Such a scheme allows the implementation of analytical capacities into machines and an ability to store information. Thanks to the neural network it is possible to analyze incoming data. In fact, it is an Artificial Intelligence, a machinery version of the human brain, where millions of neurons transmit data in the form of electrical impulses.
It allows you to quickly complete difficult tasks which require symbolic calculations.
Artificial Intelligence is represented in several varieties:
- Neural network for classification – it marshals information that is based on settings.
- Neural network for prediction – we mean prediction of the outcome of different events, i.e. the next step.
- Neural network for detecting – it is the most common type of network. Google uses it to search by photos, cameras of mobile phones determine a position of faces, etc.
However, today we are going to consider the prediction function, and, in particular, sports forecasting.
Sports forecasting is interesting mostly for owners of the betting business and betters. Clusterization makes it possible to do information categorization, which means to divide information into groups (clusters), based on common or similar characteristics. Sports betting forecasting should take into account an important factor: the same result is impossible in any case. Even we talk about a top English team and a low-grade Russian football club.
Players of the first team can suddenly be bowled over because of a disease, and guys from the second group may suddenly discover in themselves some hidden talents and win. It is all about the frequency of events. Neural networks forecasting allows us to determine a degree of possibility of all outcomes of an event. In sum, indicators are equal to 1.
Neural networks forecasting is carried out in one of its three categories:
- Kohonen’s neural network;
- ART-2;
- radially-symmetrical.
Each of these neural networks can be a learning program on the basis of fetch. They can have a fixed structure, but sports forecasting needs the possibility of an independent organization. The learning process consists not only of customization of Wide Web weight but also of the structure formation. New clusters are created, and old (unused) clusters are deleted. Networks differ from each other in the update algorithm.
Sports betting forecasting consist of the following stages:
- Acquisition of information on sports events in the same sport and rank.
- Architecture selection – such architecture is going to complete the task.
- Selection or development of a program.
- Formation of teaching selection, which is set for the used software.
- Setting up a learning algorithm.
- The program is learning and carries out cluster analysis.
- Neural network does sports forecasting and calculates the probability of possible outcomes.
You will need a huge array of information to make everything work properly. It is the main factor that influences the success of the analysis. Due to the fact that methods for football predictions work with the help of statistics and probabilities, both the amount of data and the quality of the source are important. Thus, any information on the Japanese championship will not be suitable, if you want to predict the outcome of the event within the framework of the Champions League.
Therefore, if the forecaster is going to do not only a football predictions analysis football match results prediction with the help of neural networks, but also to find out what will happen in other sports, it will be necessary for him to take this into account during the process of choosing training data.
Football match results prediction and prediction of outcomes of other events should be based on the following information:
- the field factor (does the team play "at home" on neutral territory or “on a visit’);
- up-to-dateness (the strength of the team, a dynamic pattern in relation to the index. This number notation can be obtained from reputable updated ratings);
- results of previous games.
It is necessary to pay individual attention to factors that are difficult to determine: injuries, disqualifications of major players, change of coach, the current position in the league table. It is difficult to take them into account, but still it is possible. Only using the maximum number of factors, the sports forecasting program will become very close to reality. But due to the complexity of the presentation, the information should be taken into account in the teaching selection even before the program gives out the solution. The predictor will correct probabilities of the results relying on his own experience.
In order to create your own software, you need to have a skill level in the field of Artificial Intelligence and understand the subtleties of programming. With a professional approach, the sports forecasting program, created by your own forces, will do everything more accurately and qualitatively. In your software, you can identify every nuance in order to make predictions extremely exact.
The main thing is to properly structure the available information. In order for neural networks forecasting to be exact, it is necessary to ensure the correct usage of the database. But not all source data should be used in the clustering process. It is important that vars which correspond to the results of the game have a descriptive character, that is, they need to be involved in the subsequent cluster analysis. The inclusion of such information in the select is a fundamental point, which allows to carry out such an operation in the future.
It can take a long time to establish and train the neural network until the results are satisfactory. Setting up of an algorithm consists of correction of the size of the network and several additional factors.
If it is a learning program with fixed structure, then it will be about the number of clusters. Some groups are not used, others are overflowing. Non-operational cluster prevents learning ability because the algorithm, in this case, is slow. A non-operational cluster is dangerous as it clearly demonstrates the inability of a neural network to properly separate examples based on characteristics. Prediction accuracy of such a network will be questionable.
It is also necessary to strike a balance when you install the adaptation coefficient. If you set up a high learning speed, examples can migrate between the closest clusters. But if the program is well and properly organized, users will not need to participate in the learning process.
Neural network clustering provides training during the practical use. Constant expansion of the database increases the accuracy of subsequent calculations. A modern betting business takes the opportunity of Artificial Intelligence to form coefficients.
Big betting means big money. All profit of the betting office will depend on how competently calculated coefficients are. The advanced neural network is better than any specialist in a calculation of the probability of outcomes of events, and it does it instantly.
In the future, neural networks will learn how to independently analyze the behavior of players on the field, characterize them, explore the possession of the ball, make up the most effective models of attack, etc. Artificial Intelligence will break new grounds and create the most exact methods for football predictions analysis.
The betting business should do everything to win in any situation, regardless of the outcome. This is why it is necessary to correctly calculate coefficients for the outcome of the sports event. A well-trained Artificial Intelligence, taking into account a myriad of factors, will make a forecast, even if not better than a competent analyst, but certainly several-fold faster. And in the future, with the development of the described technology and the expansion of its capabilities, the role of neural networks in a betting industry will only enhance.
