Welcome to The Turf Zone Podcast. This episode features the article “How Variability Within and Between Natural Turfgrass and Synthetic Athletic Fields Impacts Athlete Safety and Performance” written by Ava Veith, Dr. David McCall, Dr. Chase Straw, Dr. Daniel Sandor, Dr. Jay Williams, Elisabeth Kitchen, Kevin Hensler, Aaron Tucker and Dr. Caleb Henderson Authors Note and Context Ava Veith is a Ph.D. student in the Department of Plant Science at Penn State University under the advisement of Dr. Chase Straw, where her research focuses on studying within-field variability and athlete–surface interactions. However, the research presented in this article was conducted during her master’s program at Virginia Tech under Dr. David McCall. This study served as a foundational investigation into how variability within and between natural turfgrass and synthetic turf athletic fields influences athletes. The findings from this work have shaped the direction of subsequent doctoral research. Building on this foundation, the planned Ph.D. project aims to examine athlete lower-limb joint biomechanics across natural turfgrass, synthetic turf, and hybrid (natural turfgrass reinforced with synthetic fibers) surfaces using multi-segment inertial measurement units. At the conclusion of this article, the next phase of research will be briefly outlined to demonstrate how it has grown from the master’s study. In this way, the Virginia Tech study presented here represents both a completed project and the starting point for a broader, ongoing effort to better understand how the playing surface can affect athlete movement and injury-relevant mechanics. Introduction A safe playing surface is essential for athletic competition. Natural turfgrass and synthetic turf are common playing surfaces used for field sports, and extensive research has been conducted to compare these two surface types. However, limited attention has been given to within-field variability and its impact on athlete safety and performance. Studies often classify athletic fields broadly as synthetic or natural, overlooking critical surface metrics that fluctuate both within and between fields. Key field characteristics such as surface hardness, rotational resistance, soil moisture, thatch depth, and infill depth (for synthetic fields) play a crucial role in assessing field quality. Variability in these factors can be influenced by environmental conditions, management practices, and field usage patterns. Despite the known importance of these factors, current research often fails to account for field-specific inconsistencies, limiting the effectiveness of broad comparisons between surfaces. To improve field safety and optimize athlete performance, interdisciplinary collaboration among turfgrass scientists, sports scientists, and sports medicine professionals is necessary. Evidence-based field management strategies must be developed to ensure more consistent playing conditions, reducing the risk of injury. Wearable technologies such as STATSports GPS trackers (STATSports, 2025) and ankle inertial measurement units (IMUs) (IMeasureU, 2019) provide critical insights into athlete biomechanics, load monitoring, and more. These technologies allow researchers to quantify how different surface conditions influence athletes during performance, offering valuable data for injury prevention strategies. Beyond data collected by wearable technologies, athlete perceptions of field conditions also play a role in performance and injury risk. Unpredictable surface variability can affect player confidence, movement efficiency, and risk-taking behaviors, making perception-based data collection essential. Understanding how athletes experience and perceive different playing surfaces can inform future improvements in field construction and maintenance. The objective of this study is to quantify the impact of surface variability on athlete safety and performance, both within and between natural turfgrass and synthetic turf surfaces. This research will quantify how variations in key surface metrics, including surface hardness, rotational resistance, soil moisture, thatch depth, and infill depth, affect athletes utilizing data from wearable technologies, such as STATSports GPS trackers and ankle IMUs. Additionally, to further understand the influence of field surfaces, athletes will be surveyed before and after performing drills to gather insights into their perceptions of how surface variability impacts their performance. Methodology Athletic Fields Tested This research was conducted in August of 2024, where four athletic fields on the Virginia Tech campus in Blacksburg, Virginia were studied. Two of these fields were natural turfgrass (bermudagrass), while the other two fields were synthetic turf. For both field types, one field was classified as ‘low usage’, while the other was classified as ‘high usage’. This was determined based on traffic frequency, field