Vibecoding sports models via LLMs is really effective for data pipelining. You can have it write quick Python scrapers to pull historical box scores, feed them into Pandas/Polars, and backtest Poisson distributions for goal/points modeling in minutes. The key is keeping the data clean before letting the model calculate expected value.