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The most simple solution would be to use matches from European championships only. But that also comes with serious caveats: And the histories of those games are a lot more difficult to access.
The FIFA ranking for example only exists since So what do we do? As long as it takes for egg-white and yolk to form one yellowish substance.
What we basically do is a simulated coin toss. Everything stays the way it was. Home- and away team will be switched. Well, we are still unable to predict draws but overall two thirds of the games are classified correctly.
Eight out of eleven home team wins and seven out of ten away team wins are identified correctly. This model does work accuarately enough.
And now things are getting interesting. Within the tournament things are constantly changing. Favourites are dissappointing the audience by playing uninspired and boring, the Germans as usual need a few games to discover their potential and some underdogs are doing surprisingly well.
This is the reason why we are going to update our predictions on a daily basis. Recent results can and need to be taken into account.
Despite all that we might just take a look into the crystal bowl. The advantage of playing at home which was taken into account for Poland and the Ukraine will get Poland straight to the quarter finals.
Second place is going to be a tough race between Russia and the CzechRepublic with the Russian having a slight advantage.
I cannot help stating it: This is the toughest group of the tournament. In turn this make it hard to predict. In fact the differences are so tiny that it might be of importance who is just slightly better on that very day.
Hard competion between Denmark, the Netherlands and Germany to the very last minute. Two out of three from Southern Europe.
It will come down to Ukraine or France in group D. In case the Ukraine manages to use the advantage of playing at home it seems possible that they make it to the quarter finals.
England seems to be slightly ahead especially against France. But can they do it without Rooney?
Of course we are going to compare our results with others. This is why we will not only post our prediction but also betting odds and the illuminated predictions of our local expert Jan Hendrik.
Poland is going to win its first match. Or can the Greek come up with the big surprise just like in ? Highly unlikely according to our algorithm.
Betting odds and our predictions agree on a tight matches. Maybe some tiny advantages for the Russians. As a boy I was not very fond of modeling.
My fingers are all thumbs, which is why I kept breaking the small pieces that were supposed to become ships and airplanes.
On rainy Sunday in April I even glued my thumb to the desk. The end of a short and unsuccesful career in model building.
But still, I am building models today. Or better, I have them build by the computer. Imagine you had never seen an airplane in your life.
Neither did you see a ship. Now imagine someone was going to take you by the hand and kept showing you airplanes: Passenger planes, biplanes, military jets and cargo aircrafts.
After that someone would be showing you ships: Cruise liners, oil tankers, container ships, fishing boats and yachts. If you now had to decide about an unknown vehicle you could say with certainty: Despite all the differences between the individual types of vehicles you had learned from the examples.
The computer does the exact same thing. It learns from examples. It is creating rules. One of those rules could be: A ship does not have wings.
How those rules are created can be very different from algorithm to algorithm. But what comes out of a learning algorithm is always the same.
Using this model the computer is enabled to decide wether an unknown vehicle is a ship or an aircraft. For the case of soccer matches learning is a little more difficult.
The algorithm has to distinguish between three instead of two possible outcomes. And soccer always comes up with surprises. There are underdog wins, early red cards, offside goals, unjustified penalties and Arjen Robben.
Nevertheless, can one use the computer to learn a model from examples. The question is however, if the model can be used for predictions.
If one follows along on that track one ends up with the question: When is a model a good model? And the answer is: When it models reality accurately enough.
That is not very precise, I know. But what accurately enough means depends strongly on what the model is going to be used for. A boat folded from paper will slowly drift along on the river while my authentic and very accurate model of the Titanic is at home impressing the neighbours.
If anyone at all. The same thing is true for our models. They also have to describe reality to some extend.
In order to evaluate if they can be used for prediction they have to be tested. Testing is done using vehicles where we already know wether they are ships or aircrafts but that were not used for learning.
We decided to use the Euro in Austria and Switzerland as a test. The outcomes of all games of the group phase are known and can now be compared to the predictions of our algorithms.
Doing that one finds that nine out of ten wins of the home teams are classified correctly. Only three out of eleven are recognized correctly.
Taking a look at the draws things are even worse. None of those is classified correctly. But individual matches are interesting as well.
The loss of the German team against Croatia is predicted correctly. Looking at the individual parameters for both teams one finds that Germany beats Croatia in every single one.
Same thing for the win of the Swiss over Portugal. And again the Portugese seemed to be better in every single parameter. Is this the end of our idea of predicting the Euro?
Did the algorithm develope some kind of intuition or sixth sense? To address these questions one has to take a look at the predictions and at the examples that were used for learning.
Starting with the draws one finds that there are only three draws present in our test case. That is way to few to make any statements.
More matches especially more draws are needed. But also the examples the learner was trained on are important. So, probably more draws are needed for learning as well.
For wins of the home and away teams things are little more complicated. Most of the home wins are reconized as such but there are more home wins predicted as well, 19 overall.
Compared to only four predicted wins of the away team that is a lot. Thinking about games we looked at one immediately finds that the usual advantage of the home team is not present in a European championship.
