Sporting bets have always been popular. People have bet on horse races for centuries, for example, and as new sports grew in popularity over the last century, the betting markets have followed suit. The internet has made sports betting even easier, with countless websites letting betters from all over the world engage with various sports. As arguably the most popular sport on the planet, soccer predictions are among the most widespread.
One of the most exciting things about soccer is that it is full of surprises, which can make guessing the final result a real challenge. However, statistical data can give you a helping hand, by identifying patterns in past results.
Of course, the beauty of soccer is that anything can happen at the end of the day. Take Argentina’s stunning loss against Saudi Arabia in the 2022 FIFA World Cup, for example. The South Americans were on a long winning streak, and had never lost to the Falcons in their history.
They were also tipped as likely tournament winners, and indeed did go on to win it. So no data would suggest that a Saudi Arabian victory was probable. But it happened anyway. So no, there is no bulletproof technique for betting. But if you know what you’re doing and build a strong prediction model, you should expect to guess correctly most of the time.
The logic is simple: the more data you have, the more complete and trustworthy your predictions will be. With machine learning and knowledge, you can create an algorithm that uses tons of data to calculate the odds of each result. That’s actually how betting houses set their payments for each correct guess. But you can do it on your own too, and consider relevant aspects in order to make an informed guess.
First, you need to be aware of all the factors that could potentially influence the outcome of a match. The most obvious ones include each team standing in the table and the results of their most recent games. But there is much more to it than that, and the importance of each element will vary according to the type of bet you’re making.
Predicting the outcome of a game is the most well-known type of bet. Who will win? Will it end in a draw? But there are many other categories which you can bet on, such as: number of yellow and red cards issued, number of goals scored in each half, how many corners each team will have, and which player(s) will score.
The first thing to do is to decide what you are betting on. Depending on the answer, you will require a specific dataset. 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 had bitten an opponent twice in the past, when he was exposed to the stress of a highly competitive and important game.
The bettors recognized the familiar situation when the duel against the Italian squad started to get heated, and went for it – a great illustration of identifying an opportunity and knowing what to do with the betting options, according to the data available.
Gather data based on the bet you are going to make. Collect information about red card distribution during Premier League matches, for instance. You may identify a particular fixture with a higher incidence than average.
Sometimes it’s because they are rivals, so their encounters are more heated than usual… and sometimes there’s no apparent reason at all. But if you are confident that you’ve found a sufficiently distinct pattern, then go for it!
Organizing data by category is important too. The more you do, the better results you can expect. For example, a team may be doing well in knock-out tournaments, while struggling in the league.
If you consider the club’s win rate as a whole, you may not pick up on this distinction, but if you break down their results by competition, you can see the patterns and make an informed prediction.
Now that we have covered how to use available data to make informed soccer predictions, here are some aspects to base your data on:
- Time when a team scores and concedes most goals
- Average number of shots, freekicks, corners, possession, saves, and offsides
As said earlier, classify these figures in different categories, like how the average changes when the team is playing away, at home, or in one competition or other.
When you are done organizing the factors you judge relevant for the kind of bets you want to make, try using the decision tree generator, for example, to design a way to use each piece of data according to the category you are taking a bet.
Some matches are difficult to predict correctly. UEFA Champions League finals, for instance, are often unpredictable. To play it safe, stick with obvious patterns which you’ve identified in your data.
If Real Madrid are top of “La Liga” and on a 10-game winning streak, and are set to play against Getafe who sit in last place and haven’t won in that entire period, it’s pretty safe to guess what will happen.
If you are betting on a team, check how their week is going in training. A classic example to watch out for is the team’s star player getting himself injured and ruled out of the upcoming match. If your data shows that the team’s wins correlate with this player scoring, then the odds of success without him just dropped. Keep these variables in mind when making soccer predictions.