Training load is a way of measuring how much physical stress a workout, practice, or game places on your body. It combines what you actually did (the physical work) with how your body responded to it, giving coaches, athletes, and everyday exercisers a single number or set of numbers to track over time. Understanding training load helps you figure out whether you’re doing enough to improve, too much to recover from, or sitting in the productive zone between the two.
External Load vs. Internal Load
Training load has two distinct sides. External load is the work you perform in the outside world: the distance you ran, the weight you lifted, the number of sprints you completed, or the power you produced on a bike. It’s objective and measurable. In team sports, GPS trackers capture metrics like total distance covered, high-speed running distance, acceleration counts, and total player load (a measure of full-body movement intensity). In the gym, external load might be as simple as sets, reps, and kilograms on the bar.
Internal load is your body’s physiological and psychological response to that external work. Two athletes can run the same five kilometers at the same pace, but if one is well-rested and the other is sleep-deprived, their internal loads will be very different. Heart rate, blood lactate, and perceived effort all reflect internal load. The distinction matters because fitness gains and injury risk are driven not just by what you do, but by how hard your body has to work to do it.
How Training Load Is Measured
The simplest and most widely studied method is session RPE, developed by Carl Foster. After a workout, you rate the overall difficulty on a 0-to-10 scale (where 0 is rest and 10 is maximal effort), then multiply that number by the session’s duration in minutes. A 60-minute run you’d rate as a 7 out of 10 gives you a training load of 420 arbitrary units. An 87-minute session rated 4 out of 10 produces 348. These numbers mean little in isolation but become powerful when you track them across days and weeks.
Heart rate methods offer a more physiological approach. One popular version divides a session into five heart rate zones (based on percentage of your max), weights time spent in higher zones more heavily, and adds the scores together. Another method, called TRIMP (training impulse), uses your average heart rate during a session relative to your resting and maximum heart rates, then multiplies by the session duration. Research shows that combining heart rate data with perceived effort gives a more complete picture than either metric alone.
For external load, the tools depend on the sport. Runners and cyclists track distance, pace, elevation, and power output. Team sport athletes wear GPS vests that log total distance, high-speed sprints, rapid accelerations and decelerations, and overall movement intensity. Strength athletes log volume (sets times reps times weight). Each of these captures a different slice of the physical demand, so choosing the right metric depends on what matters most for your activity.
Why Training Load Matters for Performance
Every training session creates two competing effects in your body: a fitness boost and a dose of fatigue. A model first proposed by Banister in 1975 describes performance as the balance between these two forces. Fitness builds gradually and fades slowly. Fatigue spikes quickly and also fades faster than fitness. When fatigue dissipates after adequate recovery, the fitness you gained shows through as improved performance. When fatigue stacks up faster than it clears, performance drops and injury risk rises.
This is why simply doing more isn’t always better. Training load tracking lets you see the cumulative stress you’re under and make smarter decisions about when to push and when to back off. A week-over-week increase that’s too steep can push you into overreaching territory, while a load that’s too low won’t provide enough stimulus to adapt.
The Acute-to-Chronic Workload Ratio
One of the most discussed tools in training load monitoring is the acute-to-chronic workload ratio, or ACWR. First applied to cricket in 2014, it compares your recent training (typically the past 7 days) to your longer-term average (typically the past 28 days). If your recent week is much higher than your monthly average, the ratio climbs above 1.0, signaling a spike. If your recent week is lighter, it drops below 1.0.
A meta-analysis found that keeping the ACWR between 0.8 and 1.3 was associated with the lowest injury rates, with injury incidence rising by roughly 7 to 10 percent outside that range in studies of professional soccer and American football players. In practical terms, that “sweet spot” means your current week’s workload stays within about 80 to 130 percent of what you’ve been averaging over the past month. Rapid spikes beyond that range, like suddenly doubling your running volume, are consistently linked to higher injury risk.
That said, the ACWR has drawn significant scientific criticism in recent years. The choice of 7 and 28 days as time windows is somewhat arbitrary, and different researchers using different windows or different load metrics can arrive at very different conclusions. One research group calculated 350 different hazard ratios simply by varying the time windows and calculation methods. Critics also point out that ACWR measures workload rather than the actual mechanical stress on tissues like tendons and bones, and at least one study in professional soccer found that ACWR spikes were unrelated to subsequent injuries. The ratio remains a useful guideline for spotting dangerous training spikes, but it’s not the precise injury-prediction tool it was initially promoted as.
What Wearables Actually Track
Consumer wearables from companies like Garmin, WHOOP, and Apple have made training load metrics accessible to recreational athletes. Most use heart rate data, accelerometer readings, or both to generate proprietary “strain” or “load” scores. These scores are convenient, but their scientific validity is an open question. A 2022 analysis found that most commercial training load metrics aren’t well validated as true measures of training dose, and that exercise duration can confound their calculations. A long, easy session and a short, intense session might receive similar scores despite placing very different demands on the body.
This doesn’t mean wearable data is useless. Tracking trends over weeks and months still helps you spot patterns: whether your load is climbing too fast, whether you’re recovering between hard efforts, or whether you’re stuck in a plateau. Just treat the specific numbers as relative guideposts for your own training rather than precise scientific measurements.
Applying Training Load to Your Own Training
You don’t need expensive technology to start monitoring training load. The session RPE method requires nothing more than a timer and a 0-to-10 rating after each workout. Log the number daily, and within a few weeks you’ll have a clear picture of your training patterns. Most coaches recommend increasing weekly load by no more than about 10 percent at a time, which keeps your acute-to-chronic ratio comfortably in the lower-risk zone.
Pay attention to both sides of the equation. If your external load stays the same but your perceived effort starts creeping up, that’s an early signal of accumulated fatigue, poor sleep, or insufficient recovery. Conversely, if the same workout starts feeling easier over time while your heart rate stays lower, you’re adapting, and it may be time to progress.
Training load is ultimately a decision-making tool. It won’t tell you exactly what workout to do next, but it gives you a structured way to answer the question every athlete faces: am I doing enough, too much, or just right?