We've spent the last decade obsessing over health data. Step counts. Sleep scores. Heart rate zones. VO2 max estimates. The wearable market has exploded, projected to surpass $50B, and yet for one of the largest groups of active consumers on the planet, all of that data hasn't moved the needle on the most basic problem they face.
Up to 85% of recreational runners still get injured every year.
That number hasn't changed. And it won't, until we stop treating data collection as the destination.
The gap the industry hasn't closed
The wearable ecosystem is remarkable at recording. Garmin, Apple, Oura, these devices capture pace, distance, heart rate, sleep, body battery, HRV, and more. The data is rich, detailed, and largely sitting idle.
What's missing isn't more data. It's the intelligence layer that tells a runner, or their physio, or their coach, what that data actually means for how they should train tomorrow.
That gap is where injuries happen.
Around 60-70% of recreational runners are injured in any given year. Roughly half of those are overuse injuries. Not trauma, not bad luck, not poor biomechanics. Load. Specifically, load change. Research from Kluitenberg et al. (2022) found that injured runners had commonly increased their weekly mileage by 30-50% in the four weeks before injury. A landmark 140,000-session dataset (Nielsen et al., 2025) found that sessions just 10% above a runner's recent load were associated with a 64% elevated injury hazard.
Not 50% more volume. Not doubling training. Just 10%.
The data to catch this exists on millions of wrists. The product to act on it, for the recreational runner, largely doesn't.
Why this moment is different
Consumer health tech has moved through two distinct phases. The first was hardware, getting sensors onto the body and making them wearable. The second was data visualization, dashboards, trend graphs, weekly summaries. Both were necessary. Neither is sufficient.
The third phase is personalized prescription. Not generic advice. Not a fixed training plan built for an average runner. A dynamic, adaptive output built from an individual's actual physiological response to actual training, updated continuously as their behaviour changes.
This is where sports science has been pointing for years. The methodology exists. Exponentially Weighted Moving Average (EWMA) load monitoring, validated in peer-reviewed research including Williams et al. (2017, BJSM) and Impellizzeri et al. (2020, BJSM) gives a far more accurate picture of how training stress accumulates and dissipates in the body than any fixed ratio or rolling average. It's been used in elite sport for over a decade.
It has never been productized for the 50 million recreational runners who don't have a performance team behind them.
The B2B opportunity is as large as the consumer one
Consumer adoption is the obvious growth story. But the B2B surface area here is significant and underexplored.
Physiotherapists see the same overuse injuries on repeat, runner's knee, IT band syndrome, shin splints, Achilles tendinopathy. They treat the episode. They discharge the patient with advice. And then, with no visibility into what happens when that patient laces up again, the cycle repeats. A load monitoring tool that bridges the gap between clinic and training isn't just a consumer app, it's a clinical referral tool, a compliance mechanism, and a way for physios to extend their value beyond the appointment.
Running coaches face a similar problem. The recreational runner who hires a coach is a small subset of those who need coaching-level support. An intelligent load management platform lets coaches scale personalized guidance to a broader client base, and gives them objective data to work from rather than self-reported effort.
And for the wearable manufacturers themselves, the value proposition is straightforward. The hardware already collects the data. A platform that turns that data into meaningful, personalized action makes the device stickier, more differentiated, and more directly tied to a health outcome the consumer cares about.
What this looks like in practice
LODE connects to Garmin wearables, with more integrations in development, and uses EWMA to calculate each runner's acute (short-term) and chronic (long-term) training load simultaneously. Rather than comparing a ratio to a fixed threshold, LODE monitors the direction and rate of change between these two trends, classifying each runner's current training phase: recovering, maintaining, building, or overreaching.
From that classification, LODE builds a personalized weekly plan. If the runner misses sessions, goes off-plan, or has a harder week than expected, the plan adapts. It responds to what they actually did, not what was prescribed.
Physiotherapist dashboard
It also combines external load (distance, pace, duration) with internal load (heart rate response) to capture the real physiological cost of each run. Two runs at the same pace are not the same stress on the body. LODE knows this. A generic training plan doesn't.
The result, as one early user put it: "I'd had the same shin injury three times in four years. LODE showed me it wasn't bad luck. Every time, I'd spiked my load in the weeks prior without realizing."
The market framing investors should be paying attention to
Preventive health is a category that every major insurer, employer, and health system says they want to fund, and then consistently under-invests in relative to its actual ROI. Running injury is a concrete, measurable, high-frequency problem with a well-understood mechanism and a validated solution. The consumer is already instrumented. The data is already being collected.
The question isn't whether injury prevention belongs in consumer health tech. The question is who builds the product that finally makes good on the data promise wearables have been making for a decade.
That's the opportunity LODE is building into.
LODE is an injury prevention and training load management app for recreational runners. Learn more at lodefitness.com.
