Featured Projects
Featured Projects
Team members from the HERO Initiative lead a diverse and large array of university- and community-based activities designed to promote peak performance, including basic and applied research, lecture-based and hands-on coursework, direct provision of services, and the development of innovative programming for groups and organizations.
Recent activities include the following presentations at the National Strength and Conditioning Association (NCSA) annual meeting:
1. Influence of temperature on performance characteristics during competition in soccer. Soccer players are exposed to various environments during outdoor play, thereby increasing their risk of heat-related performance decrements. PURPOSE: To examine the effects of heat stress on characteristics of performance during collegiate soccer matches. METHODS: Global positioning system (GPS) data from female soccer players within a Midwestern NCAA Division-I soccer program were collected during the 2023 regular season. All players were instructed to wear the GPS tracking system with the capability of heart rate (HR) monitoring throughout all the 18 games. All data were collected continuously, regardless of if players were substituted in or out of play, therefore all data were made relative to minutes played. Matches were further categorized into thirds based on temperature. Matches with temperatures exceeding 75°F were considered high heat, while matches with temperatures between 60 – 74°F were moderate heat, and temperatures less than 60°F were categorized as low heat. GPS data were then divided into 1st and 2nd halves for players who averaged more than 20 minutes of playing time over the course of the season. The performance characteristics measured were number of sprints, percent of time spent running at low speed (LSR) zones and high speed (HSR) zones (≥15 km/hr), total time spent in low heart rate (LHR) zones and high HR (HHR) zones (≥80% of HR reserve), total distance covered (TDC), and training load (TL). Repeated measures analysis of variance was used to analyze differences between the half and temperature category (High vs low heat) with an alpha (α) set at ≤0.05. Post-hoc paired sample t-test were performed to further elucidate interactions. Results: A significant interaction was observed for the number of sprints (F=5.449, p=0.038) and duration of time spent within the HHR zone (F= 6.67, p=0.024). Post hoc comparisons indicated that the number of sprints completed in the 2nd half of the high heat matches were reduced when compared to the first half of the high heat matches (p=0.018), and the 2nd half of low heat matches (p=0.019). Additionally, data indicated that the time spent running in HHR zones during the 2nd half of the low temperature matches was lower than that of the 1st half (p=0.011). Main effects of temperature indicate greater time HSR zones (F= 5.73, p=0.034) and in TL (F=6.40, p=0.026) in low temperatures compared to high temperatures. Main effects for half indicate more time spent in the L-HR zones (F= 34.3, p ≤ 0.001) during the 2nd half. Conclusion: The number of sprints performed was lower in high temperature matches while the duration of time spent in HHR zones was higher in high temperature matches. Practical Application: Coaches may utilize this information to optimize training loads leading to competition with higher temperatures. AUTHORS: Safwan Barnawi, Ryan W Gant, Clayton Lavign, Adam R Jajtner, Meghan K Magee
2. Influence of Rest on Running Characteristics during Soccer Competition. Recovery is an important component to any well-designed training program; however, competition schedules are rigid and do not allow for additional rest should an athlete need it. PURPOSE: Examine the influence of different rest periods between competitions on various workload metrics in collegiate female soccer players. METHODS: Global positioning system (GPS) data obtained by the coaching staff of a Midwestern NCAA Division I women’s soccer program was retrospectively examined. Players wore the GPS integrated with heart rate (HR) analysis during all games through the 2023 season. Data from all 18 regular season matches were separated into games played with three (3DAY; n=8) or four or more (4+DAY; n=10) days of rest, then separated into first and second half. During each game, data was collected continuously on all players regardless of whether they were playing at that time, though only data from players who averaged more than 20 minutes of playing time over the course of the season was included. Data consisted of total number of sprints, sprinting distance, percent of time spent running above (HSR) and below (LSR) 15 km·hr-1, percent of time spent above (HR-HIGH) and below (HR-LOW) 80% HR reserve, total distance and training