The sports science underpinning load-related injury prevention has been peer-reviewed, replicated, and applied at elite level for the better part of a decade. The methodology is not new. What is new is the market.
Up to 79% of recreational running injuries are preventable (Kakouris et al., 2021). Not because runners need to do less, but because the training load is increasing faster than the body's capacity to absorb it, and nothing is flagging it before the damage is done.
Fifty million recreational runners are wearing devices that collect, in real time, the precise data required to apply that methodology. The question is not whether the science works. The question is why it has taken this long for a product to sit between the data and the decision.
The cost of doing nothing
The majority of those injuries are overuse injuries, not trauma, not bad luck, not anatomical inevitability. They are the predictable consequence of training load increasing faster than the body's capacity to absorb it.
For the individual runner, that means weeks off, lost race entries, physiotherapy costs, and a return-to-run cycle that frequently ends in the same place it started. For the healthcare system and employer health programmes that sit above them, it means avoidable utilisation driven by a problem that is, by the research's own measure, 79% preventable (Kakouris et al., 2021).
The ROI argument does not require a complex model. It requires one question: what is the cost of the injury versus the cost of preventing it?
Where the value sits
The value in preventive load management is not in the wearable. Garmin, Apple, and Polar have already solved data collection. Their sensors are accurate. Their ecosystems are mature. Garmin's own RUNSAFE dataset, drawn from over 140,000 running sessions, identified that sessions just 10% above a runner's recent load were associated with a 64% elevated injury hazard (Nielsen et al., 2025). The research infrastructure is there. The hardware is already on people's wrists.
The value sits in the intelligence layer between the data and the decision. Specifically, in the application of Exponentially Weighted Moving Average (EWMA) methodology, validated by Williams et al. (2017, BJSM) and further refined by Impellizzeri et al. (2020, BJSM) to calculate each runner's acute and chronic load from their actual training history, updated after every session, and translated into a personalized, adaptive plan.
This is what elite performance teams have had access to for years. Sports scientists monitoring load data in real time. Trends flagged before they become injuries. Training adjusted accordingly. The recreational runner has the same data. They have never had the same methodology applied to it.
The B2B layer
The direct-to-consumer opportunity is significant. But the B2B opportunity is where the structural returns compound.
Physiotherapy clinics managing runners with repeat overuse presentations have a patient cohort that reliably returns, not because the clinical intervention failed, but because the underlying load mismanagement that caused the first injury continues unchecked. From the moment a patient leaves the clinic after their first appointment and laces up for their first session, what they actually do is invisible to the treating practitioner. How much they ran. How fast the load built. Whether they followed the protocol or pushed harder than prescribed. LODE closes that gap from the start of the treatment episode, not just at discharge, giving the practitioner real-time visibility into their patient's load trend throughout the entire rehabilitation process.
Once the clinical episode ends, the running doesn't. That's where LODE shifts from a practitioner tool to a personal one, giving the runner the same load intelligence their physio was tracking, now in their own hands. Two different users. Two different moments. The same methodology protects the same runner across the full treatment journey.
Corporate wellness programmes and private health insurers face a version of the same problem at scale. Running participation among their populations is growing. Injury-related claims and absence from running-related overuse are measurable and recurring. A load intelligence platform that reduces injury incidence by a statistically meaningful margin, even 20 or 30 percent, represents a calculable return against the cost of the platform.
Run coaches managing recreational athletes operate without the load monitoring infrastructure that professional coaching staff take for granted. LODE fills that gap without requiring them to build it themselves.
The timing
Wearable penetration among recreational athletes is at a point where the data infrastructure for personalized load monitoring already exists at scale. The sports science is validated and peer-reviewed. Consumer awareness of the connection between training load and injury risk is growing, partly driven by Garmin's own RUNSAFE communications. The regulatory and liability pressure on insurers and employers to demonstrate preventive health investment is increasing.
The gap that remains is a product built specifically for the recreational runner that translates what the wearable captures into what the runner, and the practitioner sitting above them, should do next. Not a coaching app. Not a training plan generator. A load intelligence platform.
That is the gap LODE is built to close.
References: Kluitenberg et al. (2015); Kakouris et al. (2021); Nielsen et al. (2025, Garmin RUNSAFE); Williams et al. (2017, BJSM); Impellizzeri et al. (2020, BJSM)
