A Pragmatic Approach to Using AI for Sports Predictions
With the ubiquity of artificial intelligence tools today, it’s understandable that these tools have been promoted for their use in sports predictions, covering both fantasy sports and betting. It is, let’s say, an interesting proposition, though there are plenty of pitfalls.
In the simplest terms: AI tools can help with sports predictions. That’s a given, simply because AI can analyze data more effectively than a human can. However, it is far from being a magic bullet. Sports are unpredictable, and no model, whether AI or otherwise, can be 100% successful.
That said, if we accept there are ways AI can be useful, we’d suggest a pragmatic approach to thinking about it. Consider some of these ideas and things to be wary of:
Consumer-facing AI models have limitations
One issue we face is that AI is often spoken about as a singular entity, with most people automatically thinking about ChatGPT or rival models like Anthropic’s Claude. But different models are more adept at different tasks. Moreover, you can’t just give ChatGPT a list of College football game odds and expect it to pick a winning formula. It doesn’t work like that.
Data is the key consideration
Just as you might use professional data services to make fantasy football picks, AI will require that data to get ahead too. Again, something like ChatGPT is not going to have access to that bespoke data that professionals use (the information will be paywalled), but it can be fed the data that you have access to.
AI must be focused with prompting
The key strategy is to keep the AI model focused on your purpose. To do that, you may need to narrow your own focus via prompts, i.e., narrow down what you are looking for. It’s no good asking the AI model who will win the Super Bowl: you’ll get a generic answer that you could find in any sports publication. What you want to do is focus on specific teams, players and markets.
Focus on finding value
As we said, there is no magic bullet and nobody can predict sports with 100% accuracy. However, AI’s main benefit might be the fact it can analyze data and compare it to the odds or fantasy market. For instance, if a basketball player was X odds to achieve over Y rebounds in a game, the AI model may be better placed than a human to decide whether those odds represent value or not. Of course, it is again dependent on the model having access to good data.
Be wary of subscription services
With the advent of AI models comes the arrival of AI subscription services that promise help with sports predictions. While some services may be genuine, we would be skeptical of those that promise success. As we have constantly said, there is no magical bullet: AI can help analyze sports data better and that ‘may’ deliver a profit, but that is not the same as guaranteeing a profit. Anyone telling you otherwise should be treated warily.
Consider what happens next
Let’s just say for argument’s sake that AI gets really, really good at sports predictions, able to analyze and beat the sportsbooks at every turn. What will happen to the sports betting industry? It could open up a lot of problems, and the operators would need to react in such a scenario. It would likely mean less advantageous odds to protect the business model, or else the industry would become unprofitable.
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