Mathematical Football Predictions from xGscore
xGscore is a modern platform for football match analysis. We offer accurate mathematical football predictions based on dozens of statistical criteria, including xG metrics.
Football is all about numbers: scores, time, statistics, speed, transfer cost, coefficient, profit. Thus, it becomes crucial to be familiar with numbers for anyone wanting to understand football, and especially for those looking to make money on it. Our mission here at xGscore is to present these numbers in a way that is easy for you to use in betting.
Our team publishes outcome predictions for top Еuropean leagues as well as the Champions League and the Europa League daily. For each game we provide our users with the next values:
- Statistical comparison of the teams
- Team’s ranking
- Current form evaluation
- Advanced xG statistics
- Results and ratings of the latest matches
- Defence and attack condition
- Score prediction
- Own probabilities and odds for outcomes
- Bookmaker’s odds
- Profitable predictions from professionals
- Bets on trends
There is a notion that winning a bet is sheer luck but that is far from the truth. Bookmakers make millions not because they are more lucky than the player, but because of precise calculations and maths. They make a profit not at the moment the better loses, but at the moment the bet is made, due to a subtle odds manipulation. Bookmaker’s odds line is initially lowered 3-5%. In the betting world this value is called a margin, the higher the margin, the lower the player’s payout after making the bet.
Therefore, to outplay a bookmaker one has to build their predictions based on maths as well and only count on luck in rare cases.
The first thing you need to do is to find the highest coefficient to minimise the influence of the margin on your bank. Our margin calculator can help with this task. As a rule, professionals do not bet on an outcome if the margin is greater than 3%.
The second and most important task is to find football events that have a higher probability of happening than that of bookmaker’s. A player’s prediction of at least 5-7% better than that of the bookmaker is a great indicator, especially when you have a high number of long distance bets because the winning percentage in this case will grow exponentially.
It used to be considered near impossible to outplay the bookie. With the rise of computer technologies and an unlimited access to statistical data that is no longer the case. Now you don’t need to spend hours searching for and analysing information to find a profitable bet. All you need to do is write software with a universal algorithm that calculates predictions for you, and use it for large scale betting.
This is precisely what our developers and experts do. We are football fans with software engineering degrees who make money off our favourite game while doing what we love. We want to share our experience and our results with others. Below we will talk about how maths and programming is used to put together match predictions.
Football Score Predictions
Our primary task while creating predictions is to calculate the expected game score, hence the name of our site is xGscore (Expected goals score).
The computing system works on neural network algorithms. With each new prediction the system learns and as a result it applies an increasingly greater number of benchmark data, analyzes the results or previous bets and improves calculation parameters.
To predict a football match score you need to calculate the number of goals each team will score and concede. The easiest way to do this is to calculate the mean of all goals scored and conceded in a season. This approach will have a very high margin of error since each player is unique and each game involves multiple factors that you can’t dismiss. It becomes apparent that in analysing a game between two top teams one has to prioritise the matches of similar competitors at the top of the leaderboard.
xGscore prediction model assesses the significance of each individual match played in calculating expected goals. Here are the main factors considered by our algorithm:
- Actual goals and expected goals (xG)
- Date and time
- Venue (home or away)
- Rival’s strength
- Tournament level
Next, the model adds up data of all matches and produces scored and conceded goals for both home and away teams. By combining the scores of both teams we get the expected game score.
Value Bet in Football Betting
Half of the work is done. Now, the game score prediction needs to be converted into the most profitable bet. These bets are called value bets. The probability of value bets to happen is always higher than that of what a bookmaker includes in his coefficient.
This means that we need to evaluate the probability of each match outcome: wins, draw, totals, handicaps etc. To do this we turn to another mathematical function, the Poisson distribution. The Poisson distribution probability calculator is available for our users on a separate page, where you can learn more about it and try it out.
After calculating probabilities of match events the system analyzes and compares data with bookmaker’s odds and as a result we get value bets. Each bet offered by our system is additionally evaluated by an expert from our team and only after that we publish the final match betting tips.
The Main Goal of Our Service
The main intent behind xGscore development was to create an all encompassing resource that would contain all of the information needed for an accurate match prediction and for determining the most profitable bets.
In the near future, we are planning to increase the number of leagues we make predictions for, expand the necessary functionality for match analysis to include player injuries and suspensions, ROI stats etc. We need your help to speed up the development process. Please share a link for this resource with those who might be interested in it and subscribe to our Patreon.
