There are many approaches to take for football predictions. It can be as simple as seeing which team has won more matches in their respective recent form or making a decision based on the most current head-to-head results.
The great thing about football betting predictions is that they can be as finely tuned and nuanced as suits the punter. Some may well scour through banks of analytical data and then spend further time shopping around for the best value odds on that selection.
Others prefer ready-made predictions to speed things up. A prime example of this is UKClubSport. This platform offers predictions based on Team Strength Rate, a functional algorithm involving the mathematical analysis of a vast number of matches to accurately determine the balance in a given match.
Whatever option you choose, the article will help you get a better understanding of what mathematical football predictions can do for you.
What are Mathematical Football Predictions?
All the statistics that you look at for football betting tips are in one shape or another, a form of mathematics. If you look at the last five head-to-head meetings between two teams, and one team in particular has won three of those, then they have a 60% win rate. Mathematics is reliable, as it offers an unbiased solid cornerstone for betting approaches.
SOT
One calculated mathematical football approach is 'Shots on Target'. This has a big correlation to teams winning games and plays perfectly to 'Team Strength'. The better a team is at getting shots in on target, the more chances that they are going to have to win fixtures.
Using the powers of computing, sorting through the stats of 'Shots on Target' and 'Shots on Target Conceded' by every team will produce numbers that you can stack up. For example, if a team that has 3.9 shots on target per game on average is playing a team that only has 2.4 shots on target per average, that initially points to who to back.
But the factor of 'Shots on Target Conceded' has to be balanced as well. Perhaps the second team in the above scenario has conceded only an average of 2 shots per game on target, while the first team consistently ships an average of 3 per game. Combining both metrics gives a truer output.
xG
The expected goals statistics have been a game changer for many punters. This is a huge maths football prediction tool that balances the quality of scoring opportunities created and conceded.
xG is expected goals, which can be studied per team or even by player. This takes into consideration many factors and needs some supercomputing power. However, it manages to pick through different variables of expected strengths and weaknesses of teams.
A simplification of xG is how many goals a team is expected to score based on historical data. If you look at a team that has scored an average of 2 goals in their last three games, it may not paint an accurate picture. The team could have scored all six goals in just one match.
So this is why the mathematical power of xG which works off variables such as quality of opposition, home advantage and more, is seen as a big advancement.
Probability
At the end of the day, you are looking for probability. Is it worth coming up with your own xG or 'Team Strength' metrics? Not really because there is just too much specific data like the angle of shots, distance of shots and technique of shots to figure out.
But there isn't a need to understand the mechanics of the numbers, just to understand what they are telling you. For example, the 'Team Strength' rating at UKClubSports gives ratings between 0-4, the higher end of the scale representing the stronger team.
They arrive at those numbers thanks to an algorithm that compiles banks of data. But you simply compare the two numbers and see which is the stronger of the two teams and by how much.
The Outside Factors
This is football prediction territory. Some things can't be translated into numbers and that leaves a window of variability even with so much maths plugged in. For example, what influence on a team's performance will their world-class holding midfielder have?
How will a player making a debut for a new club influence the outcome? Has a team's form dipped due to a long-term injury? What influence is the weather going to have on a performance, or is a manager suddenly changing tactics?
This is where football betting predictions still rely on the human touch. Most importantly of all, that's what keeps it so engaging. Using mathematical prediction tools can certainly help and they are worth looking at for insights. But it needs to be sprinkled with intuition and non-mathematical elements.
