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tsgiannis t1_j4c2r0d wrote

No...as I wrote take a previous year's complete data.. Let's take 2021 season..and you have gone back to 2021...you have absolutely no knowledge of the outcomes of games..

The season starts and you are all fired up to earn some money... You wait until a reasonable amount of games are played... around the 60% I reckon is a good percentage So you start training the model. You start with a base amount of cash...e.g $100 You predict for the coming 5 - 10 games...how did the model performed. , Have you made a profit or not.. again..the next 5-10 games..You play until either you run out of money or the season ends. If you run out of money..the bitter truth..back to the drawing board If the season ends.. measure your money.its around $100 - $120.. well at least you didn't lose..but it was tight $121 - $150 maybe you have something $151-$200 maybe you should give it a go > $201 lets make some money 🤑

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vagartha OP t1_j4c36zw wrote

Haha, I live in CA so sports gambling so that's out of the question...

I was actually hoping to maybe write a paper or something and submit it to something like the Sloane conference or send it in to 538 as an add-on to my resume?

Also, my model uses data from seasons going back all the way to 2014 as of right now. Larger datasets would make a better model, right? So why not use more historical data?

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