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MORE INFORMATION ABOUT OUR FOOTBALL PREDICTING TECHNOLOGY

Being a team of software developers who were engaged in betting & livebetting software and who generally works for the welfare of a betting places, we were always interested in doing something for the people who visit the very same places as well.
This is a try of bring our side of a game closer to players, the side of numbers and probabilities.
Betting houses are going for sure. After giving a small advantage to one player they follow the payments for concrete events and then change their odds to make their profit sure.
It is really a lot of data processing and the system is unbeatable.
You CAN win, but at the same time somebody else loses his money.
We have come across a lot of mathematical methods for prediction of results while doing our job.
The main problem of these methods is that an average player has no data those methods work with, and of course custom user doesn't have sufficient level of technical (computer) or mathematical knowledge to make him able to use very same methods.
The principal of their writing is the same: at first you have a lot of mathematical formulas followed by some 10 decimal numbers and that's it. So, how to make use of it?
One may say that the vocabulary of this article is not mathematically correct, and this can be the subject of criticism or suggestions, but this is written for the people who have never met with the hard mathematical concepts as a try to make the way of the whole application circle easier and more understandable.
I. A LOT OF DATA IS NOT ALWAYS USEFUL
If you take in to consideration what ever team, let’s call it “A team” you should know that it has lost previous match away, and two rounds ago it played to a draw at home. And logically, these information simply asks to see how did “A team” play three rounds ago, and then four rounds ago. But last round in the some European or international competition it played bad, and now it has to improve the impression in front of its own crowd... it's good to know the results from that competition too. Let's bring the Cup matches now while we are talking about this, they were played with a lot of reserve players, as this tells us a lot about the team atmosphere and the bench strength.
And now, we have too many results, too many data. How should we deal with them?
In our application there is a review of all the results for selected season. You can choose any one of the teams from that season, view it’s results or check full time or half time table.
The table consists of three parts: results at home, away and total. There is the same table for the half-time and you can chose it on the menu on the left side, and there you can also change the team you are analyzing. All of the analysis the software does, exist both for the final and the half-time results, because a lot of players want to be engaged with the turnovers.
After choosing the team, you can see the graphic analysis of its matches. These analysis deal with the number of goals and points. The attention should be paid to a physical condition of defense during season, but for each analysis there is a question: how to take advantage of the fact that some team's record at home, concerning goals, is let say 3-4-1-0-0-3-2-2-1, and away 0-3-1-0-1-1-3-0?
For this we should use geometrical progression. The more competition you chose, the more precise it should get.
By using such analysis, together with the methods of probability, which are going to be described later, maybe we can’t predict the final result without 100% certainty, but we will get a good view of the current form of a team.
There is a reverse logic saying that the team which, one after the other weekend, loses its matches, must win the next match. How truthful is that? And is there any influence of your opinion that they should win, to a team's real form? None. So, let the team get slowly into good form, don't bring them into it yourself, because your knowledge is much lower then a team coach's is.
What we like the most, is playing the number of goals in a match, and especially in a halftimes. There are the same analysis, for both half-times.
It is always better to know what not to play, isn't it? Even if you didn't take these views for serious, never mind. In front of your friends you'll look like a great expert though. Is there any of them who knows that for example, Chelsea at home had never played from 2 to 1 in the season 2005/2006? This made us test the analysis on the season 2006/2007. And again it showed there were not games that Chelsea was losing at half-time and won at the end. In the season 2007/2008 only once, against Aston Villa , it was losing in the half-time and game ended at 4:4. It means that never during three seasons there was turn-over from 2 to 1. There are also many interesting facts you can learn using our product.
While doing these analysis try to improve the sensibility for different competitions in which team takes part. Sometimes it is convenient to include the friendly games as well, and sometimes it is not. Look at the rival's condition. As you are about to see in the following mathematical models, the capability of a team to score goal is confronted with the rival's defense form.
So far you have learned to analyze the pile of data concerning the team matches. If you have not, don't panic. Our Genius Software is going to do that instead of you.
II. ELEMENTARY PROBABILITY MODELS
Probability is a way of expressing knowledge or belief that an event will occur or has occurred. Theories of probability.
We have never really liked this part of math’s, so we are not feeling comfortable of
writing about it either. We are going to deal with the basic principles of software operation in this part, by using the simple language to describe the elementary methods software use.
We don't claim there was not a try of mathematical presentation of a football result so far, but they were mostly on academically level. There was not a software which would have produced two simple numbers out of pile of data, one for home team goals, the other for away goals – final result of the match.
It's time to mention that while predicting results different models takes in consideration different facts: how many games team played without receiving goal, standings at the moment or ranging of mutual games separately, among history of results, as a try to make the picture of two teams' current form more precise. We're going to argue about these aspects as well as about their significance. The basis for the method that is going to be used is Poisson process. The following part you are free to skip, but we simply have to write it down.
If the expected number of occurrences in the interval is λ, then the probability that there are exactly k occurrences (k being a non-negative integer, k=0,1,2,...) is equal to:

If the same is done for the away team, and then for all combinations of results, we'll get the values for the columns P(H) and P(A).
The most possible result is the biggest multiplication result of individual probabilities, which gives the most possible result.
This is the most simple presentation of what we 'd like to show here.

