BACKGROUND: Global positioning system (GPS) data, when obtained from athletes offers unique information on their performance. Given the information GPS data provides, it is important to identify data most pertinent to an athlete`s performance. OBJECTIVE: We evaluated a GPS-based running quality variable to predict the variance in total player load (TPL) and player load per minute (PLPM) from female soccer player (n= 26) data. METHODS: Running quality was the ratio of the displacement per minute to total distance covered. TPL was quantified as the sum of velocity change rates in all three planes of motion, while PLPM was a ratio of load generated per minute of activity. RESULTS: With a logarithmic transformation of TPL data, a Pearson Product Moment Correlation analysis revealed running quality accounted for significant (r=-0.65) amounts of our criterion`s variance, which implied higher running quality led to lower log (TPL) values. With PLPM as our dependent variable, running quality correlated with significant (r= 0.63) amounts of our criterion`s variance. CONCLUSIONS: Movement efficiency appears to be an important contributor to our correlations. We suggest running quality be examined as a correlate to performance in other sports in which running is crucial to success.
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