Elo Ratings

  • Calculating Expected Value Using Moneylines

    Calculating Expected Value Using Moneylines

    This is an excerpt from a recent edition of the Staturdays newsletter. Subscribe to get weekly content like this in your inbox.

    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:

    • Moneyline: A bet placed on a team to win outright, regardless of the score. Usually you’ll see these formatted like “-350” or “+200”. These are called “American Odds”. Seeing “-350” means that you’d need to bet $350 to win $100, plus your initial bet back, so $450 total. Seeing “+200” means you would win $200 if you bet $100, for $300 total. The team with the positive odds are the underdog.
    • Spread: The points a team is expected to win or lose by. It is usually written in terms of the home team, so if it’s Alabama @ Georgia and the spread is -3, that means Georgia is expected to win by 3 points. If you see a line and it just says “Alabama +3”, that would mean that Alabama is expected to lose by 3 points in whatever game they’re playing that week.
      • If you were to bet on Alabama +3, that means you expect them to “cover” the spread, or lose by less than 3 (or win outright). If you bet on Georgia -3, that means you expect them to cover, winning by more than 3.
      • Oftentimes you’ll see the spread at half-points, like “-5.5”. That just means that if the favored team wins by 6, they cover, and if they win by 5, they don’t. This just ensures that no bet is a “push“, meaning everyone get’s their money back because the spread and actual score margin were the same.
    • Implied Win Probability: This is the win probability (WP) calculated based on the moneyline odds set by sportsbooks. You can actually take the fact that a team has +400 odds and convert that into a likelihood of them winning. To do this, you follow two simple steps:
      • If the odds are positive, do 100 / (odds + 100)
        • So for +400, it would be 100 / (400 + 100) = 100/500 = 20% Implied WP
      • If the odds are negative, do odds / (odds + 100)
        • So for -300, it would be 300 / (300 + 100) = 300/400 = 75% Implied WP

    Calculating Expected Value

    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.

    Elo and Moneylines This Season

    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.

    A list of all the games from Week 7 of college football with positive expected value.

    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 Bottom Line

    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.

  • “Oh-🦆”– Ryan Day

    “Oh-🦆”– Ryan Day

    Plus: A thought about ‘Bama-Florida, and a 10% Vegas underdog 👀

    Well that just happened…

    We ended up having some quality college football games—and even better weather—on Saturday. The sun was out, which meant double-TVs on the deck (had to watch the US Open women’s final too, of course!) And I watched another Pac-12 game, this time against the Big Ten, so two halves make a whole!

    I’ll be the first to admit that I was wrong on two fronts last week.

    First, Ohio State did indeed have to worry about the Oregon Ducks, despite their 89.4% win probability, which, as we know, is nowhere near a certainty.

    Second, the Week 2 slate was not weak. Well, it was, but not if you watched all the right games and ignored whatever was going on down in the SEC.

    Wow, that was so brave of me.

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    The Buckeyes made it look close at the end, but it never felt close. Oregon controlled the game on both sides, first—it felt like—on defense, holding OSU to a touchdown in the first half. And then in the second half, with an explosive offense that ran past OSU defenders.

    And the run-game is what set the two teams apart. According to collegefootballdata.com, Oregon running back CJ Verdell averaged .38 Predicted Points Added (PPA) per play, while Miyan Williams for OSU managed only .07. The QBs were both productive, with .38 PPA for C.J. Stroud and .41 for Anthony Brown. So no Stroud slander just yet. The Buckeyes’ issues run deeper.

    Drew was working on our in-game win probability model last weekend, and found that we were very low on Ohio State’s chances at the half, even though they were only down 7!

    Near the end of the game, our model shifted sentiment, giving Ohio State a 69% chance to pull out the win. We’re not exactly sure what changed, but Ohio State were indeed in it down to the wire. There are still plenty of kinks to work out, but it was interesting to see the big swings as the game progressed.

    In other big Week 2 results, Iowa upset Iowa State (although is 10 beating 9 really an upset?), unranked Stanford walloped #14 USC and cost Clay Helton the keys to his program, and Arkansas did the same to #15 Texas, giving them a taste of what the SEC-life might be like in a few years. If they struggled to find success in the Big-12 after being “back” for the last four years, it’s gonna take a few decades of being “back” in the SEC before they see any success in that conference.

    Oh, and Virginia Tech beat Middle Tennessee. What’d I tell you? Easy money.

    Rumors Swirling

    With Clay Helton’s firing, that special time of year is coming early this fall, and will unfortunately stick with us all season: who will be the next coach of USC? Unsurprisingly, James Franklin’s name was one of the first to be thrown out there. I’ll squash this rumor here and now by asking the simple question… why? Why would Franklin want to leave what he’s got in Happy Valley? He has the #1 recruiting class for 2022 (USC’s is 29th, for now…), the #12 class for 2023 (USC is not ranked), a top-10 football program right now, and the 7th highest salary in college football, which more than covers the cost of living in central Pennsylvania.

    And now, my “only conceivable reasons for anyone to want to go to USC” list:

    – In-N-Out

    – Getting a sick tan

    – Putting avocado on everything you eat

    And these are easily outweighed by fires, mudslides, and running out of water all the time. So keep looking, USC.

    Coming Soon

    I’m working on an article about quarterbacks and interceptions. Namely, how do quarterbacks play after throwing one? Are they rattled? Do they become more conservative? More accurate? We’re going to find out, and see who cracks under pressure, and who balls out in the face of adversity. Be on the lookout for that article to kickoff your Saturday morning.

    I don’t have much to share with you, but for now here are the most-benched quarterbacks since 2014 after throwing an interception.

    Week 3 (already?)

    It’s the final week of non-conference play (kinda). And thankfully, we have some teams challenging themselves this weekend. Highlighted by none other than Auburn vs. Penn State in a primetime White Out game. Elo has Penn State as slight favorites at 60.8% win probability in this matchup, but it could go either way.

    Below are the win probabilities for the Power-5 teams, and, where appropriate (or inappropriate), my commentary. If you’re looking for Group of 5 games, check out staturdays.com.

    Big Ten

    Nebraska playing Oklahoma this weekend is exactly like when you sign up for the marathon a year ahead of time hoping that you’ll be in shape by the time the race comes around. As is usually the case, Nebraska will be puking on the sidewalk 3 miles in, and might duck into a Porta-Potty, take off their race bib, and try to blend back into the crowd.

    But in all seriousness, we have a lot of other competitive games this weekend.

    ACC

    Virginia Tech @ West Virginia looks like the game to watch here, and keep an eye on Virginia, who is underestimated by Vegas by over 10 percentage points compared to Elo 👀.

    Big-12

    Pac-12

    I will not blame you if you don’t watch any Pac-12 football this weekend. It’s okay.

    SEC

    Florida have more of a chance to beat Alabama than Oregon did to Ohio State last week, and are underdogs by about just as much. Think about that.

    Think about it… don’t act on it.

    That’s all I’ve got for you. Enjoy your weekends and remember to check out my article this weekend!

    – Kyle

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  • Bowl Game Win Probabilities

    Bowl Game Win Probabilities

    Win probabilities for remaining bowl games, including the CFB Playoff Semifinal matchups and the rest of the New Year’s Six bowl games. Home-field advantage adjustments were removed for these games.

    Elo win probabilities for all the upcoming bowl games.