NHL-Prediction-Model | team winning a given matchup

by HarryShomer Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | NHL-Prediction-Model Summary

NHL-Prediction-Model is a Python library. NHL-Prediction-Model has no bugs, it has no vulnerabilities and it has low support. However NHL-Prediction-Model build file is not available. You can download it from GitHub.

Model for computing the probability of each team winning a given matchup in the National Hockey League

Support

Quality

Security

License

Reuse

Support

NHL-Prediction-Model has a low active ecosystem.

It has 12 star(s) with 4 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

NHL-Prediction-Model has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NHL-Prediction-Model is current.

Quality

NHL-Prediction-Model has 0 bugs and 29 code smells.

Security

NHL-Prediction-Model has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

NHL-Prediction-Model code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NHL-Prediction-Model does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

NHL-Prediction-Model releases are not available. You will need to build from source code and install.

NHL-Prediction-Model has no build file. You will be need to create the build yourself to build the component from source.

It has 1033 lines of code, 67 functions and 11 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed NHL-Prediction-Model and discovered the below as its top functions. This is intended to give you an instant insight into NHL-Prediction-Model implemented functionality, and help decide if they suit your requirements.

Calculates the reliability of a given position
Aggregate previous year
Process skater data
Calculate marcel weights for a given dataframe
Get model data
Convert marcels to a Pandas DataFrame
Convert the roster to a dict
Merge all outcome outcomes from the stats_df
Returns a dictionary with the team data
Updates the player s rating
Computes the probability for the given game
R Regress elo
Get all players for a given season
Return a dict of all players and their goals
Return a BeautifulSoup object from the roster
Fix the player name
Fix the names of the players
Builds the separation models for each team
Build a pandas DataFrame for each model
Extract the relevant features from a DataFrame
Extract features from a DataFrame
Returns a BeautifulSoup object
Get information about the team

Get all kandi verified functions for this library.

NHL-Prediction-Model Key Features

No Key Features are available at this moment for NHL-Prediction-Model.

NHL-Prediction-Model Examples and Code Snippets

No Code Snippets are available at this moment for NHL-Prediction-Model.

Community Discussions

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Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install NHL-Prediction-Model

You can download it from GitHub.
You can use NHL-Prediction-Model like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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