer players were monitored in this study during two mesocycles of 21 days each. Starters and non-starters were divided based on the match time played in each mesocycle. The following metrics were recorded: exposure time, total distance, relative total distance, high-speed running distance over 20 km·h−1, very high-speed running distance over 25 km·h−1, individual very high-speed distance over 80% of maximum peak speed, and rating of perceived exertion. Differences between starters and non-starters were found for: exposure time (effect size=large to very large), rating of perceived exertion (large to very large), total distance (large to very large), and individual very high-speed distance over 80% of maximum peak speed (moderate to large). Furthermore, differences for relative total distance, high-speed running distance over 20 km·h−1 and very high-speed running distance over 25 km·h−1 were small to moderate, but not significant. This study reports that during congested fixture periods, starters had higher exposure time, rating of perceived exertion, total distance, and individual very high-speed distance over 80% of maximum peak speed than non-starters.

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Section: Methodsmentioning

confidence: 99%