load (TL). All variables were made relative to the total playing time for each individual player, which exaggerated time proportions in HR-HIGH and HR-LOW due to continuous data collection. Data were analyzed using a 2x2 (rest x half) repeated measures Analysis of Variance with least significant difference pairwise comparisons (α ≤ 0.05). RESULTS: No rest x half interactions were observed for any variables, however, main effects for rest were observed for the number of sprints (F= 10.69; p = 0.007) and HSR (F= 21.49; p = 0.001), while a non-significant main effect was shown for TL (F= 3.33; p = 0.093). Pairwise comparisons indicate all variables were greater following 4+DAY relative to 3DAY (Table 1). Main effects for half were observed for the number of sprints (F= 6.68; p = 0.024), LSR (F= 6.92; p = 0.022), HSR (F= 7.33; p = 0.019), HR-LOW (F= 40.46; p < 0.001), HR-HIGH (F= 5.83; p = 0.033) and total distance (F= 9.00; p = 0.011). The number of sprints, LSR, HSR, HR-HIGH, and total distance were reduced in the second half, while HR-LOW was increased (Table 1). CONCLUSION: Data indicate players increase high intensity external workloads with at least one more day of rest and may also be capable of greater training loads with more rest. Moreover, external workloads decrease over the course of a game, with increased time spent in lower intensity HR zones. PRACTICAL APPLICATIONS: Practitioners should continue to identify and recommend strategies that may aid in the recovery between games, while also seeking strategies that may be used to combat the decline in performance over the course of a game. AUTHORS: Adam R Jajtner, Clayton Lavign, Meghan K Magee
3. Competitive Surfaces’ Influences on NCAA D-I Soccer Performance.
Soccer fields vary in composition, with different surfaces purported to influence player performance. PURPOSE: To compare various measurements of performance metrics in collegiate female soccer players during competitions on natural grass and artificial turf surfaces. METHODS: Global Positioning Devices (GPS) were worn by players on a D-I Midwestern Women’s Soccer Team during 18 matches throughout the 2023 season. Match data were taken from 10 away matches and segmented into competitions on natural grass (n = 5) or artificial turf (n=5). Data were then further split into first and second halves of matches. GPS data were assessed for the total number of sprints (# sprints), sprint distance (in meters), time spent in low (LSR; < 15km/hr.) and high-speed (HSR; ≥ 15 km/hr.) running zones, low (LHR; < 80% HRR) and high (HHR; ≥ 80% HRR) heart rate zones, total distance (in meters), and training load (TL). Measurements were adjusted to be relative to the number of minutes played, with only players averaging more than 20 min per game throughout the season included in the analysis. A 2x2 (surface x half) repeated measures analysis of variance was employed to assess differences within matches. Additionally, significant interactions were further teased apart by using least significant differences (LSD). Alpha (ɑ) was set to 0.05. RESULTS: Data indicate an interaction for total distance (F = 21.887, p < 0.001) showing less distance covered on natural grass during the 1st half (p = 0.008), while reductions in total distance from the 1st to 2nd half on natural grass (p = 0.043) and turf (p < 0.001) were also observed. Differences were observed for time spent in LHR (F = 26.019, p < 0.001). with more time was spent in LHR zones during natural grass matches than turf during the 1st half (p < 0.001). Differences were also observed for time spent in HHR zones (F = 7.416, p = 0.021) with more time spent in HHR zones on matches played on artificial turf compared to grass during the 1st half (p = 0.012). Comparatively, more time spent in HHR zones was observed during grass matches compared to artificial turf during the 2nd half of games (p = 0.033). An interaction was observed for time spent in LSR zones (F = 14.536, p = 0.002), which revealed more time spent in LSR zones during grass matches compared to artificial turf matches during the 1st half (p = 0.041), with a significant difference in time spent in LSR zones during grass matches compared to artificial turf matches during the 2nd half (p = 0.034). Differences were also observed for time spent in HSR zones (F = 11.775, p = 0.005) with matches on artificial turf resulting in more time spent in HSR zones in the 1st half (p = 0.004). CONCLUSION: Data suggest increased workload during matches played on natural grass when compared to artificial turf. PRACTICAL APPLICATION: Coaches can use these data to adjust training loads prior to matches as match surface can influence workloads, and thereby influence performance. AUTHORS: Max DiPierro, Ryan Gant, Clayton Levigne, Adam Jajtner, Meghan Magee