The NFL season is now three weeks old, and if you’ve been using MySpari’s NFL model to make some bets, you’re probably feeling pretty good. When it comes to data, the sample size is everything and three weeks isn’t much of one, but there’s no denying that the 10,000 sims model employed by Spari has been on a heater to start the season.
The companion tool to Spari’s model data is the Edge Report, which helps identify those areas where the model’s prediction differs greatest from the Vegas sportsbook consensus and thus might be ripe for betting. When it comes to game totals (over/unders) and spreads, those edges are provided in the form of raw integers, which (hopefully) makes them relatively straightforward to interpret. But after going through most of an NBA and MLB season and now in the early stages of NFL, I’m reminded that for new and/or casual bettors, the Moneyline can be something of a different animal, and the way the Edge report presents Moneyline data isn’t always intuitive.
With that in mind, what follows here is an overview of sorts, provided to help you better understand the information Spari is providing and use it most effectively to your advantage.
Moneyline bets are fun for two reasons: 1) They’re as simple as they come – bet a team to win. That’s it. No sweating the number of points/runs, no giving/taking points on the spread. Win, lose … that’s it. 2) When you can find and bet the right underdog, Moneyline bets offer the opportunity to win you the most money. Totals and spreads will typically offer you either side of a number at close to “even” money (-110 or so), but only moneylines can give you the chance to quadruple or quintuple your money by hitting the bullseye on a lesser-favored team. If you have even a cursory knowledge of sports betting, none of this is likely new information for you. So how does Spari’s Edge report come into play?
The rest of this article is going to be a (slightly) deeper dive into two things you need to know and understand to make your Moneyline bets (and interpret the accompanying Edge Report) — Probability and Value.
Every betting odd you see — for any sport, any outcome, at any book around the world — is, at its root, an expression of implied probability. Odds of +100 or -100 mean that the sportsbook believes that event has precisely a 50% probability of success. The further away from -100 you get, the more likely the probability, and conversely, the further away from +100 you get, the less likely the probability.
A Google search can lead you to one of any number of online calculators, but below are some sample moneylines, along with their implied probability for quick reference:
+100 = 50%
+150 = 40%
+250 = 28.6%
+600 = 14.3%
-110 = 52.4%
-150 = 60%
-300 = 75%
In a world with no vig from the sportsbooks, the odds on either side of an outcome would be mirror images:
Buffalo (-7.5), -110 (52.4% implied probability) vs.
Detroit (+7.5), +110 (47.6% implied probability)
Instead, you’ll typically see both sides offered at -110, meaning the sportsbook thinks both outcomes have just over a 52% chance of occurring.
“But if both outcomes have a 52% chance of success, that’s 104%!! How can you have more than 100% probability?” you ask, correctly. That “extra” 4-5% is where the book/casino makes its money. Moneylines, especially in the NFL, aren’t offered at close to even money all that often, and when they are, it’s basically Vegas saying the game is a toss-up. But you can still find the juice when comparing both sides of a Moneyline. To use a recent NFL example, the Chiefs were -320 (76% implied prob.) at home against the Chargers at +260 (28%) … 76 + 28 = 104, and there’s that “extra” 4% again.
Spari’s Moneyline Edge Report combines two pieces of information and converts them to side-by-side equivalents to help you make your betting decision:
- The current consensus Moneyline odds (eg. -375)
- The Spari model’s expected Win percentage (eg. 79%)
The Edge Report converts the odds to an implied probability (-375 = 78.9%) and converts the model’s expected win% to odds (79% = -376). In this example, you can see that the sportsbooks and the model are pretty much in lockstep, so there isn’t any “edge” to be found. For other games, any difference between the sportsbooks’ implied probability and Spari’s implied probability is expressed as the % difference between the two.
Let’s use week 3’s Atlanta vs. NY Giants as an example:
ATL is offered at +122, which is a 45% implied probability. However, Spari expects the Falcons to win this game 57% of the time. 57 – 45 = 12, and 12 / 45 equals an “edge” of 26.5%. Spari thinks the Falcons are 26.5% more likely to win this game than Vegas does, so the model suggests this would be a good betting opportunity. (Note: Always—ALWAYS—supplement with your own research before placing a bet.)
Now, that’s a fair bit to absorb, especially if you haven’t previously considered available odds in the context of their corresponding probability. But if you take nothing else from this article, let it be this:
Just because the Edge Report shows an “edge” on a particular Moneyline (even a significant edge) does NOT mean the model thinks that team is going to win.
Granted, that is more than a little counterintuitive when we’re talking about Moneyline bets. Isn’t the whole point to bet on who’s going to win? Well…yes, but this is where and why “Value” matters.
I’ll preface this section by acknowledging that the concept of “betting for value” is probably better applied in other sports — like MLB or NBA — with much longer schedules, more random variance, and more volume. The NFL, where betting opportunities are fewer and further between (at most, 16 games a week) and there is much less parity between the teams, top to bottom, is probably not where you want to look for value, even if it’s there. This is why, in part, I thought it was essential to provide this overview in the context of the NFL season. But the concepts here are equally applicable to Moneyline betting in any other sport.
In Week 3, the single most significant “edge” for NFL Moneylines was the NY Jets (@Denver), with 92.5% (!!). The Jets are awful. The Broncos are 2-0, and they’re at home. Why on earth would Spari recommend betting on the Jets (at +450 odds)? The truth is, Spari is not exactly “recommending” it. What the Edge Report is saying is that there is VALUE in making that bet. In theory, using the Jets-Broncos game as an example, it works like this:
The consensus odds on the Jets ML are +450, which is the equivalent of just over 18% probability of success. If this game were played 100 times, the sportsbooks think the Jets would win 18 times. Spari’s model, on the other hand, gives the Jets a 35% chance of winning, or 35 wins if they played it 100 times. The Edge Report, as constructed, is saying you can get a 35% probability of success at the price of 18%, and over the long run, taking advantage of that difference is going to be profitable. For a single-game outcome, a 35% chance of winning is still not great, and you could be readily excused for not wanting to jump on that bet, but theoretically, across a large enough sample size, laying that bet is going to result in the Jets winning often enough to make you a nice bit of money.
Let’s put it in monetary terms:
You wager $10 on the Jets at +450 ten times. At Vegas’s 18% probability, the Jets will win that game twice. So for the eight losses, you’re down $80. For the two wins, you profit $45 each ($90 total), so your net winnings are $10 (note that it’s +$10 and not break even because we rounded up from 18% to 20% for simplicity).
But let’s say Spari’s 35% is the “real” probability of winning. We’ll even round down to 30% to make the math here easy. Under this scenario, the Jets lose 7 out of 10 times (-$70), but win three (+$135) for a total profit of $65. And that’s where you see the effect of value — you got 30% (or 35%) odds at the price of 18%. In the immortal words of Charlie Sheen … #winning. You have to be mentally prepared to expect to lose that bet more often than you’ll win it, but the reward when the Jets DO win, will be enough to make up for it … again, over the long run.
I should also note that when you do make these “value” bets, you generally don’t want to use a full unit to do so — again, you are expecting to lose most of the time, so please make sure you manage your bankroll accordingly. If you really want to jump deep into the weeds, you can Google “Kelly Criterion” and find a good calculator, but for now, I would recommend sticking to 0.5u or 0.25u for these bets, depending on your comfort level.
In sum, looking at “edges” when it comes to Moneyline betting is a very different animal than totals or spreads, and I hope this article has helped illustrate why. If you’re not looking at Moneyline bets and edges in terms of probability and value, you’re probably doing it wrong.
Find me in Discord (@Simms34) if you have any additional questions, and I’ll be happy to help!