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PythonBaseballSim (B.A.S.E.S.)

Installation and Usage

BASES is a python application with a website front-end interface. The website was developed with the python web framework Bottle.

Run Website:

  • First open up app.py and locate at the end of the file, the port number and debug option

  • For production, turn debug to false (debug = false)

  • The port number is anything to specify (i.e. 8888)

  • Run the website by typing the command below into the command prompt

      python app.py
    
  • Navigate to your webbrowser and enter http://localhost:8888/

About the Project

The BASES project was developed by a group of summer research students and professors at Monmouth University during the university's annual School of Science Summer Research Program.

This program intends to accurately simulate a baseball game from first pitch to last. The simulation will be based on real data obtained from the 2014 MLB season. The simulation will model a game pitch-by-pitch and use batting and pitching statistics as well as fielding statistics to best predict the outcome of a game.

Major Features/Goals:

  • Store relevant statistics of a single Major League Baseball Season in comma-separated values (CSV) files
  • Simulate the interaction between a batter and a pitcher
  • Simulate the actions of players on the field
  • Simulate the interaction between the home and away teams
  • Analyze the outcome of a simulated game based on the data provided
  • Allow the user to choose any two Major League Baseball teams to simulate a game
  • Provide a user interface with a scoreboard which updates throughout the game

Development

The BASES project was developed using these following tools and frameworks

Members

BASES development team members, without us, this whole thing wouldn't have happened.

  • Reid Cooper
  • Philip DiMarco
  • Mary Menges
  • Nicholas-Jason Roache
  • Chenqi Zhu
  • Swethana Gopisetti
  • Our Research Mentor and Professor, Gil Eckert

Funding

Our project wouldn't be possible if it wasn't for our wonderful sponsors!

Sources

Items used on our website and in our simulation are given credit below.

About

2015 Monmouth University Research

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  • Python 73.6%
  • Smarty 24.3%
  • CSS 1.4%
  • JavaScript 0.7%