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Impact of contextual variables on the representative external load profile of Spanish professional soccer match-play: A full season study.

Jose María Oliva-LozanoDaniel Rojas-ValverdeCarlos David Gómez-CarmonaVíctor FortesJose Pino-Ortega
Published in: European journal of sport science (2020)
The aims of this study were to: (1) identify the representative external load profile of match-play in Spanish professional soccer players by principal components analysis (PCA), and (2) analyse the effect of match location (home vs away), match outcome (win vs draw vs loss) and length of the microcycle (5 vs 6 vs 7 vs 8 vs 9 days) on the external load profile. Data were collected during one season consisting of 42 matches in LaLiga 123 and 11 external load variables were selected after the PCA. TD, total distance covered; DIS0-6: distance from 0 to 6 km/h; DIS21-24: distance from 21 to 24 km/h; HSRD: high-speed running distance above 21 km/h; HSRA: total of high-speed running actions above 21 km/h; VMAX: maximum speed in km/h; Sprints: total of actions above 24 km/h; ACC: total of accelerations; ACCG-avg: average accelerometer G-force; ACCMAX: maximum acceleration (m/s2); DECMAX: maximum deceleration (m/s2). Match location had an impact on HSRD (p < 0.01; ES = 0.05), DIS0-6 (p < 0.01; ES = 0.05), and ACCMAX (p < 0.01; ES = 0.05). Match outcome had a relation to TD (p < 0.01; ES = 0.05), DIS0-6 (p < 0.01; ES = 0.05) and HSRD (p < 0.01; ES = 0.05). Length of the microcycle had an impact on TD (p < 0.01; ES = 0.05), DIS0-6 (p < 0.01; ES = 0.11), ACC (p < 0.01; ES = 0.04) and VMAX (p < 0.01; ES = 0.04). This study provides coaches a selection of variables for match-play analysis, which could represent two-thirds of external load profile. Then, professionals should consider that these contextual variables could have an impact on the external load profile.
Keyphrases
  • high speed
  • atomic force microscopy
  • cross sectional
  • machine learning
  • mass spectrometry
  • deep learning