Artificial neural networks for predicting results of football(soccer) matches.
Features:
program license: Apache License v2
e-mail: jacek87markowski@gmail.com
author: Jacek Markowski
Windows:
Linux:
Download latest BetBoy release: BetBoy download page
Before you can run BetBoy you have to install Python,Pyside and Pyfann(only on linux, included in windows version) on your system.
BetBoy repository is available on github.
Download and install Python 2.6 32 bit
Download and install Pyside for Python 2.6 32 bit
To run BetBoy just double click on bet_boy.py
Go to Ubuntu software center install :
To run BetBoy open betboy directory in terminal and type 'python bet_boy.py'
BetBoy has 8 modules for different tasks:
In this module you can check statistics for selected league:
*(predictions are made only for upcoming match day not whole round, if you take predictions from day after upcoming match day it will be inaccurate and won't be included in simulation for accuracy check)
This module allows to generate list of upcoming matches for selected leagues based on criteria defined in filters (series, odds).
Here you can perform batch simulations for selected leagues,nets and filters. Slecet league filters, net andd click button 'add' to add selected items to list. To run simulation click button 'run'. After all simulations you will be taken to selected bets tab and checks if any bets matching filters criteria where selected.
r_min - minimal round to start simulation
r_max - maximum round where stop simulation
Here you can define filters for matches: points diffrences, form diffrences (between home team and away team) and series(wins, loses, draws etc.) For example:when you select series wins home => 1 for home team in simulation will be included only matches where home team has 1 or more home wins streak. When you select points > 30 for home team in simulation will be included only matches where home team points are 30% or more (home team points and away team points = 100%) You can also filter matches by odds
Here you can define how program will transform ann output(from -1 to 1) for bet (1,1x,x,x2,2) For example: net ranges are: 1 min=-1 max=-0,3 x min=-0,3 max=0,3 2 min=0,3 max=1 neural networks gives number -0,79382 so program gives us bet 1 – home to win, beacuse -0,79382 is in range [-1,-0,3]
Here you can define filters for selecting bets. In simulation process net accuracy is checked, for example: net accuracy for 1 bets is: 50% and bet filter for 1 is 60%, so program will ignore bets (1 - home to win) from this net becausse of low accuracy. Net frequency - sometimes when ranges don't give bets from specifin ann output simulation will give none prediction, for example: there were 100 matches in simulation and 50 matches had no prediction- it means that net frequency is 50%, let's say user defined min net frequency at 60% in this case program will ignore bets from this net.
Scrape website - This module is for automatic database updates. It uses list of urls to download data from sites. Before you can update database, you have to prepare file with urls in links creator. Select urls base from saved and click load → urls list is dispalyed → select url to update click button add → click button update.
If any errors,there will be created directory data/tmp/leagues (there are stored copies of broken files) and log.txt - shows wchich lines are bad and need manual fixing (for manual fixing i recommend to use notepad++). After fixing you can copy files from data/tmp/leagues to data/leagues.
Scrape website
Here you can create file with list of urls used for updates. On the left of displayed website choose football and select league, go to fixtures select all matches and week by week. On the left next to address bar there is text line where you can enter your name for this league, after you give name to league click button '+' to add to list. When you complete picking urls you can save entire list to file. This saved file can be opened in update manager.
In this module you can manually update leagues or create own leagues.
Before you can learn artificial neural network(ann) you have to prepare data for learning:
Select leagues on which ann will be trained, give name fof exported file (above export button) and click export button (wait it takes some time dependly on numbers of selected leagues) During this process data is scaled round by round and saved to file.
There are 145 inputs[in range -1,1] scaled every round for every team and 1 output(-1 - home team won, 0- draw, 1- away team won)
In inputs included are:
Select earlier prepared file from exports, set setting for neural network (training algorithm, activation functions, epochs, reports frequency, hidden layer) and click learn, after succesful learning there will be new file in neaural networks. This created net can be used for predicting of matches(you can check in simulation for which leagues it has the best accuracy)