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- Ekstrand, Jan, et al.
(author)
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Are Elite Soccer Teams Preseason Training Sessions Associated With Fewer In-Season Injuries? A 15-Year Analysis From the Union of European Football Associations (UEFA) Elite Club Injury Study
- 2020
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In: American Journal of Sports Medicine. - : SAGE PUBLICATIONS INC. - 0363-5465 .- 1552-3365. ; 48:3, s. 723-729
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Journal article (peer-reviewed)abstract
- Background: Preseason training develops players physical capacities and prepares them for the demands of the competitive season. In rugby, Australian football, and American football, preseason training may protect elite players against in-season injury. However, no study has evaluated this relationship at the team level in elite soccer. Purpose/Hypothesis: The aim of this study was to investigate whether the number of preseason training sessions completed by elite soccer teams was associated with team injury rates and player availability during the competitive season. It was hypothesized that elite soccer teams who participate in more preseason training will sustain fewer injuries during the competitive season. Study Design: Descriptive epidemiology study. Methods: We used the Union of European Football Associations (UEFA) injury dataset to analyze 44 teams for up to 15 seasons (total, 244 team-seasons). Separate linear regression models examined the association between the number of team preseason training sessions and 5 in-season injury measures. Injury-related problems per team were quantified by totals of the following: (1) injury burden, (2) severe injury incidence, (3) training attendance, (4) match availability, and (5) injury incidence. Results: Teams averaged 30 preseason training sessions (range, 10-51). A greater number of preseason training sessions was associated with less injury load during the competitive season in 4 out of 5 injury-related measures. Our linear regression models revealed that for every 10 additional preseason training sessions that the team performed, the in-season injury burden was 22 layoff days lower per 1000 hours (P = .002), the severe injury incidence was 0.18 severe injuries lower per 1000 hours (P = .015), the training attendance was 1.4 percentage points greater (P = .014), and the match availability was 1.0 percentage points greater (P = .042). As model fits were relatively low (adjusted R-2 = 1.3%-3.2%), several factors that contribute to in-season injury outcomes were unaccounted for. Conclusion: Teams that performed a greater number of preseason training sessions had "healthier" in-season periods. Many other factors also contribute to in-season injury rates. Understanding the benefit of preseason training on in-season injury patterns may inform sport teams planning and preparation.
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2. |
- Windt, Johann, et al.
(author)
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Does player unavailability affect football teams match physical outputs? A two-season study of the UEFA champions league
- 2018
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In: Journal of Science and Medicine in Sport. - : ELSEVIER SCI LTD. - 1440-2440 .- 1878-1861. ; 21:5, s. 525-532
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Journal article (peer-reviewed)abstract
- Objectives: Player unavailability negatively affects team performance in elite football. However, whether player unavailability and its concomitant performance decrement is mediated by any changes in teams match physical outputs is unknown. We examined whether the number of players injured (i.e. unavailable for match selection) was associated with any changes in teams physical outputs. Design: Prospective cohort study. Methods: Between-team variation was calculated by correlating average team availability with average physical outputs. Within-team variation was quantified using linear mixed modelling, using physical outputs - total distance, sprint count (efforts over20 km/h), and percent of distance covered at high speeds (amp;gt;14 km/h) - as outcome variables, and player unavailability as the independent variable of interest. To control for other factors that may influence match physical outputs, stage (group stage/knockout), venue (home/away), score differential, ball possession (%), team ranking (UEFA Club Coefficient), and average team age were all included as covariates. Results: Teams average player unavailability was positively associated with the average number of sprints they performed in matches across two seasons. Multilevel models similarly demonstrated that having 4 unavailable players was associated with 20.8 more sprints during matches in 2015/2016, and with an estimated 0.60-0.77% increase in the proportion of total distance run above 14 km/h in both seasons. Player unavailability had a possibly positive and likely positive association with total match distances in the two respective seasons. Conclusions: Having more players injured and unavailable for match selection was associated with an increase in teams match physical outputs. (C) 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
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3. |
- Windt, Johann, et al.
(author)
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Getting the most out of intensive longitudinal data: a methodological review of workload-injury studies
- 2018
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In: BMJ Open. - : BMJ PUBLISHING GROUP. - 2044-6055. ; 8:10
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Research review (peer-reviewed)abstract
- Objectives To systematically identify and qualitatively review the statistical approaches used in prospective cohort studies of team sports that reported intensive longitudinal data (ILD) (amp;gt;20 observations per athlete) and examined the relationship between athletic workloads and injuries. Since longitudinal research can be improved by aligning the (1) theoretical model, (2) temporal design and (3) statistical approach, we reviewed the statistical approaches used in these studies to evaluate how closely they aligned these three components. Design Methodological review. Methods After finding 6 systematic reviews and 1 consensus statement in our systematic search, we extracted 34 original prospective cohort studies of team sports that reported ILD (amp;gt;20 observations per athlete) and examined the relationship between athletic workloads and injuries. Using Professor Linda Collins three-part framework of aligning the theoretical model, temporal design and statistical approach, we qualitatively assessed how well the statistical approaches aligned with the intensive longitudinal nature of the data, and with the underlying theoretical model. Finally, we discussed the implications of each statistical approach and provide recommendations for future research. Results Statistical methods such as correlations, t-tests and simple linear/logistic regression were commonly used. However, these methods did not adequately address the (1) themes of theoretical models underlying workloads and injury, nor the (2) temporal design challenges (ILD). Although time-to-event analyses (eg, Cox proportional hazards and frailty models) and multilevel modelling are better-suited for ILD, these were used in fewer than a 10% of the studies (n= 3). Conclusions Rapidly accelerating availability of ILD is the norm in many fields of healthcare delivery and thus health research. These data present an opportunity to better address research questions, especially when appropriate statistical analyses are chosen.
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