How to make football predictions

The logic is simple: The more data you have, the more complete and reliable your predictions will be. With the help of machine learning and knowledge, you can create an algorithm that uses a ton of data to calculate the probability of each outcome. This is how bookmakers set their payouts for each correct guess. But you can also do it yourself and consider the relevant aspects to make an educated guess.

First, you need to be aware of all the factors that could potentially affect the outcome of a match. The most obvious of these include every team on the table and the results of their most recent games. But it’s much more than that, and the importance of each element will vary depending on the type of bet you’re placing.

Predicting the outcome of the game is the most famous type of betting. Who will win? Will it end in a draw? But there are many other categories you can bet on, such as the number of yellow and red cards given, the number of goals scored in each half, how many corners each team will have and which player will score.

The first thing to do is decide what you are betting on. Depending on the answer, you will need a specific set of data. An extreme example: During the 2014 FIFA World Cup, several people bet that Uruguayan striker Luis Suarez would bite someone during a match…and he did. The key data here is that the player has bitten an opponent twice in the past when they were under stress in a highly competitive and important game.

Betters recognized the familiar situation when the duel against the Italian team began to heat up and went for it – a great illustration of identifying an opportunity and knowing what to do with betting options, according to the available data.

Gather data based on the bet you are about to place. For example, to collect information about the distribution of red cards during Premier League matches. You can identify a particular fixture with a higher frequency than the average.

Sometimes it’s because they’re rivals, so their encounters are hotter than usual… and sometimes for no apparent reason at all. But if you are sure that you have found a fairly distinct pattern, then go for it!

Organizing data into categories is also important. The more you do, the better results you can expect. For example, a team may perform well in knockout tournaments but lose in the league.

If you look at the winning percentage of a club as a whole, you might not notice this difference, but if you break down their results by competition, you can see patterns and make an informed prediction.

Now that we’ve looked at how to use the data you have to make sound football predictions, here are some things you can base your data on:

• Time when a team scores and concedes the most goals
• Average number of shots, free kicks, corners, possession, saves and offsides

As mentioned earlier, categorize these numbers into different categories, such as how the average changes when a team plays away, at home, or in a given competition.

When you have finished systematizing the factors that you think are relevant to the type of bet you want to place, try using a decision tree generator, for example, to develop a way to use each piece of data according to the category you are betting on. .

Some matches are difficult to predict correctly. For example, UEFA Champions League finals are often unpredictable. To play it safe, stick to the obvious patterns you’ve identified in your data.

If Real Madrid are in the lead in La Liga and have a 10-win streak and are set to play against Getafe, who are in last place and haven’t won all this period, it’s safe to assume what will happen.

If you’re betting on a team, check out their week in training. A classic example to watch out for is a team’s star player who is injured and ruled out of an upcoming match. If your data shows that a team’s wins are correlated with that player’s performance, then the chances of success without him just drop. Keep these variables in mind when making football predictions.