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Simple football prediction API

Project description

smartbetsAPI

Github License PyPi Black Accuracy Passing coverage Progress Downloads


"Punter's choice"

Worldwide soccer-matches predictor with Fast-API and a package for integrating the scripts in your own Python code.

Features

  • REST-API

  • Script integration (package)

  • Non-ML

Installation and usage

Installation

Python 3.9+ 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 one:
pip install git+https://github.com/Simatwa/smartbetsAPI.git

To install it alongside REST-API dependencies simply run:

pip install "smartbetsapi[api]"

Usage

  1. Terminal

Running $ smartbetsAPI <token/password> will fire up the FastAPI 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

[!TIP]

Docs will be available at : http://localhost:8000/v1/docs

Redoc will be available at : http://localhost:8000/v1/redoc

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

api running

[!Note]

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
  1. 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_positionInclude 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:

API Health Status

| No. | API | Status |

|--------|-----|--------|

| 1. | On-render | cron-job |

Credits

Special Thanks

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