Author(s): SPENCER, K., APPADURAI, S., RUSSEL, P. , Institution: AUCKLAND UNIVERSITY OF TECHNOLOGY, Country: NEW ZEALAND, Abstract-ID: 1704

INTRODUCTION:
This study examines external workload of field hockey umpires in New Zealand, investigating relationships between physical characteristics, injury history, and workload demands. Limited research exists on field hockey umpire workload analysis in New Zealand, creating gaps in understanding how umpire characteristics affect performance.
METHODS:
Using GPS and Playermaker devices, data from 17 umpires officiating 30 matches during a six-day national tournament were analysed. Mixed-effects modelling addressed data dependencies to identify significant relationships in distance covered, top speed, and player loads. K-means cluster analysis explored workload patterns among umpire levels using the elbow method. Power Spectral Density and Spectrogram analysis investigated acceleration patterns comparing International Olympic and HNZ-Level 3 umpires—techniques not previously applied in this field.
RESULTS:
Results showed gender, BMI, and umpire level significantly impacted workload metrics. Male umpires recorded higher workloads, covering more distance at faster speeds than females. Higher BMI umpires covered less distance. International Olympic umpires experienced lower overall loads and top speeds than domestic-level umpires. GPS clustering revealed International Olympic umpires grouped in high-to-moderate workload categories, while HNZ-L3 umpires appeared in low workload categories. Playermaker clustering showed greater overlap between levels, with both groups often classified under low-to-moderate workload clusters. Power Spectral Density analysis indicated gradual, consistent acceleration patterns across both levels with fewer sudden accelerations.
CONCLUSION:
These findings provide valuable insights into field hockey umpire external workload, demonstrating how gender, BMI, and umpire level influence performance metrics. Further research should extend Power Spectral Density analysis and consider environmental factors influencing workload patterns.