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We’re constantly bombarded by news about self-driving cars, how automation will take over all of our jobs, and how artificial intelligence is something to embrace with caution. It’s certainly not all bad though!

Even if the realm of sports betting algorithms and AI are still in their early stages, some “sharps” are already capitalizing on its potential by using computer systems to bet on sports with astounding accuracy. We are still at the point, however, where human analysis and the trained eye of “sharps” are just as crucial.

If you want to know how sports betting algorithms work  – and how they’ll absolutely affect your future sports betting career –  keep reading!

How Do Sports Betting Algorithms Work?

When we discuss sports betting algorithms, we have to define a few terms first. Computer science is complicated!

Algorithms are a mathematical formula that can be created to solve problems based on the different kinds of data received. Therefore, algorithms can be designed to “solve” the outcomes of sporting events, based on reported data.

Algorithms can also be used to process and categorize data. In essence, this is simply a different definition of “solving a problem.”

What Kind of Data Do Algorithms Need?

The data inputted into a sports betting algorithm isn’t too crazy. For example, if someone was writing an algorithm with the express purpose of predicting an NFL game, the algorithm could make predictions using data like a teams’ home winning percentage, rushing yards, and successful reception percentage.

Currently, the amount of sports data available is incredibly vast. Online, there’s a wealth of traditional information on teams and players open to the public, but many of the advanced analytic tools (like Corsi, Fenwick, etc.) are also just a few clicks away. The availability and accessibility of information on the web dramatically increases the potential of what sports betting AI and algorithms are able to accomplish.

Because these formulas require so much data, it’s easier to create betting algorithms when there are tons of data points to analyze. Algorithms are much more accurate and comprehensive when they have many different points to analyze.  As such, a successful sports betting algorithm combines technology and publicly-available information.  In practice, creating an algorithm for NFL game predictions is inherently easier than building one for, say, a professional tennis match.

Machine Learning and Neural Networks

Machine learning is when a form of artificial intelligence is applied to algorithms. The application of machine learning produces a system with the ability to learn from – improve on –  experience. A machine learning algorithm can both access and process the data it needs to make decisions, predict outcomes, and operate successfully without constant tweaks and manual input.

A machine learning algorithm is technically artificial intelligence. Not only can it make independent decisions and predictions without any direct human involvement, but it’s also based upon something called “neural networks.”

What Is a Neural Network?

We’d need several pages to explain exactly what neural networks are, but in short, they are programs built to mimic the operation of neural networks inside the human brain. Studies have shown that building neural networks into machine learning algorithms is a highly effective way to improve their ability to solve complex problems, quickly.

Machine learning algorithms are growing in capability and availability every year, and they are doubtless the hottest and most promising tool related to both classification and prediction.

There are billions and billions of dollars every year wagered in the global sports betting market. A machine learning algorithm that can predict the outcome of sporting events is massively profitable to whoever is able to get their hands on it.

Of course, there are lots of intrepid entrepreneurs out there attempting – and succeeding – at it as we speak.

Who Makes Sports Betting Algorithms?

The rise of sports betting algorithms has a lot of crossover with the brightest minds from the stock market. Sports betting algorithms are yet another tool that “sharps” have lifted from the increasingly interlinked fields of sports betting and finance.

Since the turn of the 21st century, an expanding number of super successful money managers use algorithms to process data faster and more accurately. They remove human error, as well as human bias (emotional investments).

Machine learning algorithms have been wildly successful in finance. The best and the brightest in the finance world are now applying these same advantages to yet another profitable enterprise: sports betting.

The Real Life Application to Sports Betting

We’ve spoken a bit about Stratagem in our article on hedge funds, but here’s how sports betting algorithms actually work:

Strategem designs their sports betting algorithms to predict European football games. They believe that soccer games are among the most predictable events in the entire world. In their words: “They’re short duration, repeatable, with fixed rules. So if you observe 100,000 games, there are patterns you can take out.”

The idea at Strategem is relatively straightforward: Discern patterns, absorb them, and gain an edge over bookmakers. Finding patterns (and factoring them into your bets) can equals a ton of cash in sports betting!

Using machine learning, the proprietary algorithms Strategem has developed are exceptionally well-suited for processing and analyzing a tremendous amount of data. Their goal is to create a sports betting algorithm that can provide real-time insight into live matches. From there, they hope to apply the algorithm to live-betting at different sportsbooks.

Stratagem is still relatively far from creating an algorithm which can watch live events and offer cutting-edge insight (for example, they haven’t figured out the algorithm to avoid factoring in replays). However, machine learning is still helping the company gain an edge in its sports bets. For example, machine learning algorithms are already being employed by Stragagem to find the most attractive lines across sportsbooks.

What’s undeniable is that these algorithms are improving rapidly, and they’re only going to get better. As they become more precise and accurately-engineered, more people will start relying on them.

Don’t believe us? Look at the financial world, where machine learning and algorithms started out as a niche specialty during the 1980s. Now, every financial institution and fund worth its salt employs algorithms to process information and solve problems. The future is here for sports betting, though it may be unevenly distributed at the moment.

What Are the Flaws With Sports Betting Algorithms?

As helpful and intelligent as these algorithms and machine learning are, they aren’t much use unless they’re supplemented with real human analysis. Artificial intelligence can create maps (or partial representations) of sporting events, but they can’t fully represent the “territory”, which refers to the entirety of the sporting event. The data produced by algorithms still has to be interpreted by, and acted on, by humans.

Say that a star NHL player stays on the ice, despite suffering a horrific injury. This is something that an AI presently can successfully understand or process. A sports betting algorithm can’t pick up on the player grimacing or playing with dramatically-reduced effectiveness.

Additionally, a sports betting algorithm can’t pick up on shifts in momentum, or its effect on the emotions and psychology of players.

It’s worth noting that the most significant predictive factor in any sporting event is what the team’s starting lineup looks like. Acquiring this information before it’s formally released to the public can prove to be immensely profitable. For example, if you knew Tom Brady was going to sit (before the public did), you could bet on the opposing team and get a great price on them.

Naturally, AI and sports betting algorithms don’t acquire this information on starting lineups before the bookies do. You need insiders, sources, and the ability to build mutually-beneficial relationships with other people to acquire it. This is still the realm of humans: Chatbots aren’t getting the inside scoop quite yet.

Learn More About Algorithms to Boost Your Winnings

As is the case with an application of AI, algorithms, and machine learning to any business, small gains in the capability this new technology can end up being immensely profitable. Nowhere is this truer than sports betting. However, computers aren’t going to supplant true “sharps” anytime soon, but it can’t hurt to start studying now!