ECSS Paris 2023: CP-AP13
INTRODUCTION: With the increasing professionalisation and rising physical demands in women`s football, the need for accurate load management is evident (1). Athlete monitoring, through the systematic collection, analysis, and application of workload data alongside athletes’ training responses and wellbeing, is a well-established approach for optimising performance and mitigating injury risk (2) . With occurring recommendations on monitoring methods in women’s football, it is important to characterise potential gaps with real-life practices (3,4). However, little is known about current practices and key stakeholder’s perceptions in women`s football. Therefore, the present study aims to examine monitoring practices and perceptions among (i) players and (ii) coaching and performance staff. METHODS: A descriptive cross-sectional survey design was used. All cubs from the Norwegian women’s premier league were invited to complete a role-specific online survey on their data collection methods, data analysis, implementation and evaluation of their current monitoring practice. Eight clubs participated, eliciting responses from six head coaches, eight practitioners, and 113 players. RESULTS: Five clubs (62.5%) reported systematic monitoring. All five included subjective measures, four collected external loads, while one club measured counter movement jump-test. On perceived individualisation of training load (scale 1–7), monitoring players and staff reported median scores of 5 and 6, respectively, whereas non-monitoring players and staff reported median scores of 4 and 2. The most frequently reported challenges were “players not responding” for data collection, “time constraints” for data analysis, and “lack of equipment” and “tactical considerations” for decision on load adjustment. CONCLUSION: In this cohort, athlete monitoring is widely accepted but implemented heterogeneously and constrained by available resources. Findings on perceived individualisation generate the hypothesis that implementing monitoring may support perceived individualisation, with visible use of data and good communication acting as key facilitators. Future research should further investigate the acute and chronic effects of implementing monitoring, clarify the practical value of objective readiness measures, and identify which monitoring methods and variables that support coaches when making decisions on training load adjustments. References: 1 FIFA, 2020. 2 Gabbett et al., 2017. https://doi.org/10.1136/bjsports-2016-097298 3 Beato et al., 2024. https://doi.org/10.1123/ijspp.2023-0405 4 Coutts, 2017. https://doi.org/10.1123/ijspp.2017-0455
Read CV Miriam BybergECSS Paris 2023: CP-AP13
INTRODUCTION: Duty factor (DF) is a simple marker of movement strategy, defined as the ratio of ground contact time to stride time during running.1 Athletes who adopt aerial-based running patterns (low DF) receive increased biomechanical loads on the foot, ankle, and calf muscles whereas terrestrial-based runners (high DF) place increased load on knees and hips. Given football players typically run 9-11 km in matches, including 111-255 m of sprinting,2 there is a need to better understand loading patterns regarding implications for optimal training regimens. The aim of this study was twofold: (1) to create a method that practitioners could implement easily into training routines and (2) to categorise running styles remotely during the maximum velocity phase of a controlled sprint. METHODS: 53 football players across the Women’s Pro Game Academy League performed controlled sprints as part of their normal training routine across the 2024-25 season (161 observations total; 3.0 ± 1.5 per player). As minimal disruption to training was prioritised, a method was needed to automatically detect the maximum velocity phase while considering different routines in place at each club (e.g., 30 m or 40 m sprints, repeated sprints). An algorithm (RStudio, Posit Software, Boston, MA) was created to automatically detect the start and end times of the maximum velocity phase of the controlled sprints from 10-Hz acceleration, velocity, and distance data from a foot-mounted inertial measurement unit (Playermaker, London, UK), already in use in training by clubs. These times were manually entered into the Playermaker dashboard, which allowed the mean contact time and stride time to be calculated for the entered bout. Contact time and stride time were adjusted using a prior validation study comparing the F-IMU system with an instrumented treadmill and used to calculate DF. DF values were used to identify two separate groups (high and low DF) and to compare between playing positions. RESULTS: Results showed low DF (0.290 ± 0.016) and high DF (0.330 ± 0.015) groups achieved similar maximal sprint speeds (6.59 ± 0.41 m·s-1 and 6.61 ± 0.48 m·s-1, respectively), indicating that DF reflects movement strategy and leg stiffness rather than sprinting ability. Playing position itself did not meaningfully influence DF, with substantial variation in sprinting styles existing within positions (e.g., central [0.258-0.351] vs wide [0.268-0.330] defenders). CONCLUSION: This study provided a novel proof of concept for assessing running styles across several Women’s Pro Game Academies during the maximum velocity phase of a controlled sprint. DF can help contextualise sprint exposure beyond velocity metrics when individualising training. In team sports where there is limited time, this offers one method of monitoring running styles with minimal burden to practitioners. 1. Hanley et al. (2022). Frontiers in Sports and Active Living, 4:939676 2. Savolainen et al. (2023). Biology of Sport, 40(4):1187–1195
Read CV Claire ChaissonECSS Paris 2023: CP-AP13
INTRODUCTION: The pace of play is widely seen as a benchmark metric for level of play and thereby for the evolution of a sport. As elite women’s football has undergone professionalization in recent years, it is commonly assumed that these developments should be reflected in faster match play. However, empirical evidence for a progressive acceleration in women’s football remains limited and methodologically inconsistent. This study examined (1) whether different pace definitions (a tactical–cognitive perspective distinct from physical intensity or running demands) produce systematically different estimates of match pace, and (2) whether pace of play in elite women’s football has changed across recent international tournaments. METHODS: Event data from the FIFA Women’s World Cups (2019, 2023) and the UEFA Women’s European Championships (2022, 2025) were analysed. Pace of play was quantified using four established possession-based metrics: passes per minute, meters per second per touch, time to pass, and meters per second. Linear mixed-effects models were fitted with year (centred) and pace metric as fixed effects, while competition and match were included as random intercepts to account for hierarchical data structure and contextual variability. RESULTS: The mixed linear model revealed significant method effects (all p < 0.001) but no temporal trend across seasons (β = -0.003, p = 0.848). Passes per minute yielded substantially higher pace estimates (β = 9.644) compared to the baseline (meters per second), while time-to-pass showed the largest negative deviation (β = -13.002), and meters per second per touch showed moderate negative deviation (β = -6.778). Substantial variance existed at both competition (Var = 0.065) and match levels (Var = 0.145), indicating meaningful heterogeneity in pace across competitions and individual games beyond what the different pace measures and progress in years could explain. CONCLUSION: These findings demonstrate that pace measurement is highly method-dependent, with different calculations capturing distinct aspects of match pace. Our findings suggest that women's football maintained relatively stable pace characteristics between 2019-2025, contradicting expectations of acceleration as the sport professionalizes. As women’s football matures tactically, improvements may primarily manifest through enhanced control, decision-making, and possession quality rather than pace itself. Simultaneously, co-evolving defensive organization may produce offsetting effects, producing a dynamic tactical balance while pace remains stable. The substantial between-match and between-competition variance suggests that contextual factors (e.g., match importance, tactical approaches) may drive pace variation more than secular trends. Future research should develop theoretically-grounded pace frameworks that clarify which measurement approaches best capture specific tactical intentions, and examine match-level moderators that explain the observed variance in pace of play.
Read CV Jiangyan YangECSS Paris 2023: CP-AP13