Viktor.comAn AI coworker that actually does the work
Promoted
Statlyzer
Pure mathematical football analytics.
12 followers
Pure mathematical football analytics.
12 followers
A transparent football analytics engine powered by Poisson, Dixon-Coles & Monte Carlo simulations. We calculate exact probabilities across 8 variables. Key features: 1. Past Analyst: We log yesterday’s AI predictions vs actual results. Total transparency, no hidden misses. 2. Freemium: Get 2 Free Credits daily to fully analyze any 2 matches worldwide!
Hi Product Hunt! 👋 I'm Paul, the solo maker behind Statlyzer.
A bit of background: I actually built this entire app and its backend architecture (PostgreSQL/Supabase) from the cabin of my truck during my driving breaks across Europe. 🚛💻
The Problem I wanted to solve: The sports analytics and prediction industry is broken. It's full of "experts" selling tips while completely hiding their lost bets. I wanted to build something based on pure, undeniable math, with absolute transparency.
What Statlyzer does:
It runs heavy Monte Carlo simulations, Poisson distribution, and Dixon-Coles models to calculate exact probabilities for football matches across 8 different variables (1X2, Over/Under, Cards, Corners, etc.).
🔥 Why I'm proud of it:
The "Past Analyst" tab. It automatically logs yesterday's AI predictions against the actual real-world results. If the AI missed, you see it. No deleted data, no hidden stats. Just raw accuracy tracking.
The app gives every user 2 Free Credits daily, which means you can run a full deep-dive analysis on any 2 matches on the globe, every single day, for free.
I would absolutely love for this community to download it, test the UI, critique the math models, and give me your raw, honest feedback. I'll be here all day answering your questions!
P.S. A quick technical note: Statlyzer isn't just a static template; it's a living engine. Every night, after the final whistle, the system automatically ingests the new raw match data, learns from yesterday's variances, and recalibrates the Dixon-Coles parameters. The model you use today is mathematically smarter than it was yesterday! 📈
Love the transparency angle with the past analyst tracker. One thing that would really help me as a user is being able to filter those logged predictions by league, bet type, or odds range so I can quickly see how the model performs in the specific markets I actually care about.
@serdardvi1 Thanks, Serdar. While I appreciate the suggestion, I'm keeping the platform focused on raw, unfiltered model performance to maintain full transparency. The goal is to see exactly how the engine behaves across all markets, not to curate it. Glad you're finding the performance logs useful as they are!
honestly love that you show yesterday's predictions vs actual results right on the homepage. most analytics tools hide their misses so that kind of transparency is genuinely refreshing, and it tells me the team actually trusts their model
@salimtoptavkox Hey Salim! Thank you so much! Fun fact: there is no "team"—it's just me coding this entire engine from my truck cabin between driving shifts across Europe! 🚛💻
But you nailed it. Transparency is everything. The best part is that the model actually learns from those misses. Every night, it ingests the new data and recalibrates its parameters, so the math gets smarter every single day. Let me know if you get a chance to use your 2 free credits today, I'd love your feedback! 🚀
finally a football stats tool that doesn't hide its misses, the past analyst log is a nice touch.Used my two free credits on a derby and the numbers were surprisingly detailed.
@berk0q1a Thanks a lot for the feedback, Berk! That's exactly why I built Statlyzer—to provide a transparent analytical tool where performance logs are just as important as the predictions themselves. Glad you found the derby analysis useful! Let me know if you have any suggestions for the next engine update.
love that the past analyst feature logs yesterday's AI predictions against actual results, that kind of transparency is honestly rare in football analytics tools
@doaniikrinu Appreciate it, Doğan! I firmly believe that hiding missed predictions is ruining the sports analytics industry. Feel free to run a few simulations today and let me know your thoughts! 📊
love that you actually log yesterday's AI picks against real results instead of just showing the wins. that kind of transparency is rare in this space and takes real guts to build.
@adem4ihe Thanks, Adem! I really appreciate it. It definitely took some guts, but I realized early on that if I wanted to build a true data engine, I had to let the math speak for itself—even when it misses.
Plus, showing the misses is how the system improves. The model recalibrates every single night based on yesterday's variances, making today's Monte Carlo simulations even sharper. Feel free to jump in and test the 2 free daily credits on today's matches. I'd love to hear your raw thoughts on the UI and data! 📊