A Spanish Model
A Spanish Model
In my previous article I gave a quick recap on my pursuit on data driven betting excellence and with the English Premier League having a split gameweek, it is time to return to the continent and that means a first focus on Spain’s La Liga.
Like all other model name conventions, we are going to have give this one a name and hereby christen ‘LigaBot’ into the predictive model family. While before we put him to work, lets look at the data set that we are working with:
As before, this is working off of the home team’s last six matches versus the away teams last six matches and the points that both have accrued during that period. While the colour code should be relatively selt explanatory:
Green – The higher points of the two opposing sides
Orange – The hottest points tally
Blue – The coldest points tally
While when we turn that data into ‘LigaBot’s first initial raft of predictions, here is what they look like:
WHAT DO YOU NOTICE?
Let’s take Real Betis vs Barcelona for an example, there are 10 places between them in the La Liga table but this game is marked down as a draw and it has been due to the Catalans being indifferent on the road.
However, it seems as their poor away form is masking the fact that they are second in the table and even though they are not as dominant away from the Camp Nou, such a disparity in league places offers something of a predictive red flag.
HOW CAN WE CHANGE THIS?
At present, the predictive element is using a basis of league position and form to decide who will come out on top (or if the points will be shared) and fundamentally that will still be in place for this coming weekend.
However, there is going to be one slight twist for the dominant teams away from home and this means that their much higher league position will take on a lot more weight in this particular gameweek.
Previously the calculation was something like this:
Which means if the home team had a big enough difference in the league and in terms of form, that would be a home win and the same underlying combination would be required for the away team. However, if a team is high in the league but bad on the road, this could cause a problem.
Such as the one we are witnessing in the Real Betis vs Barcelona game and therefore, we can change the calculation to something like this:
Which means the home team still need to be much stronger in the league and in terms of form, but if the away team has a big enough difference in terms of league places (which Barcelona’s 10 places would be), then that supercedes any indifferent results on the road.
In doing that, the actual ‘LigaBot’ predictive table for the first week looks as below:
As you can see there is not an overriding difference in the results from table one to table two. However it has opened up a win for Barcelona this weekend – although now I’ve done all this work, you watch them slip up!
This will be a control week, so no money placed but as always I will use this as a V0 for the La Liga fixtures and we can build on this for the remaining third of the season, to see how we fare going forward in regard to anothet set of data driven football predictions.
Happy punting and thanks for reading. Dan
If this has grabbed your interest and you would like to discuss/feedback then please feel free to drop me a message at email@example.com. While I am always looking for new football/data projects to work on and if you feel that my skills would be of use, I can be contacted at the same address.