age, and management practices. Preliminary Data Collection Before live athletes were introduced, surface hardness was assessed on all four fields using a Clegg hammer, with 100 measurements collected per field. The data were then analyzed using ArcGIS Pro to generate surface hardness heatmaps, highlighting variability between and within each field. These maps allowed us to identify specific locations for the athletes to perform drills, where one selected area within each field was slightly harder than the rest of the field, and the other being slightly softer. Additionally, 20 measurements of rotational resistance (using Deltec’s rotational resistance tester), thatch depth (using a soil profile sampler), soil moisture (using a TDR 350 Soil Moisture Meter), and infill depth (using a Turf-Tec Professional Model Infill Depth Gauge) were taken in both the softer and harder areas to further characterize each field and understand the relationship between surface conditions and athlete performance. Data Collection During Athlete Involvement Fourteen female athletes participated in the study, equipped with STATSports GPS devices (to measure running speed) and ankle IMUs (to measure lower limb impact intensity) to quantify their movements during drills. The athletes were each given new Nike cleats prior to participation to eliminate variation based on cleat configuration. They completed three drills, including a drop landing or drop jump drill, a T-drill, and a modified acceleration-deceleration drill, which were designed to replicate common athletic movements. Each drill was performed three times in both the softer and harder areas identified within each field. Additionally, each athlete completed pre- and post-performance surveys designed to capture their perceptions of field quality before and after completing the drills, providing insight into how different surfaces may have influenced their performance. Results and Discussion Surface Hardness Data Heatmaps highlight surface hardness variability within each studied field. Surface hardness data (n = 100 per field) were analyzed using analysis of variance, and means were separated using Fisher’s protected least significant difference (LSD) test at α = 0.05 to evaluate statistical differences between locations. Both synthetic turf fields had significantly harder surfaces than the natural turfgrass fields (p available in the Spring 2026 issue of Pennsylvania Turfgrass magazine). These measurements (n = 20 per both hard and soft areas within each field) were analyzed using analysis of variance, and means were separated using Fisher’s protected least significant difference (LSD) test at α = 0.05 to evaluate statistical differences between locations. Although the fields tested in this research were not professional-level fields, it is insightful to compare the results with the FIFA natural-pitch rating system (FIFA, 2022). All rotational resistance values fell within FIFA’s ‘excellent quality’ and ‘satisfactory quality’ thresholds, which is important because excessive rotational resistance has been linked to increased lower extremity injuries due to the foot becoming entrapped in the surface during pivoting movements, and too little resistance can increase the risk of slipping. However, soil moisture values exceed 35%, which FIFA classifies as ‘unacceptable quality’. This elevated moisture is likely the primary cause of the low surface hardness values observed on the natural turfgrass fields, which were lower than FIFA’s 70-85 Gmax ‘excellent quality’ range. Additionally, FIFA considers thatch depths over 25 mm as unacceptable, and 10–15 mm satisfactory. Excessive thatch can cause athlete’s cleats to become caught within the surface, increasing knee ligament stress. The low-usage natural turfgrass field had more thatch despite regular maintenance, while the high-usage natural turfgrass field had less, likely due to recent sprigging the summer before. Soft areas in both natural turfgrass fields exhibited higher thatch levels than the hard areas, consistent with previous findings that core cultivation reduces both thatch and surface hardness (McCarty et al., 2007; Atkinson et al., 2012). This supports the understanding that increased thatch can act as a cushioning layer, absorbing impact and thereby reducing surface hardness. The high-usage synthetic turf field exhibited significantly less infill and greater surface hardness compared to the low-usage synthetic turf field, and the soft areas within both synthetic fields had more infill than the hard areas. This aligns with previous research indicating that infill depth decreases with use, which in turn leads to higher surface hardness (Dickson et al., 2022). Additionally, the low-usage synthetic field exhibited greater variability in infill depth between the selected hard and soft areas, likely due to its relatively young age (only one year old at the time of the study). Comp