A player comes back after four weeks away. He feels good. The first session is the same as everyone else’s, at full intensity. Ten minutes in, he pulls up with a sore hamstring.
The coach’s first thought is that the session was too hard. The data often says something different. The session may not have been too hard for a fit athlete. It may have been too big a step for an athlete who had been resting.
This is the idea behind the training load and injury paradox. This article explains it in plain terms. It covers what the research shows and what to do when athletes return from a break.
The Common Belief
Many coaches think more training means more injuries. It sounds logical. More work means more chances for something to go wrong.
So when injuries rise, the first move is often to cut the load.
The research points to a more careful picture. Training load is one part of it. How fast the load changes is another.
The Paradox
Gabbett (2016) proposed the training and injury prevention paradox. Athletes used to high training loads often get injured less than athletes who train at lower loads.
The paper gives two reasons.
Fitness protects. Well-developed physical qualities, such as strength and aerobic fitness, are linked to lower injury risk in many sports. Athletes have to train to build them.
Too little training carries risk. An athlete who does little is not built to handle a hard match or session. Cutting load too far can leave them exposed.
The paper also reports a team sport finding. Athletes who had trained for more than 18 weeks before their first injury had a lower risk of later injury.
The author also argues that many non-contact injuries come from how training is designed. Fast, large increases in load are a main concern, not training itself.
It Is the Change, Not Only the Amount
A study of 59 elite Australian football players tracked running loads with GPS for two seasons (Murray et al., 2017). The researchers compared the last week’s load with the average of the last four weeks.
When the last week was more than twice the four-week average, injury risk was higher. For total distance, the risk was about 8.7 times higher in that week. In the week after, it was about 5.5 times higher.
A study in elite rugby league players found a similar pattern. It concluded that a high chronic workload may lower injury risk (Hulin et al., 2016).
Both studies point the same way. A fit athlete with a steady load is better protected. A sudden jump is where the risk rises.
How to See the Change
The method used in these studies is the acute to chronic workload ratio. It sounds technical. The idea is simple.
- Acute load is the last week of training.
- Chronic load is the average of the last four weeks.
- The ratio is acute divided by chronic.
If last week matched the four-week average, the ratio is 1. If last week was double, the ratio is 2.
Load can be measured in two ways. External load is what the athlete does, such as distance run. Internal load is how hard it felt, such as session rating of perceived exertion multiplied by minutes. Gabbett suggests tracking both.
The Debate
The ratio is popular, and it has critics. Impellizzeri and colleagues (2020) argue that it has statistical problems. They also say no study has shown that changing the ratio lowers injury risk. Their conclusion is that there is no evidence for using it as a rule to manage injuries.
Both views can be true. The critics are not saying that big jumps in load are fine. They are saying the ratio is a weak tool for predicting injury and a poor basis for strict rules.
A reasonable middle path is to use the ratio as a way to look at your own data. If a week is far above the recent average, that is worth a conversation. It is not a verdict.
After a Layoff
The paradox matters most after a break. The chronic load falls during a layoff, because the four-week average gets smaller. When the athlete returns to full sessions, the ratio jumps.
This applies after injury, illness, holidays and the transition phase between seasons.
A simple way to handle it:
- Start below normal load, even if the athlete feels fine.
- Raise load in steps over the next weeks.
- Return to full load only when recent weeks are close to it.
- Keep an eye on soreness and tiredness through the ramp.
The longer the break, the longer the ramp. A short layoff needs a short ramp. A month away needs a few weeks.
What the Evidence Covers
The studies in this article are observational. They show a link between load changes and injury. They do not show cause.
Most come from elite men’s team sports, with GPS data. Results may differ in other sports, in women’s sport, and in youth athletes.
The ramp plans in this article are working conventions. No trial has tested them against other plans. Treat them as a starting point and adjust to the athlete.
Where to Start
- Record each athlete’s weekly load in one simple measure. Session rating of perceived exertion multiplied by minutes is enough.
- Compare each week with the average of the last four.
- Look for large jumps, especially after breaks.
- After any layoff, plan the ramp before the first session.
- Do not cut load for athletes who are fit and training steadily. That is the group the research suggests is best protected.
The aim is to help athletes train hard on a plan that rises step by step.
References
Gabbett TJ. The training-injury prevention paradox: should athletes be training smarter and harder? Br J Sports Med. 2016;50(5):273-280.
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
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
Murray NB, Gabbett TJ, Townshend AD, Hulin BT, McLellan CP. Individual and combined effects of acute and chronic running loads on injury risk in elite Australian footballers. Scand J Med Sci Sports. 2017;27(9):990-998. DOI: 10.1111/sms.12719
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