From Code to Cash: AI’s Role in Modern Sports Betting

A discussion on the new age of sports betting and how artificial intelligence can both help and harm consumers.

Table of Contents

Overview

Sports betting has become a global phenomenon recently because of technology. The latest developments in sports tech, data collection, and app development have allowed sportsbook companies to expand on their business through mobile sports gambling. Companies such as Draftkings, BetMGM, Fanatics, and countless others have developed online sportsbooks with easy access because of smartphones. With this creation, those who have been sports betting in person, those who enjoy sports, and those who aspire to make money have all come together to attempt to benefit off the new age of online sports entertainment. Sports leagues are even partnering with these now online sportsbooks to push out advertisements and grow the community of each game. All of this is possible because of technology. Advanced methods of fast and real-time data collection allow sportsbook to analyze game information to make predictions and create betting lines for customers. But how are these predictions made? And how might companies utilize AI for profit? In this article, I will discuss these questions, the debates of online sports gambling, and introduce how artifical intelligence helps both companies and consumers try and make money.

Sportsbooks and AI

In the end, online sportsbook companies have one goal in mind: to make a profit. But how do they do this? With today’s modern technology, an intelligent sports bettor can do some research and tutorials to create their own AI model to try and “beat the books”. One way that sportsbooks are innovating and incorporating AI for their hopeful monetary benefit is by enhancing user experience. Ricky Casino in Australia uses AI to focus on improving their book’s usability. For example, they use AI to suggest bets for users to make based on their history, tailoring specific games and odds to the user in question. They also implement AI for fraud detection purposes which “flag suspicious activity, maintaining the safety and integrity of transactions”. Additionally, AI is used to gather and process the most recent, typically real-time, data for ongoing sporting events. See, sportsbooks will offer live odds for sporting events to increase the amount of bets placed on games, in an attempt for the book to make money on not just bets for the game before it starts, but also on bets during the game, where odds change based on the state of the game. AI allows odds to be calculated in seconds which reflects variables such as injuries, scores, or even factors that the average sports bettor or fan might not be aware of like historical trends.

Sports Bettors and AI

Now that we’ve discussed AI from the sportsbooks side, how might either the everyday/average or “professional” sports bettor make use of it? The first topic I want to highlight that comes to mind is organizations that advertise AI models for sports betting success. One group called Killer Sports has a paywalled subscription that gives consumers access to an “AI Trend Vault” which they market as predictive analytics powered by AI to give bettors improved insight and an “edge” over the books. This database continually updates with new data and change in real-time using AI to give more accurate trends. Systems like these are very common online and can encourage bettors to pay extra in attempts to find the best plays. Another company called Betting Pros has their own “Sharp AI” chatbot that they advertise as being a sports betting assistant to help bettors with prop picks, game projections, best odds, and even betting education. The existence of these AI tools gives consumers access to all kinds of new information to help in their winning efforts. Moreover, it might even convince consumers to learn coding and AI implementation so they can make their own sports betting models!

Competition

So both sportsbooks and sports bettors have access to available data and machine learning algorithms. But how does each party try to obtain an advantage over the other? For sportsbooks, they are able to partner with and/or buy companies that specialize in sports data collection which can give the books access to more accurate and insightful trends. For example, one of the top sportsbooks, Draftkings, recently purchased AI-based oddsmaker, Sports IQ, a company that specializes in using machine learning models to create more advantageous odds for sports betting parties. Also, sportsbooks has the money to hire data scientists who specialize in AI, machine learning and/or sports data that have more knowledge on generating predictions better than the average sports bettor.

However, from the sports bettor side, there are numerous groups that have started their own businesses with paywalled picks and trends which give them a believed “edge” over the sportsbook. An example is an app called Pikkit, which is a platform for sports bettors to track their picks, trends, and results. It’s also a functional community of bettors to share picks, view betting lines, and see popular picks/trends for the day. One functionality of this app is it’s closing line value (CLV) calculator which users can access if they buy a Pikkit pro subscription. Behind this paywall, users can view betting line trends in an attempt to place a bet with the best odds before the sporting game/event starts. Bettors and the CLV function try to determine when you should place a bet by predicting when the value will eventually drop in favor of the books, as placing a bet before the odds get worse could allow a bettor to make more money than they otherwise could have. The CLV tool is an example of a machine learning tool that users can both use or make, in an attempt to beat the books.

Implications

Sports betting of course has very formidable monetary and legal implications and there are many differences in its availability throughout the United States and various countries across the world. However, one intriguing implication I found was that even sportsbook companies are attempting to innovate and use generative AI to expand upon their previous uses of machine learning. For instance, Draftkings now uses generative AI to perform code checks and code testing, along with improving customer experience. They also mention how they mainly use generative AI for internal purposes, like image generation and marketing, yet see this new technology as becoming integral within their compnay.

Takeaway

While the typical or professional sports bettor might think they can outsmart the books, they might never be able to just because of the sheer amount of money and brains that sportsbook can implement to make a profit. Both parties are leveraging machine learning and AI in different ways, yet both hope to use it for the same reason. I think it’s incredibly interesting that sportsbooks are mainly only using generative AI for internal use like code quality and customer support while it that sports bettors might use generative AI to help them problem solve and be more efficient in their endeavors. The competitiveness between books and bettors will always be a fascinating one, especially in a modern age where each try to use the newest technology to develop winning methods.