Volume Betting for Profit
Old school advice isn't always right
If you've been around sports betting for any amount of time, undoubtedly you've heard the advice that you should 'bet less games' or 'be more selective'. We disagree. Especially when it comes to making money betting the Beautiful Game. Let us explain why.
Winning money at sports betting is all about putting your money in +EV (positive expected value) situations. Nobody can know for sure exactly which plays will win and lose, but over time if you find enough +EV spots, you will come out ahead. We set our model threshold at 12%. If any bet shows a +EV of 12% or more, it is a play for us. Often, this can mean having more than 15 plays on a Saturday (across the many European and North American leagues we cover). We're averaging 35 plays per week on our VIP members service. Let's say that we limited ourselves to 3-5 plays per day (a very common number you will see from handicappers) to 'be more selective'. That would likely reduce our volume to about 20 plays per week (5 per weekend day and 10 total during the week).
Using our actual numbers : 35 picks per week at a 4% ROI has produced 107.5 units of profit during our 16 months in business (about 2,200 plays). This means a $100 per unit bettor is up more than $10,750 following our plays.
To gain these results, we are producing:
-109 average price
Risking 1.21 units per bet.
If we cut back to 20 plays per week at those same numbers, we would only have produced 61.3 units of profit (57% of the plays = 57% of the profit).
Clearly that's not the end of the story. Those who believe in being more selective would say that by doing so, we can hit a higher ROI than 4% thereby closing that gap. But in order to get back to the same 107.5 units of profit, we would need to increase our ROI to 6.8% over that smaller set of plays. That's a 70% increase in the ROI needed. We are already hitting 54.4% winners on -109 average plays. To get to 6.8% ROI, we would need to increase our winning percentage to about 55.7%. This might not seem like much, but increasing win percentage by 1.3% is not easily done. This is especially true in a high-variance, low scoring game like soccer. The more volume we play, the more we reduce our variance. That's statistics 101.
We would argue that we should be looking to bet as much volume as possible that can produce us this same ROI and winning percentage. This doesn't mean that you shouldn't always try to be improving and finding bigger edges. Of course we should and do.
It's easier to hit a reasonable winning percentage, a positive ROI and make your profit over a larger set of plays, then it is to hit a much higher percentage of plays over a smaller sample size. If you find that the volume leads to you not being able to play all the suggested plays, reduce your unit size.
There's another issue we've found in the theory that reducing the number of plays will lead to a higher winning percentage. It's the idea that when you edit your plays and only select the strongest subset, that those will ultimately prove to win at a higher rate!
How many times have you neglected to make a few of your plays only to see those win and lose the ones you decided to play? It happens a lot doesn't it?! I know that's anecdotal, but allow me to use our SoccerPicksClub model again to bring some data to this point.
We've spoken about our model in other blogs. The basic premise is our model projects an expected score for each team based on a few key variables. In it's over-simplified form, (without giving away our proprietary information) if the expected score produces a 12% or higher edge compared to the line / price we see enough value to make a play. Often, there are sides or totals that see 20-30% edges. Most of the plays come from edges of 12-18%. When we were first starting, we tracked the value that these higher modeled edges would produce. We found that there was no statistical significance to the amount of edge the model produces. Why? Likely, there are human / situational factors that the math model cannot account for properly. So in some ways, if the edge seems too strong, we might assume we should take another look to make sure there isn't a reason that it's this far off.
We continued to dive deep and see if we should be eliminating those outliers or adding other variables to account for other factors. What we've found is that they win at almost exactly the same rate as the lower edges do. So we value them exactly the same.
If we can't edit our volume based on modeled values, is there another way to do it?
The answer is yes and we've begun to do so.
As our data grows, we've definitely begun to find leagues where the model performs much better than others. As such, we've eliminated a few leagues in 2022 and our winning percentage has grown substantially!
There is a caveat here as well. Sometimes a league where you perform poorly one year, can be very good the next and vice versa. This is part of the variance you should expect in any sports betting markets. A great example of this for us is German Bundesliga. From Dec 2020 - May 2021 the first season we started SPC, we lost money betting on the Bundesliga. But in the 2021-2022 season we are hitting an astounding 73% in this league! Had we given up on Germany, we would not be where we are today.
Bottom line is this: We continue to learn and evolve over time as the data gets stronger. But we will continue to play all the qualifying values we see. Allowing for proper unit sizing in order to make all the plays will allow every member to maximize their profits.
See you at the cashier's window!
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