Is 20 MPH Fast? Why Soccer Coaches Should Stop Treating Every Player’s Speed the Same

Imagine two soccer players running side by side at 18 miles per hour.

They’re covering the same distance at the same speed, so it seems reasonable to say they’re working at the same intensity.

Except one player has a maximum sprint speed of 20 mph.

The other can hit 24 mph.

For the first player, 18 mph represents 90% of maximum speed. For the second, it’s only 75%.

Same speed. Very different effort.

That seemingly simple distinction is at the center of a new paper published in Frontiers in Sports and Active Living. The authors argue that soccer researchers—and, by extension, coaches and performance staffs—need to be much more precise about what we mean when we describe running speeds as “absolute,” “relative,” “individualized,” or “normalized.”

It sounds like an argument over vocabulary.

It’s actually an argument about how we understand what training does to individual players.

And as GPS trackers and other performance technologies move from professional clubs into academies, colleges, high schools, and even youth soccer, that distinction becomes increasingly important.

Soccer Has a Data Problem—And It’s a Good Problem to Have

Modern soccer can measure almost everything.

GPS and other tracking technologies can tell us how far a player ran, how quickly they accelerated, how many high-speed runs they completed, how much distance they covered while sprinting, and much more.

Researchers commonly divide those movements into categories such as high-speed running and sprinting.

But there’s a catch: What counts as “high-speed”?

Some systems use fixed thresholds. The paper gives examples such as running faster than 19.8 km/h (12.3 mph) for high-speed running or 25.2 km/h (15.7 mph) for sprinting.

That makes the analysis easy. Every player who crosses the line gets credited with high-speed running or sprinting. But physiologically, that can create a strange situation.

Not Every 15 MPH Run Is Created Equal

Consider three hypothetical players:

Player A: Maximum speed = 20 mph
Player B: Maximum speed = 22 mph
Player C: Maximum speed = 25 mph

Now have all three run 18 mph. Their GPS units record exactly the same speed. But relative to what each player is capable of producing:

• Player A is at 90% of maximum speed.
• Player B is at about 82%.
• Player C is at 72%.

That’s a major difference.

Player A is operating very close to maximum sprint speed.

Player C isn’t.

Yet an absolute-speed system could put all three runs into exactly the same category.

The authors make this point essentially: players with different maximum speeds can experience different biomechanical patterns, metabolic demands, and locomotor stress while crossing the same externally defined speed threshold.

That’s where normalization comes in.

Absolute, Relative, Individualized, Normalized: What’s the Difference?

The researchers argue that several terms commonly used in soccer science have become muddled together.

Here’s a simpler way to think about them.

Absolute speed

An absolute threshold is the same for everybody.

For example: Sprinting = anything faster than 25.2 km/h.

It doesn’t matter who the player is. Cross 25.2 km/h and you’ve entered the sprint zone.

That’s easy to measure and useful for some purposes.

Relative speed

“Relative” means you’re comparing the player’s performance with some external reference.

That might be:

• the team average,
• other players,
• a positional average,
• an opponent,
• or another population benchmark.

A player might therefore be “fast relative to other center backs.”

But that still doesn’t necessarily tell you how hard a particular run was for that player.

The paper emphasizes that these external comparisons can provide useful context without necessarily reflecting the physiological or mechanical intensity experienced by an individual player.

Individualized

An individualized measure uses information obtained from the specific player.

Maybe you’ve tested that player’s maximum sprint speed.

Maybe you’ve measured maximal aerobic speed.

The authors make an important distinction: individualized describes where the reference value came from. It doesn’t necessarily tell us what mathematical operation was performed afterward.

Normalized speed

Now we’re getting to the interesting part.

Normalization expresses running speed as a proportion of an individual’s capacity.

Instead of saying: Jonathan ran 18 mph (which I totally could 🙄)

we might say: Jonathan ran at 90% of his maximum sprint speed.

That’s similar to concepts already familiar throughout exercise science.

