nba-props

Different settings in src/props.ipynb for DraftKings or FanDuel (SITE), Classic or Single Game contests (MODE).
Input provided contest files from DFS sites in data/ as current-{site}.csv; if Single Game, add -sg before .csv in file name.
- Only manual step required from user besides toggling desired settings.
Additional output of line movments after initial run.
Calculates fpts according to site rules, hence requirement to toggle setting.
- Uses provided salaries to determine best allocation of salary for players as FPTS / $1,000, fpts/$.
Factors in implied probabilities of player props for separate value of "Expected Fantasy Points", e_fpts.
- Similarly uses this value with salary to determine best allocation, e_fpts/$

To install this is just like installing any other GitHub repository.
I have noticed I've received lots of clones, and I assume it is individuals in the DFS / Sports Betting space, so I figured I'd add some directions for people not used to dealing with Python super heavily.
On Linux or MacOS: Installation is done from the Command Line so open Terminal or equivalent. Windows use PowerShell/Terminal equivalent.
(optional) If want to install in location that is not home directory:

$ cd path/to/target/directory

$ git clone https://github.com/jackdegen/nba-props

(optional) If you want to create a virtual environment, .venv; if you prefer a different name, repalce .venv with it:
- Note: if you do not do this step and you do not use Python, you will have to manually install pandas, requests, BeautifulSoup, and all other necessary packages on your system with pip. This may require dealing with different system dependencies
- I strongly suggest following these steps, even if you are not entirely sure what they are doing.
- They are just installing the external libraries required to run the code only in this directory, not on your entire machine.

$ python -m venv .venv
$ source .venv/bin/activate
(.venv) $ pip install -r requirements.txt

If you have JupyterLab/JupyterNotebook, I suggest running the code in that as it is easier on the eyes and more interactive if you are familiar with Jupyter.
Direct CLI tool in development. PRs welcome.

$ jupyter-lab

This should have opened up a Jupyter Notebook in your browser.
Go to the navigation menu, and open src/props.py.
Toggle settings in top cell for SITE and MODE.
See instructions in top cell for additional customizable inputs.
Run the cells either one by one or with fast-forward button.
Need to be careful with the file: src/props-constant.ipynb:
- Running an infinite loop to update data and add any new players.
- Works with PropTracker and creates dataset of line movement throughout day in constant intervals
- Define max_runs (default = 100) for how many cycles to run.
- All data will have been saved and updated behind the scenes, will not be any output since it runs quietly in background except outputting any line movements every 10 runs.
A new file will have been created in data/ containing the info for the NBA slate that day for whichever site you specified.
You can read this in with pd.read_csv() or simply access it using PropHandler as done in src/props.ipynb to get the data to further interact with dataset in a notebook.
Removed most functionality from PropHandler since better to use as one wishes in src/props.ipynb

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.