The biometric data that could predict racehorse injury

POSTED ON  |  20-06-2022

Peta Hitchens
Imagine having the knowledge to prevent a catastrophic event from occurring ahead of time. In horse racing, this could be a possibility. Our new research investigated whether the same systems used to help punters pick a winning racehorse could provide the data needed to protect that same racehorse from injury.

A PROBLEM WITH MEASUREMENT

Efforts to date at predicting injuries in racehorses haven’t been much better than a coin flip. In the past, injuries in horse racing have been treated as a binary outcome – a horse is either injured or uninjured. But injuries, largely a result of bone damage, have a gradual onset.

An injury may develop over weeks or months, unless it’s due to a traumatic event (like a horse running into a fence), so it rarely occurs the very day it is observed. We know this because the majority of catastrophic injuries in racehorses have shown evidence of pre-existing bone damage. This damage accumulates during training and racing over time due to repeated loads being put on the musculoskeletal system. With every stride taken by a horse galloping at a moderate speed, loads of up to four tonnes on the fetlock joint surface have been measured.

Bone can only withstand a limited number of these loads and the strides taken at faster speeds produce greater loads. Often the initial detection of injury is when the horse breaks down or shows signs of lameness, indicating that the threshold for bone damage has already been reached. But rather than waiting until that injury becomes obvious, we realised that a way of measuring horses’ response to training and racing workloads was required.

THE DAWN OF THE DATA DRIVEN ERA

So, what if there was a way to measure the onset of injury using already established systems of data collection? As it happened there is. It all started back in 2010 when the principal racing authority of Tasmania, Tasracing, partnered with StrideMASTER, a budding technology company developing training monitoring systems for the racing industry. They developed one of the first race-day timing systems using GPS and precision motion sensor data. The initial purpose of this data was for real-time sectional timing and positional data of racehorses that was then intended for use as a broadcast and wagering product.

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