Linestar Scrape

Goals

The goal of this project is to provide a person with a standardized format for getting linestar ownership data so that it can be used for better understanding daily fantasy competitions

Example: https://www.linestarapp.com/Ownership/Sport/NBA/Site/FanDuel/PID/420

In order to scrape this page, lots of tedious work would have to be done in order to pull data from this site that could only be used for a specific use case. Why not make a package that can be used by everyone? This page contains valueable information to fantasy players and can be used for many DFS data science applications.

Installation

pip install linestar-scrape

• Be sure to update often to get the latest mapping from human datetime to linestar date id

Methods

fanduel_nba_own_date(date)

Inputs:

• Python datetime

Output: Linestar Page Data Object containing Linestar Data For That Date

fanduel_nba_own_date_range(date1, date2)

Inputs:

• date1 = Python datetime for first date
• date2 = Python datetime for second date

Output: Linestar Map with Date String (YYYY-MM-DD) being the key and a Linestar Page Data Object being a value for inclusive range of dates

Linestar Objects

Linestar Page Data

Object Name: LinestarPageData

Members

• date
• competitions (array of LinestarCompeition)
• url (link to url scraped)

Linestar Competitions

Object Name: LinestarCompeition

Members

• name (competition name)
• id (competition id)
• games (number of games for competition)
• gpp (True if GPP Competition)
• doubleUp (True if Double Up Competition)
• players (Array of LinestarPlayerObject)

Linestar Players

Object Name: LinestarPlayerObject

Members

• id (player id)
• name (player name)
• owned (percent owned, in float format (ie: 78.2))
• pos (position)
• team
• sal (salary)

Examples

import linestar

single_data = linestar.standard.fanduel_nba_own_date(datetime(2019, 2, 10))

range_data = linestar.standard.fanduel_nba_own_date(datetime(2019, 2, 5), datetime(2019, 2, 10))