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Another tumultuous week of college football has shaken up the rankings once again. The top 4 stayed put, but some noticeable slides were Texas from 19th to 27th, Penn State being overtaken (who were on a bye week), and four-spot drops each from Iowa and Florida.
Teams making upward moves included Michigan State, Oklahoma State, LSU, and Pitt, who rose four spots into the Top 25 for the first time this season.
Here are the full ratings below.


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Let’s talk moneylines and expected value, something that’s essential to understand if you want to stand a chance at profiting off sports betting in the long run.
Before I go into too much detail, let me just clarify some key terms for any new people to sports betting:
So one thing you need to do when evaluating potential bets is look at expected value. If not, you’ll end up placing bad bets and getting underpaid for your wins and overpaying on your losses, which is a good formula for going bankrupt. Expected value is basically the average you can expect to win or lose if you place the same bet many times. So if you bet $10 on a -200 moneyline (66% implied win probability), and that team actually wins that matchup 66% of the time, then you can expect to win nothing on that bet on average.
But, if you can find a team that has +200 odds (33% implied win probability) that you actually think you know has more like a 45-50% win probability, then you can expect to make a profit on bets like that in the long run. Maybe that first one, or three fails, but over time, assuming your win probability model is tuned right—meaning teams with a 50% win probability actually win 50% of the time, not more, not less—you will profit.
Let’s clarify this with an actual formula real quick:
Expected Value = (Potential Profit * Predicted Win Probability) – (Potential Loss * Predicted Lose Probability)
“Predicted Lose Probability” can also be written as (1 – Predicted Win Probability) since they’re inverses.
Let’s also do an example real quick. I’m placing a $10 bet on a team with +200 (33% Implied Win Probability) with my predicted win probability being 50%.
If I win the bet, my profit will be $20 ($30 total minus the $10 I bet). If I lose the bet, my loss will be the $10 I put down.
So the formula get’s us this.
Expected Value = ($20 * .5) – ($10 * .5) = $10 – $5 = $5 Expected Value.
So this would be a positive expected value bet because a team that Vegas is saying wins 33% of the time, I have winning 50% of the time, and if my model is tuned correctly, then I will make money on bets like this over time.
So let’s say you took every bet that Elo has recommended that had positive expected value, even if it was just 10 cents. Well, bad news: You’d be down nearly $70 after almost 200 bets, assuming each bet you placed was $10 (not advisable).
So far this season, right around $6 in expected value has been the breakeven point, meaning you’d be profiting if you bet on all the games where a team had greater than $6 in expected value. Now ideally, when the season ends, we’d want the breakeven point to be $0, so hopefully by then that’ll be the case once the sample size has increased.
Unfortunately, $6+ expected value opportunities don’t come along too often (only 38 times so far this year), because Vegas is pretty in-tune with what’s going on with these teams, and they also set the lines slightly in their favor no matter what (this is referred to as vig).
Here’s an example of applying the Expected Value calculation using this week’s games. You’ll notice that a lot of the teams with the highest expected values are the undesirable teams like Navy, Georgia Southern, Hawai’i, and Kentucky, who are huge underdogs this weekend against #1 Georgia, despite being undefeated themselves. These teams have the highest expected values because Vegas pays the best when underdogs win, and can tend to overlook the improbable happening, leading to massive profit opportunities.

If you look at the data, it’s these boring teams that pay the best. Georgia Southern, Navy, Hawai’i: these are the teams that get the good-paying odds, and when they hit, it makes up for a lot of the misses and then some. These can also be the ones where you take both the moneyline and the spread, and you hedge if they lose but keep it closer than Vegas thought, or boost your profit if they win.
The majority of games will have a negative expected value for both teams, so that’s why it’s important to calculate the expected value on each game before you place any bets, because otherwise you might bet on something that happens 80% of the time, and only get paid as if it happens 95% of the time, and over time that will come back and bite you (and your wallet.
We share all the positive expected value college football games each week in our newsletter, delivered to you every Thursday morning. You can sign up for free here.