Literature DB >> 33199359

Injury incidence and burden in a youth elite football academy: a four-season prospective study of 551 players aged from under 9 to under 19 years.

Olivier Materne1,2, Karim Chamari3, Abdulaziz Farooq3, Adam Weir3,4,5, Per Hölmich3,6, Roald Bahr3,7, Matt Greig8, Lars R McNaughton8,9.   

Abstract

OBJECTIVE: Investigate the incidence and burden of injuries by age group in youth football (soccer) academy players during four consecutive seasons.
METHODS: All injuries that caused time-loss or required medical attention (as per consensus definitions) were prospectively recorded in 551 youth football players from under 9 years to under 19 years. Injury incidence (II) and burden (IB) were calculated as number of injuries per squad season (s-s), as well as for type, location and age groups.
RESULTS: A total of 2204 injuries were recorded. 40% (n=882) required medical attention and 60% (n=1322) caused time-loss. The total time-loss was 25 034 days. A squad of 25 players sustained an average of 30 time-loss injuries (TLI) per s-s with an IB of 574 days lost per s-s. Compared with the other age groups, U-16 players had the highest TLI incidence per s-s (95% CI lower-upper): II= 59 (52 to 67); IB=992 days; (963 to 1022) and U-18 players had the greatest burden per s-s: II= 42.1 (36.1 to 49.1); IB= 1408 days (1373 to 1444). Across the cohort of players, contusions (II=7.7/s-s), sprains (II=4.9/s-s) and growth-related injuries (II=4.3/s-s) were the most common TLI. Meniscus/cartilage injuries had the greatest injury severity (95% CI lower-upper): II= 0.4 (0.3 to 0.7), IB= 73 days (22 to 181). The burden (95% CI lower-upper) of physeal fractures (II= 0.8; 0.6 to 1.2; IB= 58 days; 33 to 78) was double than non-physeal fractures.
SUMMARY: At this youth football academy, each squad of 25 players averaged 30 injuries per season which resulted in 574 days lost. The highest incidence of TLI occurred in under-16 players, while the highest IB occurred in under-18 players. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  Soccer; epidemiology; football; injuries; paediatrics

Year:  2020        PMID: 33199359     DOI: 10.1136/bjsports-2020-102859

Source DB:  PubMed          Journal:  Br J Sports Med        ISSN: 0306-3674            Impact factor:   13.800


  1 in total

1.  Application of Deep Learning Technology in Strength Training of Football Players and Field Line Detection of Football Robots.

Authors:  Daliang Zhou; Gang Chen; Fei Xu
Journal:  Front Neurorobot       Date:  2022-06-29       Impact factor: 3.493

  1 in total

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