Predict Soccer Results With Machine Learning
- Tila: Closed
- Palkinto: $20
- Vastaanotetut työt: 27
- Voittaja: yatishdua
Soccer is the world's most popular sport.
**This contest will test whether you're among the best Machine Learning engineers in the world.**
Your challenge is to use ML & Deep Learning to build a model that can best classify the outcome of a soccer match given publicly available data.
The data provided includes details on a team's recent performance, probability of winning, match location, date, recent performance against the opposing team & other recent info. In all, there are close to 100 input variables provided.
Each soccer match's results are provided under the Outcome column in the training data. A match can either be a home_team_win (indicated with 1 in the outcome colume), a draw (indicated with 0) or a away_team_win (indicated with 2).
A leaderboard of top 10 performing models will be posted daily on the contest's chat room.
The competition will run for 14 days.
A small payout has been guaranteed & will be provided to the winner of the contest.
If you win the contest, you may be hired as a consulting once the contest has concluded. Your consultation services will be compensated at a agreed payment rate.
There are 3 datasets provided.
1. [login to view URL] - This contains 31600 matches & their outcomes that you will use to train your model(s).
2. [login to view URL] - This contains 7900 matches & their outcomes that you will use to test/validate your model(s) performance.
3. [login to view URL] - This contains 500 matches (without outcomes) that you will need to predict with your model & submit their results as a list of 0,1 & 2 as part of your submission.
- The F1 Score ([login to view URL]) will be used to determine your model's performance against other contestants.
- This F1 Score will be based on the predictions you make for the data in point 3 above ([login to view URL]).
For the leaderboard, F1 Scores will be rounded off to 3 decimal places.
- Should there be a tie, all of the top positioned contestants will each get the guaranteed payout.
- You may post as submissions many times as you wish.
1. You are encouraged to use Python for model construction.
2. You may use any classification technique as you see fit (Deep Learning, Machine Learning)
Your submission must contain 2 things.
1. A list of your model's predictions on the [login to view URL] file. This must be posted as a comment in your submission. The list must be of the form: [0,1,2,2,0...,1,2]
2. A picture of your validation data F1 Score (calculated on '[login to view URL]').
You are welcome to post any questions that you have on the contest's chat board.
Are you among the best of the best in Maching Learning?
PROVE IT by winning this contest.
“Yatish submitted high quality & reproducible code.”
LuyandaD, South Africa.