Predicting injury risk using machine learning in male youth soccer players

人体测量学 数学 接收机工作特性 机器学习 跳跃 垂直跳跃 物理疗法 心理学 统计 医学 计算机科学 物理 量子力学 内科学
作者
Francisco Javier Robles-Palazón,José M Puerta-Callejón,José A. Gámez,Mark De Ste Croix,Antonio Cejudo,Fernando Santonja,Pilar Sainz de Baranda,Francisco Ayala
出处
期刊:Chaos Solitons & Fractals [Elsevier BV]
卷期号:167: 113079-113079
标识
DOI:10.1016/j.chaos.2022.113079
摘要

The aim of this study was twofold: a) to build models using machine learning techniques on data from an extensive screening battery to prospectively predict lower extremity soft tissue (LE-ST) injuries in non-elite male youth soccer players, and b) to compare models' performance scores (i.e., predictive accuracy) to select the best fit. A sample of 260 male youth soccer players from the academies of five different Spanish non-professional clubs completed the follow-up. Players were engaged in a pre-season assessment that covered several personal characteristics (e.g., anthropometric measures), psychological constructs (e.g., trait-anxiety), and physical fitness and neuromuscular measures (e.g., range of motion [ROM], landing kinematics). Afterwards, all LE-ST injuries were monitored over one competitive season. The predictive ability (i.e., area under the receiver operating characteristic curve [AUC] and F-score) of several screening models was analysed and compared to select the one with the highest scores. A total of 45 LE-ST injuries were recorded over the season. The best fit screening model developed (AUC = 0.700, F-score = 0.380) allowed to successfully identify one in two (True Positive rate = 53.7 %) and three in four (True Negative rate = 73.9 %) players at high or low risk of suffering a LE-ST injury throughout the in-season phase, respectively, using a subset of six field-based measures (knee medial displacement in the drop jump, asymmetry in the peak vertical ground reaction force during landing, body mass index, asymmetry in the frontal plane projection angle assessed through the tuck jump, asymmetry in the passive hip internal rotation ROM, and ankle dorsiflexion with the knee extended ROM). Given that these measures require little equipment to be recorded and can be employed quickly (approximately 5–10 min) and easily by trained staff in a single player, the model developed might be included in the injury management strategy for youth soccer.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
巴达天使完成签到,获得积分10
6秒前
江三村完成签到 ,获得积分10
6秒前
量子星尘发布了新的文献求助10
24秒前
CyberHamster完成签到,获得积分10
34秒前
xiaohong完成签到,获得积分10
37秒前
朱比特完成签到,获得积分10
38秒前
39秒前
zmuzhang2019发布了新的文献求助10
45秒前
onestepcloser完成签到 ,获得积分0
45秒前
zoe完成签到 ,获得积分10
46秒前
发嗲的慕蕊完成签到 ,获得积分10
47秒前
Linson完成签到,获得积分10
48秒前
顾矜应助赵三岁采纳,获得10
1分钟前
yyy2025完成签到,获得积分10
1分钟前
木雨亦潇潇完成签到,获得积分10
1分钟前
香蕉觅云应助nine2652采纳,获得10
1分钟前
量子星尘发布了新的文献求助10
1分钟前
芳华如梦完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
1分钟前
土豆丝完成签到 ,获得积分10
1分钟前
琦琦完成签到,获得积分10
1分钟前
zzzz完成签到,获得积分20
1分钟前
GEZIKU完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
赵三岁发布了新的文献求助10
1分钟前
wwb完成签到,获得积分10
2分钟前
2分钟前
2分钟前
肯德基没有黄焖鸡完成签到 ,获得积分10
2分钟前
能干冰露完成签到,获得积分10
2分钟前
牛奶拌可乐完成签到 ,获得积分10
2分钟前
量子星尘发布了新的文献求助30
2分钟前
周小鱼完成签到 ,获得积分10
2分钟前
2分钟前
2分钟前
老张完成签到,获得积分10
2分钟前
2分钟前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038039
求助须知:如何正确求助?哪些是违规求助? 3575756
关于积分的说明 11373782
捐赠科研通 3305574
什么是DOI,文献DOI怎么找? 1819239
邀请新用户注册赠送积分活动 892655
科研通“疑难数据库(出版商)”最低求助积分说明 815022