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45 symbols 172 edges 19 files 31 documented · 69%
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README

PrizePicks

Bot I created that scrapes the uses Reverse Engineering to scrape the PrizePicks website, and then cleanse and format this data to be analyzed. After this I continue to utilize Reverse Engineering to scrape ESPN's large dataset and gather a wegihted average of a statistic for each player that has a statistic line made for them. This average in cludes the average of that player for the season, the average of that player in their last 7 games, and the average of that player over the last 3 games against the specific team that they are playing. It then calculates the difference between the predicted value, and the PrizePicks statistic line and returns the values with the biggest differences (the statistically most likely lines to hit).

Core symbols most depended-on inside this repo

Cleanse_Name
called by 8
misc.py
Calc_Avg
called by 8
calculatenba.py
get_Player_Info
called by 4
input.py
Calculate_Avg_Multiple_Years
called by 4
calculatenba.py
Create_JSON_Object
called by 4
createjson.py
Season_NFL_Events
called by 2
nflevents.py
Parse_ID
called by 2
input.py
Parse_Name
called by 2
input.py

Shape

Function 45

Languages

Python98%
Go2%

Modules by API surface

nflstats.py5 symbols
nbastats.py5 symbols
parsebets.py4 symbols
input.py4 symbols
nflevents.py3 symbols
nbaevents.py3 symbols
iteratenfl.py3 symbols
iteratenba.py3 symbols
calculatenfl.py3 symbols
calculatenba.py3 symbols
parsenba.py2 symbols
misc.py2 symbols

For agents

$ claude mcp add PrizePicks \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact