Spain
Portugal
A python script that scans various football betting sites to find what are called surebets in jargon.
python betting bet surebet
I developed this program for two reasons:
learn about data mining and processing with pandas.
determine the "SURE BET", i.e. the difference in odds between different bookmakers that guarantees a sure win on each bet.
When you launch it, you will be asked to choose one of 16 leagues.
If you have already downloaded a list of matches for that league, you will be asked to use that list saved locally, otherwise it will download and save it.
In any case, sooner or later the list of matches will have to be downloaded and inserted into a DataFrame. Here are the steps to download the list of matches:
will start reading the list of matches of the selected league from the first to the last betting site (not asynchronously, to avoid conflicts)
Each site shows a different number of matches depending on how many days are left until the match, so it will take the site with the fewest matches and start filling the match with links to various sites containing the odds we are interested in.
This is where another complication comes in, namely that different bookmakers name the teams differently ("Club Atlético de Madrid", "Atlético", "Atlético de Madrid"). To get around this problem, a query will be run based on the day and time of the match and they will be evaluated based on the similarity proportion calculated by the function.
At this point, you will see a list of matches on the screen and you can choose to search for surebets across all matches or just one (surebets [1x:2, 12:x, 2x:1, g:ng, uo0.5, uo1.5, uo2.5, uo3.5, uo4.5, uo5.5, uo6.5, uo7.5, uo8.5] will be taken into account)
for each possible surebet type, the highest value for both cases will be checked and the profit will be calculated based on it
each game at the end of these calculations will be saved in a CSV file for easier final reading
