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Goal Range Model (beta)
Stop guessing. Let the data pick your bets.
GRM Pro is a football prediction engine built on Bayesian probability modelling — combining Dixon-Coles statistical blending with real empirical hit rates to generate daily picks across 360+ fixtures in 30+ leagues worldwide. Built solo over three months on a phone. No team, no funding, no official data access. The model has processed 1,000+ fixtures with 60%+ accuracy across all markets.
I built GRM Pro because I was tired of betting on instinct and losing money I could have kept.
I'm a solo developer. I built this entirely on my phone — no team, no funding, no server. Just Termux, a Bayesian probability engine, and three months of obsessive iteration. The model has processed over 1,000 fixtures across 30+ leagues and sits consistently above 60% accuracy.
The problem I was solving is simple: the betting industry sells you confidence without data. Tipsters claim hit rates they can't prove. Odds hide the real probabilities. Everyone is guessing and calling it analysis.
GRM doesn't guess. It builds every pick from empirical historical rates, Bayesian blending of season form and recent form, and a deflation curve calibrated against real backtest data. When the engine says 78% — that number came from actual results, not a formula someone made up.
The Rollover system is what I'm most proud of. It's not a gimmick. It's a mathematically structured compounding chain — pick quality filtered to ≥65% empirical rate, combined odds locked at ~2.00, with a three-bucket system that protects profit even when a step fails. Built for the long game.
This is v1. Still solo. Still on a phone. But it's real, it works, and today it's live.
About Goal Range Model (beta) on Product Hunt
“Stop guessing. Let the data pick your bets.”
Goal Range Model (beta) was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #143 on the daily leaderboard. GRM Pro is a football prediction engine built on Bayesian probability modelling — combining Dixon-Coles statistical blending with real empirical hit rates to generate daily picks across 360+ fixtures in 30+ leagues worldwide. Built solo over three months on a phone. No team, no funding, no official data access. The model has processed 1,000+ fixtures with 60%+ accuracy across all markets.
On the analytics side, Goal Range Model (beta) competes within Sports, Soccer and Artificial Intelligence — topics that collectively have 483.5k followers on Product Hunt. The dashboard above tracks how Goal Range Model (beta) performed against the three products that launched closest to it on the same day.
Who hunted Goal Range Model (beta)?
Goal Range Model (beta) was hunted by New User. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Goal Range Model (beta) including community comment highlights and product details, visit the product overview.
New User