A neural network is a type of machine learning. In this case, the program operates on the principle of the human brain. It consists of artificial neurons, which are called computational elements. Modern neural networks are mathematical models. It was thanks to them that it was possible to create AI, all elements of this network are interconnected.
When placing bets, bettors can turn to neuron for help. The network performs a number of useful functions - for example, processing a large amount of information, searching for patterns, and providing the user with a prediction. Such programs operate in different fields of activity. Now these networks are widely used in creativity, content composition, human speech recognition and processing.
The user must ask the neuron a question, after which data about a football, hockey, basketball or other confrontation for the required time period will begin to be downloaded. Then the program will begin to perform analytical work - for example, researching the results of past fights, determining the efficiency of each athlete and team, and applying probability theory. It’s worth noting right away that the probability of such forecasts passing is far from one hundred percent.
Bettors can use the results of neural network forecasts to diversify and test their analytical abilities. The calculation results provide only approximate information, which does not provide a guarantee of success. At the same time, there are a number of reasons why it is worth working with neural networks - for example, obtaining an additional argument for making a bet, choosing a team for a bet, and much more. In practice, you can see that the accuracy of AI forecasts can be higher than that of some experts on TV screens and popular tipsters on the Internet.
To make accurate forecasts, you need to analyze a lot of information. AI can do this better and more efficiently than a human. There are already a number of successful examples in football where forecasts for popular events were made in this way. If previously the octopus Paul specialized in EURO 2008 and the 2010 World Cup, then neural networks began to be widely used at EURO 2016. To do this, at the University of Lausanne, graduate students created a technology that was based on AI.
The resulting system had a number of differences from machine forecasting. For example, she took into account the effectiveness of individual performers and worked with a large number of variables. As a result, increased productivity was achieved. The probability of the outcome of the confrontations was determined using Bayesian inference. Let's look at its features:
The result was a statistical forecasting method.
The system took into account uncertain factors. They could have an unexpected impact on the outcome of matches.
The network paid a lot of attention to the presence of new players in the national team.
How says michezo-yakubeti.com over the entire EURO 2016 championship, this neural network predicted match results with 80% accuracy. After this, bettors began to pay attention to AI. Now, using AI, users are trying to predict long-term markets in football - for example, the winner of the Premier League. Such forecasts may differ; if in February Opta AI gave Arsenal a 49.15% chance of winning the trophy, then in April it was 48.6%. Neural networks are also used to invite players - for example, the AI advised Malaga to invite striker Fran Sol.