One of the most loved sports for millions of fans is football due to the fact that this sport is quite unpredictable. Despite the dominance of one team during the game, which creates chances, controls the ball and dominates in the match, it may happen that it will lose at the end of the match.
Although football is very surprising and unpredictable, the process of making predictions is always developing due to innovations.
For a long time, people were making predictions based on personal experience, reputation and results of the teams. With the development of artificial intelligence (AI) and data, the process of making predictions has significantly changed because now people can consider numerous factors before making predictions.
However, it would be a mistake to believe that it is possible to make perfect predictions in football thanks to AI because football is too unpredictable for that. Using innovative technology, people will be able to find patterns and make objective predictions through football prediction analysis.
Traditional Football Predictions
Initially, people were using traditional methods and statistics for making football predictions.
The following factors were considered:
- Recent results of the teams;
- History of the matches;
- Results in the home and away games;
- Quality of players;
- Injuries of the players;
- Importance of the game etc.
If there is a strong team playing the home game against a weak team which is taking a lower position in the table, it will be rather easy to predict the winner.
The problem is that football is too unpredictable. For example, there may be a penalty, unexpected injury of the star player, a red card, mistakes in the defense etc. which may change the result of the game. Therefore, data-driven prediction cannot make the game predictable but it can allow predicting the probability of certain events.
Why Do We Need Data in Modern Football?
Modern football is generating tons of data.
Each action of the teams and each moment of the game can be converted into data and analyzed.
Therefore, instead of speculating about the condition of the team, people have an opportunity to analyze all the data.
For example, if two teams have won their last five games in a row, it seems that these teams are equal in terms of strength.
However, with the help of analyzing the additional data, people may discover that the first team regularly creates opportunities to score while the second team wins but gives its opponents good chances.
Such information can be used in the future because these teams will meet again.
What Is Artificial Intelligence Doing Differently?
With the development of AI, the process of data analysis is brought to a completely new level.
While human analysts can analyze dozens of parameters in their research, AI systems are capable of processing huge amounts of data and finding the relations between the parameters which are invisible to humans.
Depending on the specific program, AI can consider:
- Historical results of the matches;
- Performance of the teams and players;
- Home advantage;
- Goal-scoring tendencies;
- Players’ injuries;
- Tactics etc.
After that, the algorithm is capable of calculating the probability of different outcomes of the match.
Instead of saying that “team A will win in this match”, the analyst will be able to make the following prediction:
Team A win: 58%
Draw: 25%
Team B win: 17%
Of course, it does not mean that such figures guarantee the outcome of the match but people will get the probability of a certain outcome based on the considered information.
And this is the key difference.
Expected Goals and Smarter Analyses
One of the innovative tools in football analytics is the concept of expected goals (xG).
This is a statistical indicator which is designed to measure the quality of opportunities to score.
Imagine that one team has won the match with the score of 2-0. However, this team created almost no opportunities for scoring but the losing team has missed several great chances.
By looking at the score, the analyst may think that this team dominated in the game.
However, with the help of xG analysis, people will discover that this team was not lucky.
This feature is significant because football results may hide many details. With the help of data, people will be able to understand the true situation.
AI systems may use xG for the predictions.
AI Helps Analysts Identify Patterns Which Cannot Be Found by Humans
One of the major advantages of AI is the ability to process vast sets of data quickly.
For example, if an analyst needs to analyze the performance of a certain team in the cases of:
- Home games;
- Matches against the teams with high pressing;
- Absence of the key striker;
- After the midweek game;
- Against the teams with good defensive records;
This process will take much time. However, with the help of the algorithm, people will be able to find the necessary information quickly and find certain patterns.
This will give people an opportunity to find out the relation and facts which remain hidden otherwise.
Personalized Football Analysis Is Coming
Another innovation in this area is the development of personalized football analysis.
Before, prediction websites were offering the single prediction to all users.
However, with the help of the new technology, the website will be able to offer various types of information to people.
Some of them will be interested in the results of the match, others will want to know the information about the goals and somebody wants to learn about both teams scoring, corners and correct scores.
AI systems will be able to organize the data in the proper way according to different markets and offer more information about the factors which influence them.
AI Does Not See The Future
There is a popular opinion but people should remember one important fact:
The system does not see the future.
The prediction model is not a crystal ball.
