The acute:chronic workload ratio (ACWR) is one of the most widely used indicators in load monitoring, and for good reason: in a single number it shows whether a player is doing a lot more (or a lot less) than their body is used to. Read well, it is a quick signal for the whole squad.
What the ACWR is
It compares a player's load over the last week with the load they are used to, over the last month. A value close to 1 means the week was much like usual; above 1, more load than usual; below 1, less.
It can be worked out from internal load, such as session RPE, or from external load measured by GPS.
Where the zones come from
The first studies were done in cricket fast bowlers [1] and in rugby league [2]: weeks with spikes in acute load relative to chronic load were associated with more injuries. A widely cited 2016 review summed this up as a reference zone for the ACWR between 0.8 and 1.3, and flagged values from 1.5 upwards as the ones that most deserve attention [3]. The same year, the International Olympic Committee consensus statement on load and injury included it as a monitoring tool [4].
The underlying logic is sound: sudden increases in load need to be seen coming, and so do long drops, which leave a player under-prepared for what comes next.
What the ACWR tells you
- Who is having a sudden change in load, compared with their own history, at a glance for the whole squad.
- Who is coming in with little load: a player returning from injury or not playing builds up a low chronic load, and any normal week can be too much for them.
- When a conversation with the player or a change to the plan is worth it.
What it does not tell you
The ACWR is not an injury predictor on its own. Since 2017, several studies have shown that associations between the ratio and injuries can arise from how the calculation is built [6], that dividing two measures and cutting the result into zones loses information [7], and that it has deeper conceptual problems [8]. When published data were examined again, neither the ratio nor acute load alone meaningfully improved injury prediction, and the authors proposed dropping it [9].
That is why it makes sense to read it as a signal of a change in load, alongside each player's absolute load and context, and not as an injury traffic light.
Why calculating it by hand is misleading
There are several ways to calculate the ACWR, and the same week can land inside or outside the zone depending on which one you use. The version with exponentially weighted moving averages, which gives more weight to recent days, was proposed precisely to improve on the classic calculation [5]. On top of that, you need a month of complete data for each player before the number means anything. In a spreadsheet, a missed day or a formula changed halfway through the season is enough to make the indicator no longer comparable.
The ACWR in CTBrain
In CTBrain, the ACWR is worked out automatically. In the internal load view, from the RPE each player reports in their app. In monitoring, from the external load measured by GPS, with exponentially weighted averages over 7 and 28 days: above 1.5 is flagged as overload and below 0.8 as underload, and it is not shown until there are 28 days of history, so no conclusions are drawn from too little data. The coaching staff sees it alongside each player's load, GPS and what they report.
For the basics of load monitoring, read the guide to training load monitoring.
References
- Hulin BT, Gabbett TJ, Blanch P, Chapman P, Bailey D, Orchard JW. Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. Br J Sports Med. 2014;48(8):708–712. doi:10.1136/bjsports-2013-092524
- Hulin BT, Gabbett TJ, Lawson DW, Caputi P, Sampson JA. The acute:chronic workload ratio predicts injury: high chronic workload may decrease injury risk in elite rugby league players. Br J Sports Med. 2016;50(4):231–236. doi:10.1136/bjsports-2015-094817
- Gabbett TJ. The training—injury prevention paradox: should athletes be training smarter and harder? Br J Sports Med. 2016;50(5):273–280. doi:10.1136/bjsports-2015-095788
- Soligard T, Schwellnus M, Alonso JM, et al. How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury. Br J Sports Med. 2016;50(17):1030–1041. doi:10.1136/bjsports-2016-096581
- Williams S, West S, Cross MJ, Stokes KA. Better way to determine the acute:chronic workload ratio? Br J Sports Med. 2017;51(3):209–210. doi:10.1136/bjsports-2016-096589
- Lolli L, Batterham AM, Hawkins R, et al. Mathematical coupling causes spurious correlation within the conventional acute-to-chronic workload ratio calculations. Br J Sports Med. 2019;53(15):921–922. doi:10.1136/bjsports-2017-098110
- Wang C, Vargas JT, Stokes T, Steele R, Shrier I. Analyzing activity and injury: lessons learned from the acute:chronic workload ratio. Sports Med. 2020;50(7):1243–1254. doi:10.1007/s40279-020-01280-1
- Impellizzeri FM, Tenan MS, Kempton T, Novak A, Coutts AJ. Acute:chronic workload ratio: conceptual issues and fundamental pitfalls. Int J Sports Physiol Perform. 2020;15(6):907–913. doi:10.1123/ijspp.2019-0864
- Impellizzeri FM, Woodcock S, Coutts AJ, Fanchini M, McCall A, Vigotsky AD. What role do chronic workloads play in the acute to chronic workload ratio? Time to dismiss ACWR and its underlying theory. Sports Med. 2021;51(3):581–592. doi:10.1007/s40279-020-01378-6