Do environmental temperatures and altitudes affect physical outputs of elite football athletes in match conditions? A systematic review of the ‘real world’ studies

Abstract

Players involved in the various football codes compete throughout the calendar year around the world. Therefore, environmental stressors such as temperature and altitude should be considered in preparation for, and during, matches. We aimed to systematically review the observational and quasiexperimental studies that have been specifically designed to quantify the effects of temperature (hot or cold) high altitude on in-match physical performance indicators. A search of electronic databases (Web of Science, Scopus, SPORTDiscus, PubMed/MEDLINE) was conducted, resulting in 19,424 papers being identified as relevant. Following sifting in relation to the eligibility criteria, 12 papers were deemed directly relevant. The reviewed studies scored 6-9 (on a 0-9 scale) for quality assessment using a previously used scale. The major outcome variables relevant to the current review were total distance (m), high speed running (m) and high-speed runs (count) measured during matches. Standardized effect sizes (ES) were heterogeneous across studies for total distance (ES: -0.96 to -0.14) and high-speed running (ES: -0.69 to 0.12) for >1000 m vs sea-level, time spent at the given altitude being a putative factor for this heterogeneity. Heat had mainly detrimental effects on performance, but ES were, again, heterogeneous across studies (ES: -1.25 to 0.26), dependent on temperature. Given the small number of studies that only involved mostly male athletes, and large heterogeneity across studies, more research needs be conducted on physical performance in these environmental conditions, with attention paid to standardizing outcomes and broadening the approaches of studies to guide future decision making in professional sporting environments.

Caffeine Supplementation does not Increase Performance on Professional Soccer Official Matches

“…The possible explanation for the divergent results of these three previous studies may be related to several factors such as the different forms of supplementation used in these studies, the intake of energy drinks that, in addition to caffeine, contained other substances such as sodium bicarbonate and taurine [7][8][9]. Furthermore, performance in the soccer game can be affected by numerous variables, such as physical fitness [16,17], competitive level [18,19], artificial turf versus natural grass [20,21], heat stress due to environment temperature [22,23], ball possession, and player/team technical standard [24,25]. Soccer is an unforeseeable sport and so many variables are impossible to control, therefore, they may still have influenced the results since the data collection was performed in official matches.…”

Seasonal analysis of match load in professional soccer players: An observational cohort study of a Swiss U18, U21 and first team

“…Advancements in technology made it possible to more accurately measure internal and external loads and thus the physical demands of soccer training and matches can now be better quantified ( Halson, 2014 ; Bourdon et al, 2017 ; Palucci Vieira, Carling, Barbieri, Aquino, & Santiago, 2019 ; Miguel et al, 2021 ; Torres-Ronda et al, 2022 ). Numerous studies assessed match loads of elite male, female, and youth soccer players regarding physical performance capacities, playing positions, tactical formation, or different contextual factors (e.g., match location, environmental conditions, match importance, preparation, fixture congestion, season phase, match outcome, nutrition strategies, game rules) ( Link & de Lorenzo, 2016 ; Palucci Vieira et al, 2019 ; Julian, Page, & Harper, 2020 ; Altmann et al, 2021 ; Chmura et al, 2021 ; Forcher et al, 2022a ; Forcher et al, 2022b ; Draper et al, 2022 ; Harkness-Armstrong, Till, Datson, Myhill, & Emmonds, 2022 ; Hulton, Malone, Clarke, & MacLaren, 2022 ; Sarmento et al, 2022 ). While the findings, especially at elite level, are not consistent, it is evident that data from one population group may not be relevant to other population groups ( Palucci Vieira et al, 2019 ; Saeterbakken et al, 2019 ; Reynolds et al, 2021 ; Forcher et al, 2022a ).…”