Except for the hosting countries. So, what happens as a consequence is that in case the difference between the two teams is not very large it is more likely that the home team will win.
Putting it into an example the chance of a home team win is much larger for the match Croatia — Germany than for Azerbaijan- Germany.
Such an effect is called a bias and will of course influence the prediction. Wins of the home team will be predicted much more often. Especially if the difference in strength is not very big.
Like in a Euro. Execpt for soccer June is known for something else: My Grandma taught how to make jam out of those. Two pounds of fruit, one pound of sugar, cook for five minutes and fill into a jar while still hot.
Sounds as simple as it is. Collecting historical soccer results is just as simple. Within minutes a search on google can find you basically anything you want.
Histories of all participants as well as the results of all of the final tournaments can be acessed via various websites.
And of course there are still friendlies and the World Cup. At this point one has to decide. A little more expensive but well, organic.
Or the cheap ones on sale. My Grandma always says: They have to be just perfect. Red and and fruity and full of taste. This is true for data as well.
Criteria are different though. In our case it was important that all of the basic parameters circumstances of the game could be accessed easily.
This website proved itself to be very useful. Pretty good so far. So better get some sugar. Or in our case: Go to the FIFA website.
The FIFA rankings can be accessed back until The rankings at the time of the game are an important parameter for the actual strength of the individual teams.
So is the trend. Did a nation improve? Strawberries and sugar make a pretty good jam. A little lime juice and shot of Cointreau make a taste that only Grandmas are capable of.
The same thing is true for data extracted from the Fifa ranking. They can be improved enormously using a simple trick. Not only the absolute ranking is of interest but also the difference in ranks.
So ist the difference in points. Now all ingredients just have to be cooked and filled in jars. Nevertheless, one is now enabled to predict the outcome of soccer games.
Or to make jam. Sometimes you cannot avoid the question what you are doing for a living. In case I add that I am doing this in Physics causes appreciation sometimes or surprise most of the time.
Different from what you see on TV was the best I could come up with. There's not a single blinking light in my office. But if I try to nail it down to a single point this is what I do: I classify events from a neutrino detector at the South Pole.
Usually, only physicists understand that without asking further questions. So maybe I have to simplify things.
The actual location of the detector does not really matter. So I could say: I classify events from a neutrino detector. But still it's not nice.
Now I would have to explain what a neutrino detector does. Difficult without taking the scenic route and mentioning Wolfgang Pauli and his invention of the neutrino.
Without describing the discovery of the neutrino within the famous Poltergeist experiment. Even without a short introduction to the standard model of particle physics.
You see where this is going? But what is an event? In principle an event can be anything: Tomorrow's gas price, the outcome of the next election or the outcome of a soccer match.
But how can a soccer match be similar to a physical event? If you won't settle for obvious things like the trajectory of the ball it can be summarized like that: Both can be described by certain parameters.
Parameters are basically the circumstances of an event. How are the team ranked? Who's the favorite for the bookies? Who has the better offense?
Who the better defense? In case parameters and labels are known for one might get really brave starting to make predictions.
For league games, friendlies or the EURO. And that is exactly what we are going to do. We will try to predict the games of the EURO and in a series of articles we will explain how we did that.
Starting with collecting the data and ending with an interpretation of the predictions all steps will be explained in this blog.
Can we do that? To be honest we don't know. But that's the exciting part. In soccer as well as in research. A prediction is true?
A prediction is not true? Because the real challenge is not the correct prediction but the understanding of surprising results.
Euro Who will win the European Soccer Championship? Ruhe, Tim , Differences in the B-note Looking at the three different ways of predicting soccer games one might have come up with the idea of betting.
Last game coming up on Sunday. Spanien - Italien Looks like a sure thing for Spain and the third title in a row. Who will make it to the final?
Portugal — Spain Spain slightly ahead of Portugal. We guess Ronaldo does not agree with that. After Greece Germany is going to send home Italy as well.
Opponent of the German team. Spain - France This on seems to be pretty clear. Germany - Greece According to Sami Khedira a loss against Greece does not play any role in the heads of the German players.
Czech Republic - Portugal A promising first match. The quoted probabilities correspond to the result after 90 minutes!
Last matches of the group phase. England - Ukraine Close match between England and Ukraine. Will the wikings leave the tournament with a win?
Italy, Spain or Croatia. Croatia — Spain Spain does have a clear advantage against Croatia. A mouse took a stroll through the deep dark wood.
Predicting means ordering In principle growing a decision tree is nothing more than a big ordering proceeding from the roots towards the leafs.
More trees are better Since Hermann the Cheruscan it is well known that if you will have a clear advantage if you are familiar with forests.
Using a larger number of trees in general has the effect of improving the prediction. Who will make it to the quarterfinals?
Denmark - Germany The predicted strength of the Danish for all games so far seems to be more like a natural phenomenon. Will the Dutch still make it to the quarterfinals?
Last matches of the group phase starting today. Czech Republic - Poland Our model does see some advantage for the Czech team but the psycholigical effects of playing at home are hard to predict.
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