Runners train at percentages of VO₂max.

Heart-rate training uses percentages of maximum heart rate.

Strength programs prescribe loads as percentages of a one-repetition maximum.

The authors argue that the same basic principle applies to running speed in soccer.

And suddenly our 18 mph example looks very different.

The Dashboard Can Be Right and Still Mislead You

This is perhaps the most practical lesson for coaches.

Imagine your GPS dashboard says:

Player A: 500 meters of high-speed running
Player B: 500 meters of high-speed running

It’s tempting to conclude that the players experienced similar high-speed loads.

But suppose Player A has a substantially lower maximum sprint speed than Player B.

Those 500 meters may represent a much greater proportion of Player A’s maximum capacity.

The data aren’t wrong.

Your interpretation of the data may be wrong.

That’s a distinction coaches should remember whenever technology enters training.

Numbers don’t eliminate judgment.

They create new things that require judgment.

The Paper’s Figure Makes This Especially Clear

Figure 2 on page 4 provides an excellent visualization of the problem.

The authors compare three ways of looking at a group of players:

Absolute threshold: Everyone is judged against the same fixed sprint-speed cutoff.

Relative threshold: Players are compared with an external reference, such as the team’s average maximum speed.

Normalized threshold: Each player’s running speed is expressed as a percentage of that player’s own maximum speed.

The first tells you whether players crossed a common line.

The second tells you how players compare with one another.

The third tells you how close each player was operating to his or her individual maximum.

Those are three different questions.

And coaches shouldn’t expect one number to answer all three.

Why This Matters for Training Load

Suppose you’re designing a session intended to expose players to near-maximal sprinting.

You could tell everyone: Hit 18 mph.

But that might be a near-maximal effort for one player and a fairly comfortable high-speed run for another.

Instead, you might want players reaching something like a percentage of their own maximum speed.

Conceptually, that’s what normalization attempts to capture.

The authors describe examples such as 60%, 75%, or 90% of maximum speed.

This doesn’t mean every soccer session needs individualized spreadsheets and GPS thresholds.

But it does mean that when the training goal is an individual physiological or mechanical stimulus, individual capacity becomes relevant.

This Could Matter for Injury Management, Too

Here’s where the concept becomes particularly interesting for coaches and performance staffs.

Imagine you’re trying to ensure that a player regularly experiences high-speed running in training.

A fixed threshold might say the player hasn’t done much “sprinting.”

But if that athlete has a relatively low maximum sprint speed, they may actually have accumulated substantial running very close to their maximum.

Conversely, a very fast player could accumulate plenty of distance above the team’s high-speed threshold without getting particularly close to maximum velocity.

Those two athletes may require different interpretations of their training loads.

The paper doesn’t test injury prevention or prescribe return-to-play protocols, so we shouldn’t claim that normalized thresholds will reduce injuries.

But its conceptual argument is relevant whenever practitioners are trying to understand the actual locomotor stimulus an individual player experiences rather than simply counting how often the athlete crossed a universal speed threshold. The authors argue that normalization may improve interpretation of external-load exposure and load-response relationships.

But There’s Another Catch: What’s Your “Maximum”?

This is where things get even more interesting.

Let’s say we agree to normalize running speed.

Great.

Normalize it against what?

The authors point out that soccer studies don’t always use the same reference.

One approach is to measure maximum speed during something like a 40-meter linear sprint.

Another uses the final speed achieved during an intermittent fitness test.

Those might both produce a “maximum” speed, but they don’t represent the same thing.

Performance during an intermittent field test can reflect aerobic fitness, anaerobic capacity, running economy, and acceleration-deceleration ability.

Maximum speed during a linear sprint is much more heavily influenced by sprint mechanics, including force production, stride characteristics, and neuromuscular function.

So saying a player trained at “75% of maximum” isn’t enough.

Seventy-five percent of which maximum?

That’s exactly the kind of detail that can disappear when sophisticated sports-science terminology gets condensed into a dashboard.

