Examining Relationship Between Firstbeat Sports Movement Efficiency Index and Standard Fitness Testing Outcomes in Football

Abstract

In today’s top-level football, interest in training load monitoring is continuously increasing. Coaches and sport scientists want to understand how to enhance their team’s performance while simultaneously preventing injuries and illnesses. Fitness tests have been used for decades to describe changes in endurance fitness, but at the top level, where more and more games are played, it is difficult to find time for traditional maximal effort fitness tests. This Master’s thesis was commissioned by Firstbeat Technologies. The objective of the study was to examine the relationship between the Firstbeat Movement Efficiency Index and standard fitness test outcomes. The aim was to explore whether it is possible to predict standard fitness test outcomes based on a variable that can be calculated from collected training load data, without the need for specific fitness testing. Twenty-one competitive amateur male football players were monitored during the competitive season. In this observational, non-experimental study, participants completed Submaximal Fitness Tests 13 times, and a 1200-meter Shuttle Run Test four times. All football sessions were monitored using Firstbeat Sports sensors to collect both internal and external training load data. Correlation and regression analyses were conducted to examine the relationships between the Movement Efficiency Index and fitness test outcomes. The Movement Efficiency Index showed a significant positive correlation with maximal aerobic speed (r = .475, R² = .23, p = .001) and significant negative correlations with the average heart rate during the final 30 seconds of the submaximal fitness test (r = –.562, R² = .32, p < .001; r = –.668, R² = .45, p < .001), both in absolute and relative values, respectively. The findings suggest that the Firstbeat Movement Efficiency Index can be used as a proxy indicator of aerobic fitness in within-player evaluations, especially when standard fitness testing is not feasible—for example, during congested fixture periods. It can also complement the results of less strenuous testing, such as submaximal fitness tests, by helping to infer trends in fitness status.