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Regression Toward the Mean

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...

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Updated: Jun 20, 2025

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

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Published on: May 26, 2020

A Change-Point Method to Detect Meaningful Change in Return-to-Sport Progression in Athletes.

Kate K Yung^1,2,3, Ben Teune¹, Clare L Ardern^4,5

¹Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia.

International Journal of Sports Physiology and Performance

|July 17, 2024

Summary

The change-point method effectively identifies key recovery milestones in athletes following injury. This analysis of wellness and performance data aids clinicians in understanding the rehabilitation process and return-to-sport progression.

Keywords:

complex systems decision making machine learning nonlinearity return to play time-series analysis

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Published on: May 26, 2020

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Published on: December 8, 2014

A Multi-Modal Approach to Assessing Recovery in Youth Athletes Following Concussion

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Published on: September 25, 2014

Area of Science:

Sports Medicine
Rehabilitation Science
Data Analysis

Background:

Athletes often sustain lower-limb muscle injuries during high-speed activities.
Rehabilitation requires careful monitoring of various physiological and performance metrics.
Identifying critical junctures in recovery is essential for safe return to play.

Purpose of the Study:

To investigate the application of the change-point method for analyzing longitudinal data in athlete rehabilitation.
To detect significant changes (change points) during the recovery process.

Main Methods:

A prospective, single-case observational study design was employed.
A professional football player with an acute lower-limb muscle injury was monitored.
Four wellness metrics and five running-performance metrics were collected throughout rehabilitation.

Main Results:

Univariate analysis identified distinct change points for individual wellness metrics (stress, sleep, mood, soreness) and performance metrics (distance, acceleration, speed, deceleration).
Multivariate analysis revealed a common change point for wellness metrics (day 50) and performance metrics (day 67).
Data collection spanned 130 days, capturing the athlete's progression.

Conclusions:

The change-point method offers valuable insights into the timing and sequence of recovery markers.
Multivariate analysis provides a consolidated view of recovery, aiding clinical decision-making.
This method can help clinicians integrate and visualize data for evaluating an athlete's return-to-sport trajectory.