Historically Profitable NBA Algorithm Predictions for 4 Wednesday Spreads (Oct. 26)

Historically Profitable NBA Algorithm Predictions for 4 Wednesday Spreads (Oct. 26) article feature image
Credit:

Justin Ford/Getty Images. Pictured: Paolo Banchero #5 of the Orlando Magic.

There's a 55% correct, 8% ROI NBA algorithm that has collected data since 2005 which targets four games on Wednesday night.

Under specific parameters proprietary to the Action Network, certain types of teams have done fantastic against-the-spread (ATS) over a very lengthy sample size.

These parameters all fit the two aforementioned games, with teams of this sort going 439-357-16 since 2005, good for a 55% winning clip.

If you had bet $100 on each game over the last 17 years, you'd be up $6,160.

Here's what you need to know about this 55% correct NBA algorithm pick for Wednesday.

The Historically Profitable NBA Algorithm Predictions for 4 Wednesday Spreads

The betting algorithm at play targets road underdogs early in the season, where "early in the season" constitutes the first 10 games of the away team's year.

The opposing home team also needs to have a winning record.

Since 2005, road underdogs that play opponents under these parameters win an aforementioned 55% of the time. That's an incredibly lengthy sample size and is more than statistically significant.

For Wednesday night, that means the Nets, Hornets, Magic and Rockets' spreads are the way to go.

(Click the links on each pick to automatically load the bet into your FanDuel bet slip with QuickSlip.)

Do keep in mind that this historically profitable algorithm applies to about 50 NBA games per year. This might be an opportunity to cash in, but keep in mind that this is a long-term investment.

The best way to make money through this algorithm is to bet on every game that fits these parameters for the rest of the year.

We'll continue to write about them.

About the Author
Avery Yang is an editor at the Action Network who focuses on breaking news across the sports world and betting algorithms that try to predict eventual outcomes. He is also Darren Rovell's editor. Avery is a recent graduate from Northwestern University's Medill School of Journalism. He has written for the Washington Post, the Associated Press, Sports Illustrated, (the old) Deadspin, MLB.com and others.

Follow Avery Yang @avery_yang on Twitter/X.

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