DOI: 10.57760/sciencedb.18023
title: Performance profiles of national premier-level women football players: Examining performance characteristics of top half vs bottom half teams
title: Performance profiles of national premier-level women football players: Examining performance characteristics of top half vs bottom half teams

description: Participants:Sample Size: 87 players from 8 teams.Groups: Players were divided into two groups based on league standings:Top-Half Teams (n = 53).Bottom-Half Teams (n = 34).Inclusion Criteria:Active players participating in at least three training sessions per week.Age: 16–35 years.Exclusion Criteria:Recent muscular injuries (within the last 3 months).Significant bone, tendon, or ligament injuries (within the last 6 months).Measures:Anthropometric Measures:Body mass and height.Skinfold calipers (8-site sum) for body composition.Performance Tests:Speed:10m and 30m sprints using timing gates.Power:Countermovement Jump (CMJ) and Depth Jump (DJ) Reactive Strength Index (RSI) measured on a force plate.Strength:Isometric Mid-Thigh Pull (IMTP) to assess absolute and relative peak force.Endurance:Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1).Other Measures:Relative strength normalized to body mass.Rate of Force Development (RFD) during the IMTP.Procedures:Preparation:Participants abstained from vigorous activity for 48 hours before testing.A standardized warm-up routine was performed before assessments.Testing Protocols:Field tests (sprints and Yo-Yo IR1) conducted on artificial turf with football boots.Laboratory tests (CMJ, DJ, IMTP, and anthropometric measurements) conducted in controlled conditions (22°C, 20% humidity).Data Collection:Three trials conducted per test, with the best result used for analysis.Equipment calibrated before each session.Analysis Plan:Statistical Tests:Descriptive Statistics: Means and standard deviations for all measures.Comparative Analyses: Independent t-tests to compare top and bottom teams.Correlation Analyses: Pearson’s correlation to explore relationships between variables.Effect Sizes: Cohen’s d for assessing the magnitude of differences.Software: IBM SPSS Statistics (v29.0.2.0).Ethical Considerations:Ethical approval was granted by St. Mary’s University, London.Written informed consent obtained from participants (and guardians for minors).Data anonymized to protect participant confidentiality.
description: Participants:Sample Size: 87 players from 8 teams.Groups: Players were divided into two groups based on league standings:Top-Half Teams (n = 53).Bottom-Half Teams (n = 34).Inclusion Criteria:Active players participating in at least three training sessions per week.Age: 16–35 years.Exclusion Criteria:Recent muscular injuries (within the last 3 months).Significant bone, tendon, or ligament injuries (within the last 6 months).Measures:Anthropometric Measures:Body mass and height.Skinfold calipers (8-site sum) for body composition.Performance Tests:Speed:10m and 30m sprints using timing gates.Power:Countermovement Jump (CMJ) and Depth Jump (DJ) Reactive Strength Index (RSI) measured on a force plate.Strength:Isometric Mid-Thigh Pull (IMTP) to assess absolute and relative peak force.Endurance:Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1).Other Measures:Relative strength normalized to body mass.Rate of Force Development (RFD) during the IMTP.Procedures:Preparation:Participants abstained from vigorous activity for 48 hours before testing.A standardized warm-up routine was performed before assessments.Testing Protocols:Field tests (sprints and Yo-Yo IR1) conducted on artificial turf with football boots.Laboratory tests (CMJ, DJ, IMTP, and anthropometric measurements) conducted in controlled conditions (22°C, 20% humidity).Data Collection:Three trials conducted per test, with the best result used for analysis.Equipment calibrated before each session.Analysis Plan:Statistical Tests:Descriptive Statistics: Means and standard deviations for all measures.Comparative Analyses: Independent t-tests to compare top and bottom teams.Correlation Analyses: Pearson’s correlation to explore relationships between variables.Effect Sizes: Cohen’s d for assessing the magnitude of differences.Software: IBM SPSS Statistics (v29.0.2.0).Ethical Considerations:Ethical approval was granted by St. Mary’s University, London.Written informed consent obtained from participants (and guardians for minors).Data anonymized to protect participant confidentiality.