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1.
Scand J Med Sci Sports ; 34(1): e14546, 2024 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-38059701

RESUMEN

BACKGROUND: How the physical metrics, especially physical intensity, and possession interact with each other, and subsequently combine to influence performance remains opaque. Therefore, we investigated the interrelationship of possession, physical metrics, and team performance in elite soccer. METHODS: Four seasons of a top European league were used to derive 80 team league performances (points), together with possession and physical data. Physical metrics were absolute distances (m) during the whole match and ball-in-play, and rates of distance covered (m⋅min-1 ) as the index of physical intensity, notably when in-possession/out-of-possession, in total and within five speed categories. Interrelationships of possession, physical metrics, possession, and performance were assessed with Pearson's correlations and mediation analysis. RESULTS: Overall possession (r = 0.794) and time out-of-possession within the defensive third (r = -0.797) were most strongly correlated with performance. The strong relationships between in-possession distances and performance appeared coincidental due to greater time in-possession. Physical intensity had a complex relationship with possession and performance, with opposite relationships according to possession status: lower physical intensity when in-possession and higher physical intensity when out-of-possession were associated with possession and performance. Mediation analysis revealed the direct, independent importance of possession for team performance; however, the association of physical intensity with performance was largely (>79%) mediated by possession. CONCLUSION: Based on these findings, we propose a novel model of the interrelationships between possession, physical intensity, and performance, whereby higher possession is the largest, direct contributor toward enhanced team performance, with lower physical intensity in-possession a consequence of higher possession, but greater physical intensity when out-of-possession a cause of increased possession.


Asunto(s)
Rendimiento Atlético , Fútbol , Humanos , Estaciones del Año
2.
Eur J Sport Sci ; 23(9): 1892-1902, 2023 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-37078225

RESUMEN

The physical demands of soccer match-play have typically been assessed using a low-resolution whole match approach ignoring whether the ball is in or out of play (BIP/BOP) and during these periods which team has possession. This study investigated the effect of fundamental match structure variables (BIP/BOP, in/out of possession) on the physical demands, and especially intensity, of elite match-play. For 1083 matches from a major European league, whole match duration, and player physical tracking data, were divided into BIP/BOP, and in/out of possession periods throughout the match, using on-ball event data. These distinct phases were used to derive absolute (m) and rate (m·min-1) of distance covered in total and within six speed categories during BIP/BOP and in/out possession. The rate of distance covered, an index of physical intensity, was >2-fold greater during BIP vs BOP. Whole match total distance covered was confounded by BIP time and poorly associated with physical intensity during BIP (r = 0.36). Whole match rates of distance covered substantially underestimated those during BIP, particularly for higher running speeds (∼-62%). Ball possession markedly effected physical intensity, with the rates of distance covered running (+31%), at high-speed (+30%) and in total (+7%) greater out than in possession. Whole match physical metrics underestimated the physical intensity during BIP, and thus the rate(s) of distance covered during BIP are recommended for accurate measurement of physical intensity in elite soccer. The greater demands of being out of possession support a possession-based tactical approach to minimise fatigue and its negative consequences.


This large-scale study utilising >1000 elite level competitive matches found profound differences in rate of distance covered between periods of BIP vs BOP, being 2-fold higher overall and 8- to 33-fold higher for the rates of distance covered within running, high-speed and sprinting speed categories.Consequently, commonly used whole match physical metrics, that incorporate both BIP and BOP, such as distances covered but even rates of distance covered, were not valid indices of physical intensity (rate of distance covered) during BIP.Thus a more valid and direct approach to quantifying physical intensity during elite soccer match-play as the rate of distance covered during BIP is proposed.Utilising a unique within-match analysis the effect of possession (i.e. in vs out) revealed that teams covered ≥30% more running and high-speed distance while out than in possession during BIP.


Asunto(s)
Rendimiento Atlético , Carrera , Fútbol , Humanos , Fatiga
3.
Neural Netw ; 19(2): 236-47, 2006 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-16527458

RESUMEN

This paper uses a symbiotic adaptive neuro-evolutionary algorithm to breed neural network models for the River Ouse catchment. It advances on traditional evolutionary approaches by evolving and optimising individual neurons. Furthermore, it is ideal for experimentation with alternative objective functions. Recent research suggests that sum squared error may not result in the most appropriate models from a hydrological perspective. Models are bred for lead times of 6 and 24 hours and compared with conventional neural network models trained using backpropagation. The algorithm is also modified to use different objective functions in the optimisation process: mean squared error, relative error and the Nash-Sutcliffe coefficient of efficiency. The results show that at longer lead times the evolved neural networks outperform the conventional ones in terms of overall performance. It is also shown that the sum squared error objective function does not result in the best performing model from a hydrological perspective.


Asunto(s)
Inteligencia Artificial , Evolución Biológica , Simulación por Computador , Redes Neurales de la Computación , Lluvia , Algoritmos , Desastres , Inglaterra , Monitoreo del Ambiente/métodos , Monitoreo del Ambiente/estadística & datos numéricos , Reproducibilidad de los Resultados , Factores de Tiempo
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