The Problem With Chasing “Good Numbers”
One of the first questions athletes ask after testing is:
“Was that good?”
Whether it’s a force plate assessment, a sprint time, a jump test, or an exit velocity number, athletes want to know where they stack up.
And honestly, that’s understandable. Sports are built around numbers. Rankings, leaderboards, PRs, velocities, times, and scores are everywhere.
The problem is that a number by itself rarely tells the whole story.
One of the biggest mistakes in sports science is looking at a single test result and treating it like the final answer.
Because the goal isn’t to create athletes who test well on one day.
The goal is to create athletes who perform better over years.
The Snapshot Trap
A single testing session can give us a lot of useful information.
We can learn about:
Force production
Movement strategy
Reactive ability
Fatigue
Asymmetries
Neuromuscular readiness
But a single testing session can also be misleading.
An athlete might jump higher because they slept great, are fully recovered, and are having an awesome day.
Another athlete might test worse because they just finished a week of exams, played four baseball games over the weekend, and haven’t slept enough in days.
Same athlete. Different circumstances.
That’s why looking at isolated numbers can become dangerous.
When we focus too much on one data point, we start chasing noise instead of development.
The Most Important Graph Isn’t the Highest Number
One of my favorite things about working with athletes long-term is looking back at years of data.
The most valuable graph usually isn’t the one with the highest peak.
It’s the one with the best trend.
When you see small improvements stacking over months and years, you’re looking at something far more important than a great testing day.
You’re looking at adaptation.
A middle school athlete who gradually improves force production, movement quality, coordination, and reactive ability over three years will often outperform the athlete who had better numbers at age 13 but never continued developing.
Long-term athletic development rarely looks dramatic while it’s happening.
Most of the time it looks like:
Slightly cleaner movement
Slightly better positions
Slightly higher outputs
Slightly improved coordination
Slightly better repeatability
Nothing flashy.
Just consistent progress.
And those small improvements compound.
Development Isn’t Linear
Another mistake people make when looking at data is expecting every test to improve.
That’s not how development works.
Athletes plateau.
Athletes regress.
Athletes grow.
Athletes gain strength.
Athletes go through stressful seasons.
Athletes get stronger before they learn how to use that strength effectively.
Sometimes performance dips before it improves.
Sometimes a force-time curve gets messier before it gets better.
Sometimes a lower jump today is part of building a higher ceiling tomorrow.
The question shouldn’t always be:
“Did they improve today?”
The better question is:
“What direction are they moving over time?”
Technology Doesn’t Replace Coaching
This is where sports science can get itself into trouble.
Technology is incredible.
Force plates are incredible.
Motion capture is incredible.
GPS is incredible.
But none of those things coach athletes.
People do.
Technology is only valuable if it helps us make better decisions.
The best coaches use data to:
Ask better questions
Confirm what they’re seeing
Identify blind spots
Improve communication
Track adaptation
Guide training decisions
The data should support coaching.
Not replace it.
The Hidden Power of Consistency
The athletes who make the biggest jumps long-term usually aren’t the ones searching for shortcuts.
They’re the ones who:
Show up consistently
Stay healthy
Build strength over time
Develop movement competency
String together quality training weeks
Trust the process
It’s not exciting.
It’s not flashy.
But it’s usually what works.
Especially with younger athletes.
Final Thoughts
As coaches, we have to remember that athletes attach a lot of emotion to testing.
One bad test can feel like failure.
One great test can create a false sense of accomplishment.
Our job is to keep the focus on development.
A force plate profile isn’t an identity.
A sprint time isn’t a ceiling.
A testing session isn’t a final verdict.
They’re simply checkpoints.
The athletes who ultimately succeed are usually the ones who stop chasing good numbers and start chasing consistent improvement.
Because in the long run, that’s what the numbers are supposed to represent anyway.