What ACWR is and is not

ACWR (acute:chronic workload ratio) is one of the most cited — and most misread — numbers in sports load monitoring. This guide explains what it measures, the two common ways to calculate it, and what the more recent evidence says about its limits.

Acute load and chronic load

Acute load summarises a player’s recent work, usually the last seven days. Chronic load summarises a longer period, usually the last four weeks, and acts as a reference for what the player has been tolerating. ACWR is, at heart, the ratio between the two: how this week compares with what has become normal for that player.

An ACWR close to 1 means recent load is in line with what the player has been sustaining. A value well above 1 marks a jump against that baseline; a value well below 1 marks a drop. Neither is automatically “good” or “bad” — the number describes a change, it does not interpret it for you.

Two ways to calculate the average

Rolling average

The simplest method weighs every day in the chosen window equally. With a 28-day chronic window, a session from four weeks ago counts exactly as much as one from yesterday.

EWMA

The exponentially weighted moving average (EWMA) weighs recent days more heavily and gradually reduces the weight of older ones, rather than treating them all the same. Williams et al. (2017) proposed this alternative because a rolling average can produce artificial spikes: when a demanding session enters or leaves the 7- or 28-day window, the average can jump sharply even though the player’s actual load has not changed that much. EWMA smooths that transition.

Coupled and uncoupled

A second, separate choice is whether the acute load sits inside the chronic load (coupled) or whether the two are calculated over non-overlapping periods (uncoupled). In a coupled calculation, the most recent week is both the numerator and part of the denominator, which creates a mathematical dependency between the two numbers. An uncoupled calculation avoids that overlap by calculating chronic load only over the weeks before the acute one, without including it.

Where the interest in ACWR came from

Interest in this ratio grew out of two studies looking for a simple, practical signal for everyday use. Hulin et al. (2014), studying elite cricket fast bowlers, found that sharp spikes in acute workload were associated with more injuries in the following week. Gabbett (2016) then framed the now-famous “training–injury prevention paradox”: training hard is not, by itself, the problem if load is progressed appropriately — the risk sits in poorly managed spikes, not in the volume of work on its own.

What the more recent evidence says

Impellizzeri et al. (2020) reviewed the conceptual and statistical problems with ACWR: as a ratio, it is sensitive to how each component is defined, it carries the mathematical dependency of the coupled calculation, and there is still no solid evidence of causal or predictive validity at the individual level. Their conclusion is not that ACWR is useless, but that it should not be used alone, or presented as if it forecasts injury.

That is why this guide does not say ACWR “predicts” or “prevents” anything. ACWR is a monitoring ratio, not a prediction model: a way to see, at a glance, whether a player’s load moved more than usual. What to do with that information stays a decision for the coaching and medical staff, read alongside the rest of the context they have — wellness, RPE, availability — not that number on its own.

Common misreadings

Three mistakes come up often. The first is chasing a magic number: there is no universally “safe” ACWR value for every player or every sport; the useful reference is that player’s own history over time, not a generic threshold. The second is switching method mid-season: comparing an ACWR calculated with a rolling average against one calculated with EWMA makes no sense, because they do not measure the same thing. The third is reading a player’s ACWR from only a few logged days: with an incomplete chronic window, the ratio can be misleading, and it is worth waiting for a few weeks of load before drawing conclusions.

In practice

Because there is no single “correct” method, what matters is that each coaching staff can use the one it already knows and trusts. Athlo lets you configure ACWR profiles with rolling average or EWMA, and coupled or uncoupled calculation, so the number you see is the one you already know how to read. The result is read alongside the rest of the load dashboard, not on its own.

Sources

• Gabbett TJ (2016) “The training–injury prevention paradox: should athletes be training smarter and harder?” British Journal of Sports Medicine 50:273–280.
• Hulin BT, Gabbett TJ, Blanch P, Chapman P, Bailey D, Orchard JW (2014) “Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers” British Journal of Sports Medicine 48:708–712.
• Williams S, West S, Cross MJ, Stokes KA (2017) “Better way to determine the acute:chronic workload ratio?” British Journal of Sports Medicine 51:209–210.
• 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 15:907–913.