Everything In Sports Betting Is A Guess
How official-looking numbers can make bad processes look good.
I’ve been in data science and analytics for over a decade now, and I have a firsthand view of how numbers can instill a false sense of confidence in so-called data driven decisions. Pick your tactic- 7 decimal points to convey the illusion of 7 decimal point accuracy, a long and multifaceted end-to-end modeling process designed to let people gawk and marvel at “sophisticated” estimation techniques, P-value hunting from A/B tests- there’s no shortage of ways to launder fundamentally flawed analysis into a pretty seeming end result. It’s part of why I’ve always preferred to stay in sports betting- your bankroll doesn’t lie over the long term, and the betting markets reward being accurate and don’t care if you got there with a flashy approach. But as sports betting becomes a more mature industry and we see more tools emerge, I can’t help but see a lot of these tools falling prey to the same tendencies of unsophisticated methods dressed up in a pretty UI and some official-sounding words behind them to convey a lot more certainty than they imply. To be clear, there will be some really good tools coming out that will in fact help people increase their win rates. (We’re obviously making sure Betscope will be one of them!) But all tools, including Betscope, are at the end of the day making educated guesses about the betting recommendations they produce. Some guesses are more educated than others, and (hopefully) the actual useful tools will win out over those that look like they may work but don’t have the results to back it up. But in the meantime, sports bettors would greatly benefit from a couple peaks under the hood of what’s going on with some of these tools.
Let’s start with one of the most common examples of tools out there- projections. You can find projections for just about anything in sports these days (team strengths, spreads/totals, prop values), and many places even offer betting recommendations off of these projections. The projection-to-bet process is simple: produce your projections, see where they differ from the market, and bet accordingly. I understand why projections are as popular as they are: they have the feeling of elegance and simplicity all in one, giving confidence that someone is crunching numbers for you and all you have to do is find where they’re different. It’s even more intoxicating if you’re making your own projections and bet them: there’s a genuine rush you might get when your projections are different than market values, because you feel like you found something based on your process, and you can’t wait to get rewarded for outsmarting the entire sports betting market. The UI for these projection-based tools gives it a sort of authority as well: they all have some explanation of their official-sounding methodology, and the numbers they display make it feel like there’s a robust method behind them, giving them some gravity and authority. This, by the way, could apply to literally any sports betting tool that shows numbers and percentages: the way the numbers are displayed make them feel scientific, which ends up being a short circuit for questioning the accuracy or methodology of these numbers.
In practice, most projections don’t actually beat the market, and if they show a different number than the market, it usually means the projection process is wrong, not the market. There are any number of common explanations why: their prediction process simply isn’t accurate enough, they can’t keep up with breaking news fast enough to produce actionable recommendations, or they have some flaw in converting projected outcomes to the distributions that betting requires. Anyone who bets their own projections into markets, myself included, has learned the hard way that profitable projections are hard; getting punched in the mouth by actual negative returns remains one of the best ways to drive improvements in your projections process. Even the good and genuinely profitable tools, of which there are a couple, have their mistakes as well. As we mentioned above, all tools are powered by many different methodologies and assumptions, each of which has its mistakes and smoothed over by any number of shortcuts under the hood, obfuscated by a seemingly official number at the end of the process. Betscope had plenty of those before it was released, and we took pains to make sure those were tamped down. (And this is a never ending process for us- there’s always improvements to be made in any model or process.)
To be fair, many tools and projections-based sites are aware of this, so they’ll often come with a disclaimer like “projections are just estimates, we recommend that they be just one part of your overall betting process.” I agree, this is good advice- but the actionability of this advice is often lacking. Personally, I think it acts as more of a liability waiver for the places who know their tools aren’t all that good. It’s easy to say “this is not intended to be investment grade advice” even though the presentation of said advice looks incredibly investment grade- it’s an attempt to have their cake and eat it too. What are you, the reader of this article, supposed to do with a line about how some tools are just intended to be part of a process? Should every ROI number just be thrown out entirely? Should projections be combined with your own subjective opinions on the game? How do you know what tools to trust if you know all of them have official-looking numbers but many of them might not work out all that well in practice?
There are a couple ways you can intelligently incorporate this information. The arduous but reliable route is long-term ROI tracking of bet recommendations produced by betting tools. In the end, if something works, the money will show up. That unfortunately places a burden on you, the user, to either track tools results yourself or rely on someone else to do it for you. But at a higher level than that, even just knowing that the numbers you see on these tools can come from wildly different approaches is empowering alone. If you know what questions to ask about these tools, you can start to deduce for yourself which tools might be good and which ones might be bad. If you start to see certain patterns in the results they produce, you can start to question some of the assumptions these tools might be making. And even when you get good numbers from tools, you can pair those numbers with information beyond just their calculations to put together pieces of the puzzle for how to find profitable bets.
None of this is admittedly all that actionable so far, and in the next couple of articles we’ll get into some far more specific use cases to illustrate some of these concepts. But for now, it’s important that you recognize that even though some of the numbers you might see out there look official, at the end of the day they’re all just guesses, some better than others. Knowing that is liberating in itself- you can free yourself of being beholden to the outputs of a specific tool and expand your lines of thinking beyond just following what’s on a page for you. Speaking from experience, it can be incredibly frustrating building a tool where we take pains to make sure our numbers are as accurate as possible, only to have compete with other tools that look flashier and more promising but don’t have nearly the same levels of rigor. But over time, the entire sports betting space has to trend towards greater efficiency, better tools, and smarter bettors. We’ll be doing our part to make sure you’re included in the last group along the way.