Regular- and postseason comparisons of playing time and measures of running performance in NCAA Division I women soccer players

Abstract

The management of playing time in National Collegiate Athletic Association (NCAA) soccer athletes may be a key factor affecting running performance during competition. This study compared playing time and running performance between regular-season and postseason competitions during a competitive women's soccer season. Nine NCAA Division I women soccer players (age, 21.3 ± 0.9 years; height, 170.3 ± 5.7 cm; body mass, 64.0 ± 5.8 kg) were tracked using portable GPS devices across 21 games during a competitive season (regular season (n = 17); postseason (n = 4)). Movements on the field were divided into operationally distinct thresholds defined as standing/transient motion, walking, jogging, low-speed running, moderate-speed running, high-speed running, sprinting, low-intensity running, and high-intensity running. A significant increase in minutes played (+17%, p = 0.010) was observed at postseason compared with the regular season. Concomitant increases in time spent engaged in low-intensity running (LIR: +18%, p = 0.011), standing/transient motion (+35%, p = 0.004), walking (+17%, p = 0.022), distance covered while walking (+14%, p = 0.036), and at low intensity (+11%, p = 0.048) were observed. Performance comparisons between the first and second half within games revealed a significant decrease (p ≤ 0.05) in high-speed and high-intensity runs during the second half of the postseason compared with the regular season. Changes in minutes played correlated significantly with changes in absolute time spent engaged in LIR (r = 0.999, p < 0.001), standing/transient motion (r = 0.791, p = 0.011), walking (r = 0.975, p = 0.001), jogging (r = 0.733, p = 0.025), distance covered while walking (r = 0.898, p < 0.001) and low-intensity activity (r = 0.945, p < 0.001). Negative correlations were observed between minutes played and absolute time sprinting (r = -0.698, p = 0.037) and distance covered sprinting (r = -0.689, p = 0.040). Results indicate that additional minutes played during the postseason were primarily performed at lower intensity thresholds, suggesting running performance during postseason competitions may be compromised with greater playing time in intercollegiate women's soccer.

Physical Demands of Women's Soccer Matches: A Perspective Across the Developmental Spectrum

“…Interestingly, there was no impact of poor sleep on match demands in these players (Turczyn, 2018). In contrast to the impact of match schedule, no differences were observed for high-speed or sprint distances between NCAA Division I regular-season and playoff matches (Wells et al, 2015), suggestive that players were able to continue playing with similar intensity throughout an entire season. Overall, these studies highlight how contextual factors might impact game demands for female college soccer players and the need to monitor these metrics in order to manage the physical demands players experience during the season.…”

“…So, researchers tend to either include players that competed in full matches (which limits the sample size) or "create" 90-min matches from multiple players (which tends to alter movement rates). This is evident from a study comparing Division I regular season and post-season matches, which showed a 10% increase in total distance with a corresponding 6.5% decrease in movement rate (Wells et al, 2015). Nevertheless, total distances reported for NCAA Division I (∼9,000-9,900 m) (McCormack et al, 2014;Vescovi and Favero, 2014;Sausaman et al, 2019), Division II (∼10,000) (Gentles et al, 2018), Division III (∼9,600-9,800 m) (Jagim et al, 2020) as well as Canadian University matches (∼8,800-9,600 m) (Turczyn, 2018) are fairly similar, with subsequent movement rates of ∼100-110 m/min.…”

“…Nevertheless, total distances reported for NCAA Division I (∼9,000-9,900 m) (McCormack et al, 2014;Vescovi and Favero, 2014;Sausaman et al, 2019), Division II (∼10,000) (Gentles et al, 2018), Division III (∼9,600-9,800 m) (Jagim et al, 2020) as well as Canadian University matches (∼8,800-9,600 m) (Turczyn, 2018) are fairly similar, with subsequent movement rates of ∼100-110 m/min. Despite slightly different velocity thresholds used to define high-intensity running, it seems that when the velocity band spans only 3-4 kph the amount of distance covered is within a range of ∼600-800 m (Vescovi and Favero, 2014;Wells et al, 2015;Ramos et al, 2017;Turczyn, 2018;Jagim et al, 2020) with a notable exception reaching ∼1,000 m (Sausaman et al, 2019). For sprint distances, increasing the lower limit velocity threshold from 18 to 19 kph (∼280-420 m) (Alexander, 2014;Sausaman et al, 2019;Jagim et al, 2020;McFadden et al, 2020) to 20 kph (∼200-250 m) (Vescovi and Favero, 2014;Ramos et al, 2017) and 22 kph (<100 m) (Wells et al, 2015) has the expected reduction of reported distances.…”

“…Despite slightly different velocity thresholds used to define high-intensity running, it seems that when the velocity band spans only 3-4 kph the amount of distance covered is within a range of ∼600-800 m (Vescovi and Favero, 2014;Wells et al, 2015;Ramos et al, 2017;Turczyn, 2018;Jagim et al, 2020) with a notable exception reaching ∼1,000 m (Sausaman et al, 2019). For sprint distances, increasing the lower limit velocity threshold from 18 to 19 kph (∼280-420 m) (Alexander, 2014;Sausaman et al, 2019;Jagim et al, 2020;McFadden et al, 2020) to 20 kph (∼200-250 m) (Vescovi and Favero, 2014;Ramos et al, 2017) and 22 kph (<100 m) (Wells et al, 2015) has the expected reduction of reported distances. Investigators have also examined the impact of contextual factors (e.g., altitude, match frequency, etc.)…”

Trends in Recurrent Anterior Cruciate Ligament Injuries Differ From New Anterior Cruciate Ligament Injuries in College and High School Sports: 2009-2010 Through 2016-2017

“…11 Increased risk of recurrent injury during postseason implies slightly different risk factors for recurrent injuries compared with primary injuries, which occur most often during regular season across all collegiate divisions. 20 Postseason often requires a different type of play, such as increased number of minutes played 41 and increased perceptual strain during similar work, 28 which may heighten the risk of recurrent ACL injury. Sports performance and medical staff may need to consider injury history during postseason.…”