For decades, the working assumption in running research has been that injuries build up gradually, the product of cumulative stress and overuse that a runner can track and manage. A new study from Aarhus University, published in the British Journal of Sports Medicine, argues that assumption is largely wrong. Lead researcher Rasmus Ø. Nielsen and colleagues followed 5,205 runners across 87 countries for 18 months, recording 588,071 individual running sessions, and concluded that most injuries trace back to a single session in which a runner made a specific training error, rather than to a slow accumulation of load over weeks.
The scale of the dataset is what sets the study apart. Previous work on the Acute:Chronic Workload Ratio (ACWR), the model behind the commonly cited advice to raise weekly mileage by no more than 10%, rested on a single 2016 study of just 28 participants. Nielsen's team wanted a sample large enough to test that guidance properly, and 35% of their much bigger group sustained an injury over the study period — enough injury events to examine against the training data that preceded each one.
The pattern they found was not proportional in the way ACWR assumes. Runners who exceeded their longest run of the previous month by 10 to 30% carried a 64% higher injury risk than those who stayed within their recent range. A 30 to 100% increase raised the risk by 52%, and going more than double the recent longest run raised it again, to 128% higher. Nielsen frames this as evidence that injuries occur because runners make training errors in a single session, not because load creeps upward gradually across a training block.
The finding has practical implications for the guidance built into most GPS watches and coaching apps, much of which is derived from ACWR-style weekly-percentage rules. If the Aarhus data holds up, that guidance compares the wrong numbers: a runner's current week against their recent average, rather than a single run against their own recent longest effort. Nielsen's team says it plans to build a free, publicly available algorithm that would flag risk closer to real time, using a traffic-light system tied to how a runner's current session compares with their own recent history, rather than a blanket weekly percentage.
For now, the study gives runners a simpler question to ask before a big session than the one most training plans pose. Rather than tracking whether this week's mileage is more than 10% above last week's, the more useful comparison, on this evidence, is whether today's run is dramatically longer than anything covered in the past month. The research does not settle every objection — an 18-month observational study cannot fully separate cause from coincidence, and self-reported injury data always carries some noise — but the sample size is large enough that sports medicine researchers are treating it as the most serious challenge yet to a rule of thumb that has shaped training plans for a decade.