Goal Range Model (beta)
Stop guessing. Let the data pick your bets.
What it does
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.
Does the same job
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Hey HN, I fine-tuned a small open-source model on golf forecasting and it beats GPT-5 at predicting golf outcomes. The same approach can be used to build a specialized model in any domain, you just need to update a few search queries. We fine-tuned gpt-oss-120b with LoRA on 3,178 golf forecasting questions, using GRPO with Brier score as the reward. Our model outperformed GPT-5 on Brier Skill (17% vs 12.8%) and ECE (6% vs 10.6%) on 855 held-out questions. How to try it: the model and dataset are open-source, with code, on Hugging Face. How to build your own specialized model: Update the…
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Today, I’m proud to announce Homebrew 6.0.0. The most significant changes since 5.1.0 are a new tap trust security mechanism, the new faster, smaller, default internal Homebrew JSON API, sandboxing on Linux, better defaults informed by our user survey, many brew bundle improvements, improved performance and initial support for macOS 27 (Golden Gate). Happy to discuss any questions here!
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