Sports data is an incredible trade asset. It’s almost as valuable as any other valid currency currently circulating on the internet and throughout stores across the globe. However, it’s not as obvious as first just how valuable such data is. In fact, if more people knew what practices lie behind sports data trading and handling, we’d have many more billionaires rising up.
But let’s leave aside fluff arguments and focus on what exactly makes sports data so precious. Why is it being used by companies to generate revenue like very few others could imagine? And how did this industry rise up to encompass a major part of another highly successful branch – the sports betting industry? Stick around and we’ll try to unravel this conundrum.
Sports Data in the World of Betting
There are tons of platforms, such as https://www.feedconstruct.com/ and many others that take specific sports data, crunch it, and then interpret it and show it to the crowd in an easy-to-understand manner.
This data is invaluable to bettors, the house, and all the partners that get in between the process of placing a bet and winning. Go to any betting website and you will notice a sidebar widget or even an eye-popping front-and-center panel with all sorts of sports data related to upcoming events and past matches alike.
Do you understand now why this data is so valuable? It’s because bettors wouldn’t know what to do without it. And the house would have to rely on calculating approximates instead of displaying their accurate odds, thus gaining an unfair advantage over the bettor.
Machine Learning and Artificial Intelligence in the World of Sports Data
Examples of sports-related data include a player’s past injuries, their penalties, faults, goals, assists, height, age, experience, etc.
What happens to this data and why is it important? Well, each of these stats plays a role in determining the odds of winning in a certain match. Eliminate just one of these states, and the odds could be recalculated endlessly, thus leaving both bettors and the house with a sore eye.
Luckily, we now have the wonders of technology to help us out in ways that weren’t possible 20 years ago. Machine learning algorithms take this data and interpret it appropriately so that no one human has to go through the tedious process of crunching it on their own.
Artificial intelligence further takes these concepts and adapts to them future-wise. With that said, whatever data the AI crunches makes it easier for the algorithm to process certain odds and other factors in the future. It practically learns as it goes. It’s probably as close as a machine will ever get to use a human being’s logic.
How Sports Data Is Collected
There are numerous ways that this data gets collected, crunched, and interpreted in such a way that it can become profitable. First off, you’ve got cameras all over the playing field. These track player movement and inform the servers about ball possession, number of passes, and so forth.
Secondly, many players have opted to get their data collected by wearing smartwatches when training during their free time. This data comes in handy not necessarily for betting, but for the player’s overall health once it is analyzed by a physician.
Another way that this data is collected is, ironically, through matches that have happened in the past. Oftentimes, programmers feed the algorithm videos of old matches so that it knows what to interpret when it comes to a particular player’s data.
The Bottom Line
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