Three Years, Twenty Miles Per Hour, and a Data Problem Nobody Talks About

Posted on by David Navarre

I first coached this kid when he was throwing 40-44mph in rec ball. He was maybe ten years old, learning to grip a baseball properly, figuring out what his arm was supposed to do. Now he’s an 8th grader who just made the high school roster, sitting on 60+ mph on his four-seamer.

Twenty miles per hour in three years. That doesn’t happen by accident.

It happens through consistent work and honest feedback — the kind where you actually look at what the ball does after it leaves his hand, not just whether it ended up where you wanted it. It happens because this kid has always been coachable, and because the people around him have cared enough to pay attention over time.

But here’s something I almost couldn’t show you.

The silo problem

His early sessions ran through PitchLogic. His more recent work has been on Rapsodo. Two different tracking systems, two separate data sets, neither one designed to talk to the other. Each system is good at what it does in isolation — but neither one can show you a three-year velocity arc. Neither one can tell you whether his movement profile has matured alongside his velocity. Without a way to pull those silos together, the chart at the top of this post doesn’t exist. You have snapshots. You don’t have a story.

This is more common than people realize. A kid pitches at one facility in the fall, another in the spring, uses one tracking system at a showcase and a different one at his home field. Every session generates data. Almost none of it follows him anywhere.

What the data actually shows

Velocity is the headline, but it’s not the whole story. What I care about as a coach is whether his development is coherent — whether the pitches he throws are moving the way we intend, consistently, from session to session.

That means looking at movement consistency: how much does the actual shape of his fastball vary across a bullpen session? Not relative variation as a percentage of the mean — what matters to a hitter is actual variation in real units, inches of movement, degrees of spin axis. A pitch that varies three inches horizontally is three inches of unpredictability, regardless of how much it moves overall.

It also means looking at tunneling — how similar do his pitches look to a hitter through the first 20 feet of flight before they diverge? Velocity gets you into the conversation. Tunneling and movement consistency are what keep hitters uncomfortable.

These aren’t things you can eyeball from the mound. They’re things the data tells you, session over session, if the data is actually connected.

What comes next

At the current trajectory, this kid projects to mid-80s by the end of high school. Nothing is guaranteed — progress is never perfectly linear, and bodies and mechanics evolve in ways that charts can’t predict. But the data gives us a foundation to work from. It gives him something to own and carry forward, regardless of what facility he walks into next or what coach is standing behind the mound.

That’s what I built DiamondMetrics to do — make a player’s development record as portable as he is. Not a snapshot. A passport.

If that problem sounds familiar, I’d be glad to talk. I’ll be at the Buying Sandlot Summit in Philadelphia next week — find me there, or reach out any time at diamondmetrics.net

Who Owns Your Player’s Development Data?

Posted on by David Navarre

One of my players trained at three different facilities last year. Rapsodo sessions at one place, PitchLogic at another, some Trackman work at a showcase. He played on four teams with game data (a spring and 2 fall school teams, plus a summer travel team). He’s got other health and strength metrics in various apps. By December, his development story was scattered across six different logins, five different dashboards (no combined game data dashboard), and six different formats. He has even more if we start looking at his hitting.

Sound familiar?

This is the reality for most families in travel baseball. You’re investing serious money in player development, and the data that documents that development — spin rates, velocities, movement profiles, progress over time — lives in silos you don’t control.

The Tension Nobody Talks About

Here’s the uncomfortable truth: the facilities and technology vendors who create this data have little incentive to make it portable. Their business models reward stickiness. If your data lives in their system, you keep coming back to their system.

I don’t say this to vilify anyone. These are businesses, and businesses need to survive. But it creates a tension that families bear the cost of.

Facilities have the money to invest in tracking technology and analytics platforms. Families need the portability to maintain continuity as players move between facilities, change geography, or simply want to see their full development arc in one place.

Who funds it versus who owns it — that’s the question nobody’s answering clearly.

What If We Treated Player Data Like Medical Records?

Think about how healthcare handles this. Your doctor creates your medical records. The provider generates the data, maintains the systems, employs the staff. But you, the patient, have portability rights. You can request your records. You can take them to a new provider. Your history follows you.

The provider funds the creation. The patient owns the portable artifact.

What would this look like in baseball? A facility invests in Rapsodo, employs coaches who run sessions, pays for the analytics platform. During the time a player trains there, data aggregates into something useful. But when that player moves on — to a new city, a new facility, or just a different phase of their development — they take their history with them.

The next facility can add to that history. The player never loses what they’ve accumulated.

What This Means for Facilities

Some facility operators might read this and think: why would I pay for something that helps players leave?

But consider the alternative framing: you’re not paying for lock-in. You’re paying to be the place that gave families something valuable they’ll remember.

In a market where every facility has the same Rapsodo machines and runs similar programming, the ones that differentiate will be the ones that think beyond the transaction. Families talk. The facility that treated their data as belonging to them — that’s a story worth telling.

Where This Goes

I don’t have all the answers here. The economics are genuinely hard. Tracking system vendors need revenue models that don’t depend on data captivity. Facilities need value propositions that survive player mobility. Families need something that actually works without requiring a computer science degree.

But I think the medical records model points in a useful direction. Provider creates, patient owns. Funder and owner don’t have to be the same.

The families investing in player development deserve to see the full picture of that investment — not fragments scattered across a dozen logins they’ll eventually lose access to.

I coach high school baseball in western North Carolina and think way too much about data and player development. If you’re a facility operator or technology vendor working on this problem, I’d love to hear how you’re approaching it.