https://github.com/harmanveer-2546/sports-bets-winning-algorithm

Sports betting is the activity of predicting sports results and placing a wager on the outcome.
https://github.com/harmanveer-2546/sports-bets-winning-algorithm

adaboostclassifier ascii betting-models ensemble extratreesclassifier gradientboostingclassifier kneighborsclassifier labelencoder matplotlib mlpclassifier nfl nflstats numpy pandas plotly python seaborn sports-data string winning-algorithm

Last synced: 4 days ago
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Sports betting is the activity of predicting sports results and placing a wager on the outcome.

• Host: GitHub
• URL: https://github.com/harmanveer-2546/sports-bets-winning-algorithm
• Owner: harmanveer-2546
• Created: 2024-08-20T18:50:39.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-09-17T17:09:56.000Z (about 2 months ago)
• Last Synced: 2024-09-17T21:31:57.162Z (about 2 months ago)
• Topics: adaboostclassifier, ascii, betting-models, ensemble, extratreesclassifier, gradientboostingclassifier, kneighborsclassifier, labelencoder, matplotlib, mlpclassifier, nfl, nflstats, numpy, pandas, plotly, python, seaborn, sports-data, string, winning-algorithm
• Language: Jupyter Notebook
• Homepage:
• Size: 2.79 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Sports Bets Winning Algorithm

Make your betting decisions and moves strategically with the math-driven logic of our sports betting algorithm solutions. The sports betting prediction and 

algorithms use neural networks and machine learning algorithms to understand and predict the best outcomes from complex problems and provide your 

players with accurate odds based on team and individual players’ statistics. From planning sports betting software to development, and addition of 

sports betting algorithm software, and even after, we make everything possible.

### About the Dataset :

National Football League (NFL) game results since 1966 with betting odds information since 1979. The dataset was created from a variety of sources including

games and scores from various public websites such as ESPN, NFL.com, and Pro Football Reference. Weather information is from NOAA data with NFLweather.com as a 

good cross reference. Betting data was used from http://www.repole.com/sun4cast/data.html for the 1978-2013 seasons. Pro-football-reference.com data was then 

cross-referenced for betting lines and odds as well as weather data. From 2013 betting data reflects lines available at sportsline.com and aussportsbetting.com.