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An R-Based Landscape Validation of a Competing Risk Model
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Comparison of Concussion Risk Functions Generated from Two Different Datasets.

Madelen Fahlstedt1,2, Shiyang Meng1,3, Declan Patton4

  • 1Division of Neuronic Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.

Stapp Car Crash Journal
|July 8, 2026
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Summary

Concussion risk functions differ significantly between American football and Australian sports datasets. This highlights the critical importance of data selection and collection methods for accurate injury prediction in sports.

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Published on: December 8, 2014

Area of Science:

  • Biomechanics of Sport Injuries
  • Sports Medicine
  • Injury Prevention

Background:

  • Concussion risk functions are crucial for estimating injury likelihood in sports.
  • Existing functions often rely on global kinematics or tissue-level predictors derived from various sports datasets.
  • Large datasets from American football and Australian football/rugby provide valuable kinematic data for concussion research.

Purpose of the Study:

  • To analyze differences between American football and Australian sports concussion datasets.
  • To understand the influence of data source on the development of concussion injury risk functions.
  • To compare kinematic and tissue-based predictors for concussion risk assessment.

Main Methods:

  • Utilized two large datasets of video-verified concussive cases from American football and Australian football/rugby.
  • Applied kinematic data to the KTH head model to develop and compare risk functions.
  • Evaluated accuracy, sensitivity, specificity, and Area Under the Curve (AUC) of the developed risk functions.

Main Results:

  • The two datasets generated distinct concussion injury risk curves.
  • Significant differences were observed in resultant angular velocity between datasets, with American football cases showing more coronal plane rotation.
  • The Australian dataset predicted a lower 50% risk of concussion compared to the American football dataset.

Conclusions:

  • The choice of input data significantly impacts the development and output of concussion injury risk functions.
  • Methodological improvements in sampling and data collection are necessary for developing more reliable and valid injury risk models.
  • Understanding sport-specific kinematic differences is vital for accurate concussion risk assessment.