Countermovement Jump Force‐Time Mechanics Differentiate ACL Injury Status in Elite Alpine Ski Racers.

Biomechanical assessments of stretch‐shortening cycle (SSC) movements such as the countermovement jump (CMJ) are used to evaluate neuromuscular function in alpine ski racers after anterior cruciate ligament reconstruction (ACLR). However, this analysis yields multiple CMJ force‐time metrics that qua...

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Published in:Scandinavian Journal of Medicine & Science in Sports (John Wiley & Sons, Inc.) Vol. 36; no. 4; pp. 1 - 12
Main Authors: Morris, Nathaniel, Torres, Ricardo da Silva, Heard, Mark, Baker, Patricia Doyle, Herzog, Walter, Jordan, Matthew J.
Format: equations & formulas research tables/charts Journal Article
Published: John Wiley & Sons, Inc. Apr2026
Online Access:View this record in EBSCOhost
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      jtl: Scandinavian Journal of Medicine & Science in Sports (John Wiley & Sons, Inc.)
      issn: 16000838
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      dt: Apr2026
      vid: 36
      iid: 4
      pid: 52269
      pub: John Wiley & Sons, Inc.
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        10.1111/sms.70270
        193164276
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        atl: Countermovement Jump Force‐Time Mechanics Differentiate ACL Injury Status in Elite Alpine Ski Racers.
      aug:
        au:
          Morris, Nathaniel
          Torres, Ricardo da Silva
          Heard, Mark
          Baker, Patricia Doyle
          Herzog, Walter
          Jordan, Matthew J.
        affil: Integrative Neuromuscular Sport Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary Alberta,, Canada
      sug:
        subj:
          Jumping
          Resistance Training Classification
          Biomechanics
          Anterior Cruciate Ligament Injuries Rehabilitation
          Athletes, Elite Psychosocial Factors
          Snow Skiing
          Athletic Performance
          Machine Learning Algorithms Utilization
          Classification Algorithms
          Athletic Injuries Risk Factors
          Risk Assessment
          Human
          Comparative Studies
          Random Forest
          Support Vector Machine
          Logistic Regression
          T-Tests
          ROC Curve
          Anterior Cruciate Ligament Reconstruction
          Sports Re-Entry
          Decision Making
          Descriptive Statistics
          Data Analysis Software
      ab: Biomechanical assessments of stretch‐shortening cycle (SSC) movements such as the countermovement jump (CMJ) are used to evaluate neuromuscular function in alpine ski racers after anterior cruciate ligament reconstruction (ACLR). However, this analysis yields multiple CMJ force‐time metrics that quantify SSC mechanics, creating challenges for data synthesis, interpretation, and return‐to‐sport decision making. Machine learning (ML) classification algorithms address this problem by determining patterns that distinguish healthy control athletes and athletes recovering from ACLR. ML classification algorithms were trained using CMJ force‐time metrics obtained from healthy control elite alpine ski racers (Control) and skiers tested after ACLR to identify features predictive of group membership. Participants (ACLR: n = 24, Control: n = 42) performed multiple CMJ testing sessions as part of a longitudinal athlete monitoring program (n = 836). ML algorithms (random forest, support vector machine, logistic regression, naïve Bayes, k‐nearest neighbors) were trained using 23 CMJ force‐time features with 5‐fold cross‐validation and evaluated using an independent test dataset. Classification performance was high with balanced accuracies ranging from 0.59 to 0.88 and areas under the receiver operating characteristic curve of 0.63–0.95. Features corresponding to the propulsion phase were most important for differentiating CMJ tests from ACLR and Control athletes. Recovery of neuromuscular function after ACLR may be inferred when the CMJ mechanics of athletes with ACLR become indistinguishable from those of healthy controls. In conclusion, ML classification models may assist interpretation of CMJ force‐time metrics after ACLR by identifying high‐information features related to injury status along with a potential indication of rehabilitation progression relative to healthy control athletes.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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