ClutchTip didn't start as a business idea. It started as a pattern recognition problem that I couldn't stop thinking about.
The Background
I've always had an obsession with pattern recognition. In 2015, I wrote a paper predicting economic patterns that, looking back, accurately anticipated several major market movements including aspects of the GFC aftermath.
When I started applying the same analytical approach to sports data, I noticed something: prediction markets are inefficient in predictable ways. Not always, not dramatically, but consistently enough that a systematic approach could find edges.
The Build
What started as a simple statistical model evolved into something far more sophisticated through years of iteration. The current system incorporates bespoke features developed through pattern recognition analysis - identifying edges in the data that standard approaches miss.
We've refined these proprietary inputs across thousands of historical games, continuously testing and improving. The specifics of what makes our model different remain confidential - that's our competitive edge - but we're committed to full transparency on results.
The system continues to evolve. We're always working to improve overall accuracy to the highest possible level, adding new features and refining existing ones based on what the data tells us.
Why Go Public?
I could have kept this to myself. But I wanted to build something that forced accountability. When every prediction is public, tracked, and timestamped, there's nowhere to hide. That transparency is what separates ClutchTip from the tout services that cherry-pick their correct calls and bury their misses.
This blog will document the journey - the correct predictions, the incorrect ones, and the lessons learned from both.