Why we don't show an acute:chronic workload ratio

If you've used a training app or read about team sport, you've probably met the acute:chronic workload ratio (ACWR). It takes how much you trained in the last week and divides it by your average over the last four. Under 1 means you're doing less than usual; over 1, more. The headline claim is that injuries are least likely between about 0.8 and 1.3, and most likely above 1.5.

Prøva's Load page (for coaches, and the weekly totals in the app) doesn't show it. Here's why.

Where the ratio came from

The idea was introduced in cricket fast bowlers in 2014 and made famous by a 2016 review in the British Journal of Sports Medicine on the "training-injury prevention paradox" [1]. Its message was a good one: athletes used to high loads get hurt less than athletes on low loads, and it's sudden spikes that hurt. That review put the "sweet spot" at roughly 0.8–1.3 and the "danger zone" at 1.5 and above.

Two details matter. The data came from cricket, Australian football and rugby league. And the author warned that applying it to athletes in individual sports should be done with caution [1]. Within a few years it was nonetheless being used in apps and wearables for almost everything, and the IOC's consensus on load had recommended it for monitoring injury risk [4].

What's wrong with it

The two halves aren't independent. The usual "chronic" average includes the same week as the "acute" one. So the two are correlated by construction, before any athlete has trained: a simulation of 1,000 athletes found a correlation of about 0.5 from the arithmetic alone [2]. Some of the ratio's link with injury is that correlation, not a training effect.

Dividing doesn't add anything. When researchers re-analysed the ratio, the chronic part did little: dividing the last week's load by a made-up or random "chronic" load gave similar results. And neither the ratio nor the last week's load on its own predicted injuries better than a model that knew nothing about load at all [5].

A ratio hides what happened. 2 hours after 2 hours is 1.0. So is 10 hours after 10 hours. A climber back from a month off, doing one easy session, can show a "spike". A ratio says nothing about the kind of training either, and for climbers that matters most: an hour of easy mileage and an hour of limit crimping are not the same week [3, 4].

The thresholds aren't solid. Reviewers found the ratio being calculated in many different ways, with different windows and averages [3, 4]. Its supporters replied that removing the overlap between the two halves changes little in practice [6], which is fair, but it doesn't answer the bigger problem above: the ratio predicts no better than the last week's load does. A 2025 meta-analysis of 22 cohort studies did find that higher ratios went with more injuries, but its authors called for caution, citing different calculation methods and possible publication bias [7]. An association across groups is not a number you can steer one climber by.

There's no climbing data. We know of no study that has tested the ratio in climbers. What climbing research does point to as risk factors is intensity, bouldering, crimping, low finger strength and a previous injury; the evidence on how much you train is conflicting [8].

So does load not matter?

It does. The good part of the 2016 message holds up: build up gradually, avoid sudden jumps, and don't drop to nothing then come back at full speed [1, 9]. The trouble is turning that into one number with a threshold.

What Prøva does with this. The Load page shows each climber's week as it is: planned against done, split into fingers, strength and climbing, with finger load on its own. It compares a week only with that climber's own 4-week average, and says it in words: "finger load 40 % above their 4-week average, 2 sessions logged outside the plan". That's a reason to talk, never a rule, and Prøva never changes a plan because of it. The limits that do change a plan are simpler and stricter: how much a finger load can rise from one session to the next and over a week, and no rise at all within a week of a niggle, in a deload, or while coming back from an injury.

Sources

1. Gabbett TJ (2016). The training–injury prevention paradox: should athletes be training smarter and harder? British Journal of Sports Medicine 50(5):273–280. https://pmc.ncbi.nlm.nih.gov/articles/PMC4789704
2. Lolli L, Batterham AM, Hawkins R, et al. (2019). Mathematical coupling causes spurious correlation within the conventional acute-to-chronic workload ratio calculations. British Journal of Sports Medicine 53(15):921–922. https://doi.org/10.1136/bjsports-2017-098110
3. Impellizzeri FM, Tenan MS, Kempton T, Novak A, Coutts AJ (2020). Acute:chronic workload ratio: conceptual issues and fundamental pitfalls. International Journal of Sports Physiology and Performance 15(6):907–913. https://doi.org/10.1123/ijspp.2019-0864
4. Wang C, Trejo Vargas J, Stokes T, Steele R, Shrier I (2020). Analyzing activity and injury: lessons learned from the acute:chronic workload ratio. Sports Medicine 50(7):1243–1254. https://doi.org/10.1007/s40279-020-01280-1
5. Impellizzeri FM, Woodcock S, Coutts AJ, Fanchini M, McCall A, Vigotsky AD (2021). What role do chronic workloads play in the acute to chronic workload ratio? Time to dismiss ACWR and its underlying theory. Sports Medicine 51(3):581–592. https://iris.univr.it/retrieve/e34cfb98-e922-4c2f-aab5-18583ab7e31b/Impellizzeri_What%20Role%20Do%20Chronic%20Workloads%20Play_SportMed_2021.pdf
6. Windt J, Gabbett TJ (2019). Is it all for naught? What does mathematical coupling mean for acute:chronic workload ratios? British Journal of Sports Medicine 53(16):988–990. https://doi.org/10.1136/bjsports-2017-098925
7. Qin W, Li R, Chen L (2025). Acute to chronic workload ratio (ACWR) for predicting sports injury risk: a systematic review and meta-analysis. BMC Sports Science, Medicine and Rehabilitation 17:285. https://doi.org/10.1186/s13102-025-01332-x
8. Quarmby A, Zhang M, Geisler M, et al. (2023). Risk factors and injury prevention strategies for overuse injuries in adult climbers: a systematic review. Frontiers in Sports and Active Living 5:1269870. https://doi.org/10.3389/fspor.2023.1269870
9. Soligard T, Schwellnus M, Alonso JM, et al. (2016). How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury. British Journal of Sports Medicine 50(17):1030–1041. https://bjsm.bmj.com/content/50/17/1030