What This Means for Players

For players, there’s a reassuring message here:

Don’t obsess over somebody else’s number.

If a teammate hits a higher top speed, that doesn’t necessarily mean your training wasn’t intense.

Likewise, covering less distance in an arbitrary “sprint zone” doesn’t automatically mean you worked less hard.

Some metrics are useful for comparing players.

Others are better for understanding the load experienced by you.

The important question isn’t always: How fast did I run?

Sometimes it’s: How fast did I run relative to what I’m capable of?

That’s a very different way of thinking about performance.

What This Means for Coaches

The paper leads to several useful coaching principles.

1. Know what your GPS zones actually mean

If you’re using player tracking technology, find out how “high-speed running” and “sprinting” are defined.

Don’t assume the software’s default categories represent meaningful physiological boundaries for every player.

The authors note that operational definitions can vary according to tracking-system manufacturers, proprietary algorithms, and whether practitioners use default or customized thresholds.

2. Match the metric to the question

If you’re comparing your team’s speed with another team, absolute thresholds may be useful.

If you’re comparing a winger with other wingers, a relative benchmark may be useful.

If you’re trying to understand how close a particular athlete came to maximum sprint speed, normalization may be more useful.

There isn’t necessarily one “correct” metric.

Some metrics are more or less appropriate for particular questions.

3. Test players when individualization matters

You can’t meaningfully calculate a player’s percentage of maximum sprint speed unless you have a reasonable estimate of that player’s maximum sprint speed.

And that number can change.

A developing player gets faster.

An injured player returns.

A teenager matures.

Training improves performance.

The reference point may therefore need updating if you’re going to base training decisions on it.

4. Don’t let terminology fool you

“Individualized” sounds sophisticated.

“Relative threshold” sounds scientific.

“Normalized load” sounds even more impressive.

But the label isn’t what matters.

Ask:

What exactly was measured?

What is this number being compared against?

How was the percentage calculated?

What does this metric actually tell me about the player?

Those questions are far more valuable than the terminology itself.

What About Youth Soccer?

This is where I think coaches need to be especially thoughtful.

Young players can differ enormously in physical development.

Two 13-year-olds on the same team may have very different body sizes, maturation levels, running mechanics, and maximum speeds.

A universal sprint threshold could therefore represent very different physical demands for different players.

That doesn’t mean youth coaches need expensive GPS systems.

In fact, the larger principle works perfectly well without technology:

Treat players as individuals.

A conditioning exercise that is near-maximal for one player may not be near-maximal for another.

A player struggling to keep up isn’t necessarily less motivated.

And the fastest player isn’t necessarily receiving the greatest training stimulus simply because they’re covering ground more quickly.

Data can help quantify those differences.

Good coaching should already recognize them.

A Necessary Word of Caution

This paper is a Perspective, not an experiment demonstrating that normalized speed thresholds produce better players, fewer injuries, or superior training outcomes.

That’s important.

The authors themselves caution against concluding that normalized thresholds are inherently superior.

Absolute thresholds remain useful when comparing players, positions, teams, or levels of competition. Normalized thresholds may be especially useful when the goal is understanding running demands relative to an individual’s sprint capacity.

So the lesson isn’t:

Stop using absolute speed.

It’s:

Know what question your speed metric answers.

The Bottom Line

Twenty miles per hour is twenty miles per hour.

But it doesn’t mean the same thing for every soccer player.

A speed that’s nearly maximal for one athlete could represent a substantially lower-intensity effort for another.

That’s why this new paper argues for much greater precision when soccer scientists and practitioners talk about absolute, relative, individualized, and normalized running speeds.

For coaches, the practical takeaway is straightforward:

Measure the player, not just the number.

Technology can tell us exactly how fast someone ran.

The harder—and more important—question is what that speed meant for that player.

And sometimes, understanding the difference between 18 mph and 90% of maximum is exactly where useful sports science begins.