Predicting The Outcome Of Soccer Matches With Data
In a post i did a couple of months ago, i was looking into whether we could use big data to predict the outcome of a soccer match. Before you say that's a waste of time, Google's doing something similar with their competition to predict the outcome of the NCAA basketball championship on Kaggle.
Unfortunately, after month of looking around, i've come to realize that such data doesn't come cheap. The freely available data also lacks a lot of the data points that i'm interested in like player values and suspensions.
Time for plan B
I don't have the deep pockets of Google to pay for such data so i've had to improvise. If i can't do a proper prediction model and run it through a test set, i will create a model manually, assigning weights to data points that affect the outcome of a match in order to come up with a score for each team. The team with the higher score wins and if they're close, this indicates a high probability of a draw.
I won't give the exact weights for the fields but here is what i've found that's able to predict the result fairly accurately:
- Number of days between matches
- Squad value
- Home/Away form
- Manager H2H
The results so far
Because squad value is subjective, this prediction model tends to only work on the bigger leagues where there's a fairly accurate estimate of a player's worth. Using it on a small league like the S-League had much poorer performance. With 2 weeks of publishing predictions so far, the results have been 7/10 for both weeks. It really should have been 8/10 on the second week but i got distracted lol.
You can see the predictions - here and here.
Predictions made randomly should average out to 3/10 over the long run. I'll continue to publish the predictions over the coming weeks and hopefully the model holds up. It will get interesting after Game Week 35 because some teams won't have anything to play for. They'll start resting players and it's hard to know who makes the squad. The model assumes the best team from each side plays so i expect the performance to decrease.
For about 15 years me and my friends are playing a soccer prediction game. In one of these years I try to create a model to predict the score of the game. As predicting the score is more difficult than predicting the result, my model resulted so bad than I thought.
While I was creating the model I include these factors:
Actually the model was not bad when predicting the result, as it gives correct results between 40% to 60% but when it comes to score prediction it is not what i expect.
Very interesting, @udgu. I think to consistently predict the correct score is impossible because there are so many possibilities.
Asian Handicap might be more accurate the odds are so low it is often not worth it unless the bookies get it wrong :)
As you said there are so many possibilities but I just want to try it for our game. I used that for two weeks actually and quit it because my own predictions are more accurate :)
these type of thing are needed in football ... thanks for the article.
Hope you will find it useful
This will be so useful in football bro👊🏽
To listen to the audio version of this article click on the play image.
Brought to you by @tts. If you find it useful please consider upvote this reply.
You got a 2.65% upvote from @postpromoter courtesy of @numpypython!
Want to promote your posts too? Check out the Steem Bot Tracker website for more info. If you would like to support the development of @postpromoter and the bot tracker please vote for @yabapmatt for witness!
This post has received gratitude of 4.89% from @appreciator courtesy of @numpypython!
Cool! I follow you.
I also think using the prediction sites moves us closer but it is not also accurate. I win most times but just little money because i picked few secured games