There was a time, not too long ago, that sports betting was like shooting craps. If you held the dice just right, performed all the rituals, and were graceful enough, you might just land a winning combination. The problem with such methodologies is the inter-reliance of multiple factors.
In statistics, the probability of multiple successive events occurring is the product of each probability multiplied by the others. As you can imagine, your odds of being correct at any given time are infinitesimally small. And yet, sports betting has only grown in popularity since its inception. It is, by some accounts, the biggest betting market in the world.
And when something is so big, it naturally attracts a lot of attention. Some of it comes from unexpected sources like the tech sector. Artificial intelligence, commonly abbreviated as AI and Machine Learning (ML), is the wunderkind of information collation, dissemination, and correlation. AI almost has superhuman computational abilities.
Many tech aficionados are quietly scratching their heads, wondering what they have unleashed on the world with AI and ML. These constructs are capable of powerful computation of big data at incredible speed. At least that’s the perception of what it can do.
From an operational perspective, AI and ML software have deep roots in the World Wide Web. ML is an AI subset. It details how machines are taught to learn from data and continually improve their performance over time. These systems build connections with a seemingly infinite number of nodes.
All the while, powerful algorithms are scouring big data in text form, putting it all together, and replying to human inputs. These human requests initiate a sequence of rapid processing, whereby the AI construct decides upon a plan of action to come up with the most appropriate and accurate response. And it’s surprising how easily AI can generate favorable outcomes.
Thanks to ongoing tinkering by human programmers, generalists, and subject area professionals, AI is learning how to answer questions much better. AI cannot understand in our sense, nor can it hear or speak from the vantage point of a human mind. And it certainly isn’t a psychic with powers of prediction. But leading AI prediction models, like sport betting on Betwhale, can significantly improve sports betting analysis, given the massive datasets they work with.
How is AI helpful for sports betting purposes?
We prefaced our expose with a series of prediction models based on the likelihood of multiple independent, related variables working in sync to generate desired outcomes. When betting on a trifecta in horse racing, the desired outcome is that horses finish in positions one, two, and three, respectively. With multiple horses running in any given race, the odds of getting positions one, two, and three correct are incredibly small.
However, past performance, current form, turf conditions, weather outlook, horse and jockey health, inclusions, exclusions, and other factors can be fed into an AI construct for an accurate assessment of potential occurrences. Each factor plays a part in determining the outcome. AI is a powerful computational resource that punters can use to simplify the analysis. And when all the number-crunching is done, the result can certainly square up with reality.
Without such tools, the human mind tends toward bias. Deep down, we have an innate leaning toward certain outcomes. This is routinely imprinted through experience, preference, or possibility. However, AI does not have emotions or human memory. It tackles every challenge on its merits. When AI systems are correctly prompted for a response using precise inputs and metrics, they are better able to deliver on expectations for sports bettors.
No human being gets these prediction models right every single time. It’s virtually impossible to do so. AI is a phenomenal tool, but it’s not a perfect prediction system. Since its outputs are heavily dependent on its inputs, the quality of the prediction depends on the quality of the information provided. If the AI model is fed the right information, then the chances of a successful prediction are much enhanced.
Can we Rely on AI Systems for Sports Betting?
The betting market is an information-based system. Those with access to the right information may be more likely to generate favorable outcomes than those with poor information. The operable word is likely. Powerful AI systems tracking all the variables in a horse race can help sports bettors perform above expectations.
Granted, AI can fail at any given point because in sport, as in life, Lady Luck always has the final say. There is often no logical, rational, or sensible reason why a longshot competitor pips the winner at the post. It’s one of those inconceivable incongruences that simply doesn’t match up with expectations. And it happens with regularity in the world of sports betting.
If we were to rely on past performance as a precursor for future performance, we’d be in peril. A football team that did well in one Premier League season might not perform so well the following season. Much the same can be said of Formula One, boxing, MMA, tennis, cricket, rugby, FIFA World Cup, and virtually every other sport in the world. Therefore, we know that past performance is not always a reliable indicator of future performance.
