Zoltar is my NFL football prediction computer program. It uses reinforcement learning and a neural network. Here are Zoltar’s predictions for week #2 of the 2022 season. These predictions are fuzzy, in the sense that it usually takes Zoltar about four weeks to hit his stride.
Zoltar: chiefs by 6 dog = chargers Vegas: chiefs by 3.5
Zoltar: browns by 6 dog = jets Vegas: browns by 6
Zoltar: commanders by 0 dog = lions Vegas: lions by 2.5
Zoltar: colts by 2 dog = jaguars Vegas: colts by 4
Zoltar: buccaneers by 0 dog = saints Vegas: buccaneers by 3
Zoltar: giants by 2 dog = panthers Vegas: giants by 2.5
Zoltar: steelers by 2 dog = patriots Vegas: patriots by 1.5
Zoltar: ravens by 1 dog = dolphins Vegas: ravens by 3.5
Zoltar: rams by 6 dog = falcons Vegas: rams by 10.5
Zoltar: fortyniners by 6 dog = seahawks Vegas: fortyniners by 9
Zoltar: cowboys by 6 dog = bengals Vegas: bengals by 7.5
Zoltar: broncos by 6 dog = texans Vegas: broncos by 10
Zoltar: raiders by 1 dog = cardinals Vegas: raiders by 6
Zoltar: packers by 9 dog = bears Vegas: packers by 10
Zoltar: bills by 2 dog = titans Vegas: bills by 10
Zoltar: eagles by 4 dog = vikings Vegas: eagles by 1.5
Zoltar theoretically suggests betting when the Vegas line is “significantly” different from Zoltar’s prediction. In mid-season I use 3.0 points difference but for the first few weeks of the season I go a bit more conservative and use 4.0 points difference as the advice threshold criterion.
At the beginning of the season, because of Zoltar’s initialization (all teams regress to an average power rating) and other algorithms, Zoltar is very strongly biased towards Vegas underdogs. I probably need to fix this. For week #2:
1. Zoltar likes Vegas underdog Falcons against the Rams.
2. Zoltar likes Vegas underdog Cowboys against the Bengals.
3. Zoltar likes Vegas underdog Cardinals against the Raiders.
4. Zoltar likes Vegas underdog Titans against the Bills.
For example, a bet on the underdog Falcons against the Rams will pay off if the Falcons win by any score, or if the favored Rams win but by less than 10.5 points (in other words, by 10 points or less).
Theoretically, if you must bet $110 to win $100 (typical in Vegas) then you’ll make money if you predict at 53% accuracy or better. But realistically, you need to predict at 60% accuracy or better.
In week #1, against the Vegas point spread, Zoltar went a very good (but lucky) 5-2 (using 4.0 points as the advice threshold). Zoltar’s predictions against the point spread were correct except for recommending the Rams over the Bills (the Rams were beaten badly, 31-10, and so the Bills easily covered their 2.5 point spread), and recommending the terrible Jets against the Ravens (the Jets lost 24-9 and so the Ravens covered their 5.5 point spread).
Just for fun, I track how well Zoltar does when just trying to predict just which team will win a game. This isn’t useful except for parlay betting. In week #1, just predicting the winning team, Zoltar went 7-8 which isn’t very good but is typical of the first few weeks of the season. Note: There was one tie game: Colts 20, Texans 20. Vegas did very well just predicting winners in week #1, going 10-5.
Zoltar sometimes predicts a 0-point margin of victory. There are two such games in week #2. In those situations, to pick a winner (only so I can track raw number of correct predictions) in the first few weeks of the season, Zoltar picks the home team to win. After that, Zoltar uses his algorithms to pick a winner.

My NFL prediction system is named after the Zoltar fortune teller machine you can find in arcades. Left: A Zoltar machine outside of Houdini’s Magic Shop in the New York New York hotel in Las Vegas. Sadly, I think the shop is gone now. Center: Wagering on NFL games is a multi-billion dollar business. This is a photo of the sports book (betting area) at the MGM Grand hotel in Las Vegas. Right: This is a sheet where you can see the point spread for a given week. You can place a bet by going to a person at a desk in the sports book, or you can place a bet using a terminal or online.

.NET Test Automation Recipes
Software Testing
SciPy Programming Succinctly
Keras Succinctly
R Programming
2026 Visual Studio Live
2025 Summer MLADS Conference
2026 DevIntersection Conference
2025 Machine Learning Week
2025 Ai4 Conference
2026 G2E Conference
2026 iSC West Conference
You must be logged in to post a comment.