Purpose: Large changes in workload over short periods of time are known to increase injury likelihood and decrease performance output. Dynamic stress load (DSL), speed intensity (SI), and fatigue index (FI) are 3 GPS-derived variables that can help evaluate efficiency on the field. Additionally, the acute:chronic workload ratio (ACWR) has become crucial in the analysis of physical conditioning and injury risk. In this study, it was utilized to examine the ratios of DSL and its impact on field performance. Comparisons were made between conference and non-conference matches as well as weeks with optimal vs. minimal rest between matches in order to evaluate changes in performance. Methods: Twenty-eight Division 1 female soccer players (Mean ± SD; Age: 20.07 ± 1.36 years, Height: 169.82 ± 5.66 cm, Weight: 64.41 ± 6.2 kg) were recruited for this study. The subjects each wore a GPS device during training sessions and matches. Using StatSports Viper software the devices monitored SI, DSL, and FI. DSL, FI, and SI were chosen as the best indicators of running exertion, fatigue levels, and overall performance. The data was split up into 14 weeks, which included 7 weeks of non-conference play (1-7) and 7 weeks of conference play (8-14); moreover, there were 7 weeks where matches were played on Friday/Sunday (3,5,8,9,10,12,14) and 7 weeks with more time in between matches (1,2,4,6,7,11,13). The values for DSL (the total of weighted impacts above 2x gravity), SI (a weighted score dependent on the time spent at each speed), and FI (DSL/SI) were recorded and the averages were calculated after and graphed to determine relationships. The ACWR for DSL for each week was calculated manually. A paired-samples T-Test was performed to compare the means of DSL ACWR values between conference/non-conference matches and the between-match rest time differences. Results: The average value of SI was 631.87 ± 282.58 SD and it had its highest values of 1,492 and 934 in weeks 1 and 2, due to harder training and not as many matches in the first week of season. No significant difference was found between conference/non-conference and rest time in between matches. The same trend was seen in DSL (807.65 ± 250.07); however, weeks 8 and 10 had the highest values (other than 1 and 2) of 957 and 1,120 (Friday-Sunday match weeks). FI (1.19 ± 0.21) had its highest values in weeks 3, 8, 10, and 12, which were all Friday-Sunday match weeks. DSL ACWR (0.79 ± 0.22) was not significantly different in conference (0.775 ± 0.09) and non-conference match weeks (0.8825 ± 0.15). Friday-Sunday matches (1.01 ± 0.06) vs. other weeks (0.81 ± 0.13) showed a larger mean difference, but was not of statistical significance (p = 0.135). Conclusions: Conference vs. non-conference matches did not show significant differences, which can be attributed to competitive spirit of collegiate athletes. However, the data suggests that playing matches within 48 hours of one another (Friday/Sunday) is more likely to lead to an increase in DSL, FI, and ACWR values for DSL. Practical Applications: Coaches and conference officials are advised to look into increasing the amount of rest time in between matches not only to increase efficiency of the players but also to lessen prevalence and risk of non-contact injuries. Coaches should also be aware of the weekly increases or changes in workload in order to plan accordingly for needed rest periods.
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