Artificial intelligence refers to a computer's ability to perform tasks that would normally require human intelligence. Historically humans have always been interested in predicting sporting outcomes and modern history is no different. Human bias has always been one of the biggest downfalls when we try to bet on sports, which is one area in AI that has a significant advantage over us. The 2000s saw a massive rise in how accessible data has become to everyday consumers. Within a couple of clicks, you can find career averages for every NBA player since the beginning of the league. The more accessible and plentiful the data is for a certain sport, the stronger your machine learning will be.
When it comes to any artificial intelligence use case, you must look at 3 things: the data available, the models selected, and how accurate the real-life conditions are to the training conditions.
Data is Everywhere
As mentioned earlier, in 2021 there is so much free public data available that anyone with basic programming skills and can connect to APIs can perform their own analysis. The artistry in crafting these models comes from new and creative ways to manipulate the data to create insights. Here at Infinity Sports AI, we consider this to be our bread and butter.
When it comes to model selection, libraries like scikit-learn, TensorFlow, and other easy-to-use machine learning packages have made it very easy to run a well-designed dataset through dozens of models with little regard for what’s going on behind the scenes. The pros are that you have a very rapid iteration process, and can quickly select the best model, while the cons are that without a fundamental understanding of how the model functions, it will be difficult to optimize it further beyond your initial results. Once again, our philosophy has always been a high level of transparency, so we have selected models which we fundamentally understand and have fully optimized to solve our sports betting problems.
Accuracy of Real-Life Data
The final challenge in sports betting predicting using AI is making sure the data you are using to predict matches as closely as possible to the accuracy of the data you used in training. An example of this is making sure the stats you are using for a matchup are the most up-to-date. It is easy to build an ultra-complex training dataset, but now you need to maintain that complexity in your real-life dataset as well. This usually involves finding new sources for this more up-to-date data.
Overall, recent years have shown tremendous improvements in the real of machine learning, and data has become more plentiful in sports. These 2 factors combined represent the main reason artificial intelligence is now changing the entire industry of sports betting. Sportsbooks in Vegas are even hiring artificial intelligence experts now in an effort to keep up with the new era.
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