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Self-reported wellness profiles of professional Australian Football players during the competition phase of the season
Gallo, Tania F. Cormack, Stuart J. Gabbett, Tim J. Lorenzen, Christian H.
Gallo, Tania F.
Cormack, Stuart J.
Gabbett, Tim J.
Lorenzen, Christian H.
Abstract
Abstract: Gallo, TF, Cormack, SJ, Gabbett, TJ, and Lorenzen, CH. Self-reported wellness profiles of professional Australian football players during the competition phase of the season. J Strength Cond Res 31(2): 495-502, 2017-With the prevalence of customized self-report measures in high-performance sport, and the incomplete understanding of athletes' perceived wellness in response to matches and training load, the objective of this study was to explore weekly wellness profiles within the context of the competitive season of professional Australian football. Internal match load, measured through the session-rating of perceived exertion method, match-to-match microcycle, stage of the season, and training load were included in multivariate linear models to determine their effect on weekly wellness profile (n = 1,835). There was a lower weekly training load on a 6-day microcycle compared with a 7-day and 8-day microcycle. Match load had no significant impact on weekly wellness profile, while there was an interaction between microcycle and days postmatch. There was a likely moderately lower wellness Z-score 1 day postmatch for an 8-day microcycle (mean; 95% confidence interval: -1.79; -2.02 to -1.56) compared with a 6-day (-1.19; -1.30 to -1.08) and 7-day (-1.22; -1.34 to -1.09) cycle (d; 95% confidence interval: -0.82; -1.3 to -0.36, -0.78; -1.3 to -0.28, respectively). The second half of the season saw a possibly small reduction in overall wellness Z-score than the first half of the season (0.22; 0.12-0.32). Finally, training load had no effect on wellness Z-score when controlled for days postmatch, microcycle, and stage of the season. These results provide information on the status of players in response to matches and fixed conditions. Knowing when wellness Z-score returns to baseline relative to the length of the microcycle may lead practitioners to prescribe the heaviest load of the week accordingly. Furthermore, wellness "red flags" should be made relative to the microcycles and stage of the season to determine an athlete's status relative to their typical weekly profile.
Keywords
monitoring training, athlete self-report measures, psychometric tools
Date
2017
Type
Journal article
Journal
Journal of Strength and Conditioning Research
Book
Volume
31
Issue
2
Page Range
495-502
Article Number
ACU Department
School of Behavioural and Health Sciences
Faculty of Health Sciences
Faculty of Health Sciences
Relation URI
Source URL
Event URL
Open Access Status
License
File Access
Controlled