Athlete load monitoring can be a thankless job for sports practitioners. You are responsible for designing sessions that ensure an athlete effectively trains on the threshold to gain what Windt and Gabbett, 2016 refer to as fitness rather than fatigue. One step too far and you risk an injury, falling short leaves your athlete below their athletic potential. What we have learned through navigating the sporting field and conversing with leading sports medicine, strength and conditioning, and science coaches is that there is very little room for error. And when we acquired the information on how much financial cost, never mind endorsements, missed winning potential, or program structure implications comes as a result of injury in a season we understood why. For example, the English Premier League issued how there was a 54 million euro injury related cost each year between the 2012/1313 and 2016/17 seasons. Reinforcing to us, that yes – injuries are a major epidemic in sport. This figure isn't even including the current female athlete ACL epidemic as female athletes lean into more professional programs.

The drag flicking technique in hockey can leave athletes vulnerable to injury.

A rise of research into optimal load, athlete monitoring tools such as Global Positioning Systems, or screening technology like Force Decks has come as a result of the emphasis on load management, which according to the Hockey Ireland physio, has moved physios to hold a “higher expectation to be able to control the load related injuries”. DANU, a new movement analysis technology, has the capacity to integrate into an athlete's lifecycle whether it be for performance, injury prevention, or rehab. It achieves this through its unobtrusiveness to athletes in its form of a Smart Socks that moulds to the users foot in any footwear, environment or conditions while gathering paramount bilateral analysis data to provide meaningful metrics. And most importantly, as a sock can get smelly, is machine washable.

DANU conducts movement analysis for gait plyometric, and balance assessments. Bilateral feedback is provided for each limb through an array of metrics whether it be contact times, flight times, step length, peak/mean velocity as well as asymmetries for every metric. Combining this with sensors that line the sole of the sock to provide foot strike mechanics, centre of pressure mapping, a comprehensive picture of athletes dominant limbs, normative movement patterns and asymmetries can be achieved all while on the field of play. DANU seamlessly assesses multiple athletes at any one time, and holds longitudinal data so that reference can be made to progression overtime, injury risk parameters, or regression notices.

The Case Study involved three international hockey players using the DANU system as a remote load analysis and progression tool who were playing in the Hockey 1 league in Australia in 2023. How it integrated into their training was in two ways:

1. Training Day Neuromuscular Readiness Assessments – Plyometric tests (CMJ & Repeated Hops)
2. Athlete Screening every 3-4 weeks – Plyometric & Gait tests (5 minute Steady State, Sprint Assessment, SL & DL Drop Jumps, CMJ, Repeated Hops)

Through the daily neuromuscular assessments, we used longitudinal data with one standard deviation which could alert practitioners if any of the athletes were fatiguing from their training. However, all three maintained scores within the set criteria throughout the block, demonstrating how they could sustain the load.

What was of interest for neuromuscular response to load was the bilateral gait analysis during the Athlete Screening Assessments. Most athletes have dominant limbs reflected by patterns of asymmetries for contact and flight times as their norm. Where each athlete's stride time remained consistent in the 5 minute steady state assessments, what did change was what was going on within each stride. DANU bilateral analysis in the steady state runs demonstrated a steady rise in contact times as load increased during the period combined with a decreased flight time. Indicating how the athletes when fatigued would spend more time on the ground and less in the air for each stride. For two out of the three athletes, although this pattern was identified due to fatigue, the dominant limb for the most part remained and their asymmetries were fairly consistent.

One issue did flag from with one of the athletes on the DANU gait assessments who had a significant shift in her asymmetries. Although her stride time remained consistent, she suffered a switch in the leg she was loading after noticing some high right hamstring discomfort. Evident in the graphs below, she spent more time on the ground with her left leg, and more time in the air with her right. This change in gait pattern was a strategy that the athlete was doing unbeknown to her which one—highlighted that yes there is discomfort there, two—increased further risk of injury, and three—displayed what was going on before the injury surfaced, and at what point things started to change.

After further investigations into her plyometric tests—CMJ & Repeated Hops—there was no major change that might signal muscular weakness. What transcended was a diagnosis of Osteitis Pubis by the team medical staff.

DANU was also pivotal in looking at providing quantifiable information around sprint strategy, and while the time of each sprint was not recorded, the athletes technique of completing a sprint was. Two of the athletes in particular experienced decreased contact times, and stride times combined with increased flight times, peak tibial acceleration, and cadence between the baseline and final Athlete Screen. Combining this with a maintained or progressive RSI from drop jumps and repeated hops might suggest a capacity to maintain and improve the max velocity phase where leg stiffness is increased (Haugen et al., 2019).

What we learned from this Case Study was that while many systems are effective in tracking and monitoring athlete load, DANU’s ability to highlight how an athlete is responding to said load within their natural training environment, and for each limb can be a game changer in early injury risk and injury pinpoint identification. It achieves this through the system’s ability to combine gait and plyometric analysis to track asymmetries and dominant limbs while running. As Hockey is a running based sport, gait analysis should be used more often as a tool and DANU can unobtrusively combine with GPS systems to tell the story of an athlete from baseline throughout a season comprehensively. Where previously there were restrictions around gait analysis due to the expense, lab requirements, and time, DANU offers a solution to integrate gait screening within the athletes normal training routine.