Story

Show HN: Open-source LLM and dataset for sports forecasting (Pro Golf)

bturtel Tuesday, February 24, 2026

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 search queries and instructions in the Lightning Rod SDK to generate a new forecasting dataset, then run the same GRPO + LoRA recipe.

SDK link: https://github.com/lightning-rod-labs/lightningrod-python-sd... Dataset: https://huggingface.co/datasets/LightningRodLabs/GolfForecas... Model: https://huggingface.co/LightningRodLabs/Golf-Forecaster

Questions, feedback on the SDK, suggestions for new domains to try this on - all are welcome.

Summary
The Golf Forecaster is a machine learning model that predicts the outcome of golf tournaments, including individual player performances and tournament winners. The model is trained on historical golf data and can be used to assist with sports betting, fantasy golf, and tournament analysis.
7 0
Summary
huggingface.co
Visit article Read on Hacker News