smartbetsAPI 1.1.2

Simple football prediction API

smartbetsAPI

"Punter's choice"

Worldwide soccer-matches predictor with a dedicated standalone Flask server as an endpoint and a package for intergrating the scripts in your own Python code.

Features

• REST-API

• Script intergration (package)

• Non-AI

Installation and usage

Installation

1. Linux

Python 3.7+ is required for this script to be fruitful to you.

• Installing through pip is always the most preferred way:

pip  install smartbetsAPI

• For those who like enjoying the latest releases from Github like me, rather than waiting for the next release:

pip install git+https://github.com/Simatwa/smartbetsAPI.git

• The hard-core guys with trust issues are very much sorted this way:

git clone https://github.com/Simatwa/smartbetsAPI.git



cd smartbetsAPI



bash install.sh 



  #or



sudo bash install.sh

Usage

1. Terminal

Running $ smartbetsAPI <api-password> will fire up the Flask server with the following default configurations.

Command	Default
Port	8000
Username	API
Filename	None
level (Logging)	20
host	False
debug	False
no-net	False
log	False
colorize	False
gui (Termux)	False

• For instance :

$ smartbetsAPI mypass9876

Here is an example of a simple program that makes prediction using the api.

Note

• Content-Type of the response (predictions) is application/json

• Reinstall with sudo privileges if smartbetsAPI command can't be found.

Example predicting using REST API

from smartbets_API import predictor

predict = predictor('http://localhost:8080','password')

bets=predict.get_predictions('Arsenal','Manchester')

print(bets)

#Output

#(True, {'choice': 55.56, 'g': 14.0, 'gg': 80.0, 'ov15': 80.0, 'ov25': 65.0, 'ov35': 55.0, 'pick': 'ov15', 'result': '1'})

• For more information you can run smartbetsAPI -h

2. Importing Package

Module predictor provides two ways of interacting with it at the programming level, based on the data-type in which the teams have been packed and parsed to it:

• Using predictorL object which accepts teams (List data-type).

For example:

#!/usr/bin/env python3

from smartbets_API.predictor import predictor



teams = [

    "Napoli",  # Home team (index [0])

    "AC Milan",  # Away team (index [1])

]

# Instantiating predictor

predict = predictor()



# Using predictorL object to handle teams (List data-type)

predictions = predict.predictorL(teams)



# Display info

print(predictions)



#Output

#{'g': 8.0, 'gg': 65.0, 'ov15': 70.0, 'ov25': 40.0, 'ov35': 30.0, 'choice': 60.0, 'result': '2', 'pick': 'ov15'}

• Using predictorD object which takes teams (Dictionary data-type):

For example:

#!/usr/bin/env python3

from smartbets_API.predictor import predictor



teams = {

    1: "Manchester City",  # 1 for home-team

    2: "Liverpool",  # 2 for away-team

}



# Instantiating predictor

predict = predictor()



# Using predictorD object to handle teams (Dictionary data-type)

predictions = predict.predictorD(teams)



# Display info

print(predictions)



#Output

#{'g': 8.0, 'gg': 65.0, 'ov15': 60.0, 'ov25': 45.0, 'ov35': 30.0, 'choice': 56.16, 'result': '1', 'pick': 'gg'}

• The output initials are explained in the table below.

Parameter	Function
g	Goal-average of the two teams
gg	Probability of both teams to score
ov15	Probability of having more than 2 goals
ov25	Probability of having more than 3 goals
ov35	Probability of having more than 4 goals
choice	Probability of the specified 'result' to occur
result	The most suitable outcome from [1,1x,x,2x,2]
pick	The most suitable outcome from [1,1x,x,2x,2,gg,ov15,ov25,ov35]

Note

• Probabilities are in percentange (%)

Further info

The predictor class accepts multiple parameters that includes :

Parameter	Function	Default
include_position	Include team's league ranking in making predictions	False
log	Log at api default log's path	False
level	Logging level	0
filename	Log to the filename specified	None
color	Colorize the logs	False
gui	Run with some Graphical interface notifications (Termux)	False
api	Run with api-server's configurations	False

The two predictor's object (predictorD, predictorL) accepts two parameters i.e.

• teams - Required

• net - Source of team's data - Default True (Online)

Source of data

Team performances are sourced from Soccerway after retrieving the uri from Google.

Warning Copyright related issues are liable to the user of this script!

Disclaimer

This project aims to help punters and bookmarkers to make informed and well researched soccer-predictions. Nevertheless, it is important to specify that 100% accuracy does not exist and smartbetsAPI can't guarantee the accuracy of the predictions. It is therefore your responsibility to trust the information generated by smartbetsAPI after evaluating its reliability. As the creator, I CANNOT be held responsible for any loss of capital that may occur during the use of this program.

Contributing and Support

Contributing

Contributions are always welcome!

Please take a look at the Contribution guidelines.

Feel free to open an Issue or to Fork this repo.

ToDo

• Upgrade to Machine learning

• Improve algorithim's accuracy

• General code improvements

• Fix bugs

Support

Consider donating to this project if you find it useful:

Credits

• Soccerway

• Google

• Python.org

Special Thanks

• victhepythonista

• YOU.