So, let's move on.
Parameter λ which you have already met with earlier, from now on we'll call "scoring rate". Since the results of the team differ at home and away we'll introduce the terms "home scoring rate" and "away scoring rate".
Now the table 1. will get a little more complicated, depending on whether the match is played at home or away for the team we want to predict the result.
And still this can be calculated by the simple operations in MSExcel.
This model has grown complicated even if we still haven't put exactly the same important parameter as the scoring rate, and that is the capability of one team defiance and not to receive a goal.
It is true that it's the most probable that home team will gain two goals, but also the probability is the same for the guest team not to receive more then one.
Of course this parameter should also be included . Even better, two parameters should be included, home defensive modifier and away defensive modifier.
The way this formula works out the most probable result will not be described here because this is not some mathematical study. What is important is that you know two things.
1. parameters depend on each other, because it is not possible to calculate the home scoring rate without away defensive modifier known and vice versa.
2. parameters are calculated by repeating calculating process while the values of parameters are not converged to some value, i.e. that values in i+1 iteration don't differ less than, for example, 0,000001 in i iteration.
If we don't use, like many authors argue, parameters that are very important: the advantage of home ground and the length of the bench, we will get a satisfying model which will lead us firmly through many games that bookmakers offer.
This model was tested through all games during season in many world leagues and the results are very satisfying. It means that disposition of 12 to 14 teams (out of 18) matches exactly, while a problem exists only for the teams in the middle of the table.
Since this method is based on setting of results, it means there is a great certainty one team will win, it might be a wrong result, but a winner is certain.
We think there is an problem of tied games which is mentioned in some articles and we will try to overcome this problem in next versions of the application.
The application in its work don't use this model. It uses a little bit complex model. The problem with previous calculations is in the fact that games at the beginning of the season has the same difficulty factor as the ones at the end. It means one should not considerate a momentary form of the team. Instead of calculating the team's parameters at once for whole season, the application goes on calculating the results again and again, each time after a match have played.
Since this method is more complex from the previous, WeI won't even try to "spice" this article with formulas. They use Gamma functions and Poisson's distribution. This method is often met in literature and it's often the object of analysis.
Whether someone is interested in the essence of these methods, I suggest to read some of the articles mentioned in Reference part of this article.
III. HOME GROUND ADVANTAGE
We all agree that in football ( and also in many other sports) a home ground is of great importance. But how this advantage could be modeled and presented in numbers.
Should it be considered on a whole league level or only on a team level?
Which factors should be considered?
Well, we will enumerate several now, and we are sure you'll remember a group around ten yourselves. Ball possession, number of posts, number of cards, number of passes completed, number of winners of home team in a league... The database that software is using hasn't these data (it's a doubt whether other databases has these information). That's why we have let these modeling to you. Our advice to you is that it is the best, with the exception of testing, not to use this option for many reasons. You can be sure you won't guess the right value, and also the model you are using already has some information about home team advantage, through the history of the matches.
IV. THE BENCH STRENGTH
Maybe during weekend’s friendly conversations about games we never talk about bench strength, but we certainly do mention injuries of key players.
Let's look at the Barcelona FC.
The injury of Chavi has an important role in team's play in next round, but the fact that Iniesta spends his time on the bench is less important, or is to so? Software based upon the history of results simply has no information about the quality of the bench.
Do you have them? Do you think it is important?
Our suggestion for you is not to use this option. First, you don't even know for sure whether there would be any substitution or not, and beside this there is a fact that some of the players have, in some previous games, took part in the game, so the software will "see" them through the history of the results. If they haven't took their part until now, it is even better. It is probable they won't now.
V. HEAD TO HEAD
We provide you with head-to-head section.
Keep in mind that you need to check this option before you place a bet.
You can find interesting and very usefull things here.
VI. PREDICTION WIZARD
OK. It's simple from now on. From the first tab of the Wizard chose country and home team, and away team.
We're trying to simulate the next:
Round of the season 2009/2010. Under this part of application there are 3 options, which offer the following possible choice:
1. All the competitions in which the teams took part in. We like this the most. It offers me the most games, and one can choose what he thinks is going to be useful later.
2. The competitions in which both team took part in, whether or not they had met each other. For example, if you are testing AC Milan and Manchester UTD, you’ll see that both teams took their part in the Champion league, but have not met each other yet.
3. The competitions in which both teams took part in and met each other. This should, if the teams are from the same country, be the local leagues.
Let we repeat, for the above remarks numbered as 2. and 3. the number of games in the analysis is somewhat limited, and this isn't good sometimes. Since we're talking about scoring rate and defensive modifier, we cannot completely perceive condition for example, if we study only duels through long period of one season. But this choice is also up to you. Have in mind that this model (not like others) is not 100% fixed, and also it depends a lot on you and your skills.
Other models just give you theirs predictions, trying to hide input parameters and limit your knowledge in calculation.
There is also possibility to chose mathematical method wizard will use in it’s prediction.
There are three methods at the moment, and we are always working on new once and current methods improvement. First method is based on all the games in selected seasons for calculating probabilities.
Second includes current scoring rate of teams and defense modifiers, and probability is calculating after each game, so it implements current form of a team more precise. Third model is similar to second, but it makes difference between home and away matches.
So don’t be surprise if you get completely different results. It’s up to you to choose appropriate option for what you have in mind, or better yet, use all models and find games that will have same results for all the models...those are the one you should go for sure.There will be many situations where all three methods will suggest different results.
In this case move to the next game or go for 1X2, not for scored goals, turnovers or some other option.
Our final tip is not to bet just looking at the wizard results. Use graphical presentations in “Analyze team” section of the application, look at both teams form and if you don’t find some logical result, like in previous example, just go to other game and by doing so minimize your risk.
VII. CONCLUSION
During time we have tested many models which deal with predicting football results.
Our original idea was to gather in one place a lot of leagues and seasons results and offer them to users, and the predicting of the results was never simple.



References
* Predicting Football Results, Andrew James Moore May 6, 2004
* Multivariate Poisson models, Dimitris Karlis,October 2002
* Bayesian and Non-Bayesian Analysis of Soccer Data using Bivariate Poisson Regression Models, Dimitris Karlis and John Ntzoufras April 2003