Even the most advanced systems may make incorrect predictions. Of course, the algorithm will identify correctly that one team has higher chances to win. However, it is the probability and not certainty: in case the team has 70% of winning chances, it has 30% chances to lose.
Therefore, the analysis should be based on the probabilities and not promises.
Promises like “100% sure prediction” or “guaranteed winner” should be taken with a grain of salt.
Human Analysts Remain Relevant Too
It would be a mistake to think that the future will bring the complete replacement of football analysts by AI-based systems.
The reason is that human knowledge is still relevant and there are always some aspects of football which cannot be captured by any data set.
Therefore, the experienced analyst will take into account such aspects as tactics changes, atmosphere in the dressing room, managerial decisions etc. which will not be considered by the algorithm.
That is why the best strategy will be combining technology and human knowledge.
The system is capable of processing numbers while the analyst will provide the context.
In this way, people will be able to make better predictions.
Changes in the Process of Prediction Made by Football Websites
As technology changes, football prediction websites change as well.
Nowadays, the websites are capable of using statistical analysis, historical trends and performance data in their predictions.
Therefore, instead of making the prediction “Home win”, the website is capable of considering:
- Recent performance in home games;
- Record of the opponent as an away team;
- Goals scored and conceded;
- Chances creation;
- Defensive performance;
- Availability of the players;
- Trends;
- Form
etc.
In this way, the process of prediction becomes easier to understand.
The Future of Football Predictions
The future is probably going to bring more innovations.
With the development of football technology, the data for predictions will become more detailed.
The information may include such factors as positions of the players on the field, movement patterns, team formations, in-match events etc.
The prediction will also become more sophisticated because instead of the analysis before the kick-off, the algorithm will be able to process everything which happens during the match and change the probabilities accordingly.
For example, the early red card will dramatically increase the probability of the loss of one of the teams. The system will be able to recognize this event and change its prediction.
Thus, football prediction will become more dynamic.
Data Can Help But Cannot Replace Common Sense
The key lesson from the development of AI in football predictions is that the technology should be used as a tool and not as an absolute authority.
Statistics can help people to find out the patterns but it cannot consider all possible events perfectly.
Football remains a human game which contains unpredictable events and, therefore, good prediction analysis should be based on data, context and realistic expectations.
Therefore, the goal should not be finding a magic system which will never make a mistake because such a system does not exist.
FAQ
- Can AI predict football matches accurately?
AI is capable of helping with the analysis of football because it allows identifying the patterns and calculating probabilities on the basis of the vast amount of data but it cannot guarantee the outcome of the match because it is too unpredictable.
- What data is used for football predictions?
Predictive models may use such data as recent results, goals scored and conceded, expected goals, home and away performance, players’ statistics, injuries, strength of the teams etc.
- Is the AI football prediction guaranteed to win?
No. AI predictions are probabilities and not guarantees because even the prediction with the high probability may fail because there are unpredictable events which may change the match.
- What are the expected goals (xG)?
This is a statistical metric which is used for estimating the quality of chances for scoring. It helps people to understand the attacking performance better than looking at the result of the game.
- Will AI replace football prediction experts?
Probably not completely. AI is great for processing vast amounts of data while human analysts may use their football knowledge. In this way, they will be able to provide stronger predictions.
- Why are data-based predictions so popular?
They allow people to conduct more systematic analysis of the game. As opposed to the pure opinions and reputation of teams, people are able to analyze statistics and probabilities before making their forecast.
- Can AI predict exact scores?
AI is capable of estimating the probabilities of different scorelines but exact-score predictions are especially hard because there are lots of small events which may influence the result.
Conclusion
The new era is coming in the field of football predictions.
With the help of data and artificial intelligence, football analysis is changing. Instead of relying on personal experience and opinions, analysts are now capable of processing vast amounts of data and using advanced models to understand the patterns and probabilities better.
However, of course, the technology cannot yet remove unpredictability from football. The AI system is capable of analyzing the game in detail but it cannot guarantee the result.
Therefore, the future of football predictions is probably going to belong neither to humans nor to machines.
Both humans and machines working together will be a better option.
AI is capable of processing the numbers, identifying the patterns and calculating the probabilities while the analyst is capable of providing football knowledge, context and common sense.
Combining these two approaches in the responsible way, people will be able to make transparent, educational and data-driven football predictions without forgetting about the nature of the sport. For readers interested in following this type of analysis, VerifiedPredict.com can also be used as a football prediction resource.
