Takeshi Watanabe was a university student that brought the promise of developing artificial intelligence towards the horse racing prediction systems in place. This development came to life from the love and enthusiasm that he had for watching horses and predicting the outcome, rather than the fruits that follow from winning in horse race gambling.

While many often search for the best racing betting offers to aid their progress within the field of sports betting, perhaps this technology is now the future for horse race betting and the scope of imprint that it currently has over the world.

The link that Watanabe made, was how AI is all about analysing data, as well as prediction. Therefore, even though he was not superior in the arts of horse race betting, he wanted to use his major from university, within the real world and approach it within the eyes and settings of real matters. Just from studying and reading up on the publications of AI and IoT, Watanabe tried to get his information correct by seeking as many sources as he could. Expanding his knowledge of data analysis and prediction; how to apply it within mathematical and theoretical situations such as horse race betting.

Watanabe realised that predictions are made through the feeding of data that the past 10 years hold over horse race betting. All these conditions are fed into AI. AI can increase the process of prediction, as well as pinpoint tendencies around the data. 

Watanabe decided that to better understand and visualise the system as much as he could, he needed to look deeper into existing races and their data. He opted for the Muromachi Stakes, which had the track of 1200 metres. The system he developed named as AI Ringo, predicted two out of three circumstances as a final outcome.  Through the power of ratio, it was able to predict the horse that will win, alongside the return punters get from their bets placed. 

Watanabe believed that by betting on the top favourites you will win 80-90% of the races, however the return will be low. If, however you bet on local races, the chance of a higher return is more likely, due to the AI Ringo being able to predict much more easily of the outcome. The local races are the ones that can bring in a larger and better return, due to more knowledge of the data that surrounds the race environment and variables. 

However, selecting the most significant data is crucial for the AI predictions to be as close as possible. If a race doesn't finish for example, that itself can affect the system of the AI. So, while this data prediction system of AI is still in conditioning, Watanabe believes that the use of data prediction systems will soon be very popular and customer reliant, as data cleaning and selection is developed.

Who knows, maybe this could go as far as predicting huge races like the Grand National one day?