Related Experiment Video
Updated: Jun 18, 2025
06:52
An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
Published on: May 26, 2020
7.9K
Is Travel Associated With Match Performance in Elite North American Professional Soccer? An Exploratory Study
Garrison Draper1,2, Paul Chesterton1, Matthew David Wright1
1School of Health and Life Sciences, Teesside University, Middlesbrough, United Kingdom.
Summary
Elite soccer teams traveling more accumulate higher player exertion but fewer team points. Cumulative travel impacts performance, suggesting further research into travel
Area of Science:
- Sports Science
- Exercise Physiology
- Soccer Performance Analysis
Background:
- Travel fatigue is known to affect cognitive and physiological systems.
- The specific impact of travel on elite soccer match performance remains unclear.
Purpose of the Study:
- To explore the association between travel and match outcomes in elite North American soccer.
- To investigate how travel metrics correlate with team and player performance.
Main Methods:
- Retrospective observational study analyzing travel data and match outcomes (points, goals) from 26 elite professional soccer teams.
- Data included 148 team matches and 1252 player matches, examining correlations between performance and acute/cumulative travel metrics.
Main Results:
- Cumulative travel (distance, time, time away) positively correlated with high-intensity running in both team and individual players.
- Cumulative time away was negatively associated with team points and positively associated with goals conceded.
- No significant association was found between acute travel metrics and match outcomes or physical performance.
Conclusions:
- Increased cumulative travel in elite soccer is linked to greater player exertion but diminished team rewards (points).
- The observed associations, while small, suggest that cumulative travel may negatively impact team performance.
- Further research is warranted to explore the cumulative effects of travel on soccer performance.
Related Concept Videos
01:04Social Facilitation
31.9K
Not all intergroup interactions lead to negative outcomes. Sometimes, being in a group situation can improve performance. Social facilitation occurs when an individual performs better when an audience is watching than when the individual performs the behavior alone. This typically occurs when people are performing a task for which they are skilled.
31.9K
01:10Standard Deviation
16.0K
The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more variation.
16.0K
01:23Motion of a Projectile
764
Projectile motion becomes evident when a player kicks the ball into the air. The launch angle, or the angle at which the ball is kicked, plays a crucial role in determining the trajectory of the projectile. As the ball soars through the air, influenced solely by gravity, its motion can be dissected into two independent velocity components: the horizontal and the vertical.
Horizontal motion, governed by the initial kick, maintains a constant velocity throughout the flight of the soccer ball.
Horizontal motion, governed by the initial kick, maintains a constant velocity throughout the flight of the soccer ball.
764
01:09Wilcoxon Signed-Ranks Test for Matched Pairs
111
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
111
01:12Coefficient of Correlation
6.1K
The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
6.1K
01:17Sign Test for Matched Pairs
121
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
To conduct the sign test, we first calculate the differences in...
121