NHLData is a low dependecy Python package for pulling NHL data from multiple sources. Output is either a list or a list of dictionaries for all calls, allowing the end user to manipulate or store data as thier project requires.
- Python >- 3.8
- requests
pip install nhldataThe first module here is nhl_api which is a module built to connect to the two public facing NHL APIs. The endpoint documentation is based on NHL-API-Reference by Zmalski.
There are two classes (WebConnector and StatsConnector), each with unique calls inside. It is highly recommended that you reference Zmalski's work to understand what each call is doing, but there are docstrings for each function in the classes.
from nhldata import nhl
# Make connectors for the API endpoints
nhl_web = nhl.WebConnector()
# Call the API and return data
nhl_web.roster(team=COL,season=2023)from nhldata import nhl
# Make connectors for the API endpoints
nhl_stats = nhl.StatsConnector()
# Call the API and return data
nhl_stats.leaders(pos='skaters', attr='points')The second module is designed to access the available data from MoneyPuck.com. This is a series of .csv files that are converted to lists of dictionaries.
Of particular interest here is the shots data that MoneyPuck has going back to 2007/2008. THese are transported as .zip files and unpacked into list/dict structures for consumption. Per MoneyPuck:
All historical shot data is available to download. This includes 1,717,746 shots from the 2007-2008 to 2022-2023 seasons. Data for the 2023-2024 season is also available and updated nightly on this page. Saved shots on goal, missed shots, and goals are included. Blocked shots are not included in these datasets. There are 124 attributes for each shot, including everything from the player and goalie involved in the shot to angles, distances, what happened before the shot, and how long players had been on the ice when the shot was taken. Each shot also has model scores for its probability of being a goal (xGoals) as well as other models such as for the chance there will be a rebound after the shot, the probability the shot will miss the net, and whether the goalie will freeze the puck after the shot. The data has been collected from several sources including the NHL and ESPN. A good amount of data cleaning has also been done on the data. Arena adjusted shot coordinates and distances are also calculated in the dataset using the strategy War-On-Ice used from the method proposed by Schuckers and Curros.
from nhldata import moneypuck
# Make connectors for the file endpoints
moneypuck = moneypuck.Connector()
# Pull the file(s) and return the raw data
moneypuck.season_stats(file_type='skaters',seasons=[2022,2023],gametype='regular')If you know of another strong data soucre for NHL stats date, please let me know/submit a push request and we can get it added here. Happy to talk about expected format and such.