For reference, a hybrid fuzzy-SVM has a prediction accuracy rate of 88.26%. https://ieeexplore.ieee.org/document/8344688

(This shows why betting on sports is almost impossible to have a long-term edge as it's already a very efficient market and the odds usually reflect the win rate very well.)

As another reference, an earlier predictor that also uses the elo rating system has an accuracy of 65.3% which is very close to the result in this post, and I guess this may be a typical range for elo-based predictors. https://github.com/luke-lite/NBA-Prediction-Modeling

By the way, I really like the interface of this "emailware". It's really fun to play with.

The 66.45% it's pretty average and might also be sometimes misleading. The model lacks many features and has been developed for around 3 weeks now. I'm only 20 studying my first year in Software Engineering and the project was a lot of fun to create and to se it in action, sometimes being able to outperform the odds (not so consistently to be used to make and edge obviously as it is practically impossible)

Here's how 66% compares to the trivial predictor: "pick the team with the higher win rate and flip a coin if they're equal" gives you 64% for the 2024 season I just tried it on.

I'm not even considering home/away, let alone win margins, recent form, strength of schedule etc. I'm almost amazed this model couldn't make any use of them.