Someone has to make the data trustworthy
There's a glamorous half of working with data and an unglamorous half. OZ Intelligence is my bet that the unglamorous half — making the data clean and trustworthy — is where the real value hides.
By Andrew Pyle
There's a glamorous half of working with data and an unglamorous half, and almost everyone wants the glamorous one. The glamorous half is the dashboard, the insight, the clean chart that makes something obvious. The unglamorous half is everything that has to happen first: the gathering, the cleaning, the endless checking of one source against another until you actually believe the numbers. OZ Intelligence is me choosing the unglamorous half, on purpose.
It started, like a lot of my projects, with a wall I kept hitting. I needed trustworthy sports data to build the things I wanted to build, and getting it was miserable every time — locked behind expensive or restrictive APIs, or available but messy, inconsistent, quietly wrong in ways you only discover after you've built on top of it. So eventually I did the annoying thing instead of the easy thing. I started building my own warehouse: crawling the data, cleaning it, cross-checking it, normalizing it into one place I could actually rely on. It's grown into something that tracks well over a hundred and seventy thousand games.
01The real asset
The data layer is the real asset
And here's what surprised me. The boring foundation turned out to be the most valuable thing I'd built. The sites people actually see — the scores, the standings, the pages — are just windows onto it. The real thing is underneath, out of view. The data layer is the asset; everything visible is a read on it.
Most of the work, it turns out, isn't gathering the data. It's trusting it. A dataset is only worth what you can rely on in it, so the bulk of the effort goes into validation — checking sources against each other, catching the one game where two feeds disagree, the score that's off by a point, the schema that silently drifted last season. It's tedious and invisible and it is the entire point. An untrustworthy dataset is worse than no dataset, because it costs you nothing to not have data, and it costs you a great deal to build on data that lies to you.
02Trust isn't free
Trust is not a commodity
Which is the whole thesis, really. Raw scores are a commodity — I've said before that everyone has the same numbers. But clean, validated, deep, historical data is not a commodity. The commodity is the raw fact; the asset is the trust. And the gap between “this data exists somewhere” and “you can build on this without re-checking every row” is enormous. Closing that gap is slow and unglamorous, and that is exactly why it's worth something. Everyone wants to build on data. Almost nobody wants to do the work of making it trustworthy.
03Tool to product
From a personal tool to a product
I built OZ for myself, because I needed it — I want to be honest that it started selfishly. But the wall I kept hitting is the same wall every small developer and team hits. Good sports data that's clean, affordable, and comprehensive is genuinely hard to come by. So OZ is becoming a product too: an API other builders can use to skip the miserable part I couldn't. It's early — there's a waitlist, not some finished business — and I won't pretend otherwise. But the need behind it is real, because I lived it before I ever thought of selling it.
And while only the sports floor is built so far, OZ was designed to be the data layer under everything I build, not just sports. The plumbing is general even if the water only runs to a few rooms yet. Over time the same warehouse is meant to feed the rest of what I'm making. That's the quiet ambition underneath a site that, today, is honestly just about sports.
04The work worth owning
The work worth owning
I'll admit one more thing, which is that I actually like this work. The cleaning, the validation, the small satisfaction of a dataset you can finally trust — most people find it tedious, and I find it grounding. There's something honest about work whose entire purpose is to make sure a number is right. It doesn't perform. It just has to be true.
Nobody admires a foundation. They admire the building. But the building only stands because someone did the careful, boring, unwitnessed work underneath it — and got it right, quietly, where no one was looking. OZ is me deciding to be the person who does that work. The scores were never the hard part. Making them trustworthy was, and that's the part I wanted to own.