Group 15 - socceranalysis (python)

[vincentho32]

Submitting Author: Flora Ouedraogo (@florawendy19), Gaoxiang Wang (@louiewang820), Manvir Kohli (@manvirsingh96)
, Vincent Ho (@vincentho32)
All current maintainers: (@florawendy19, @louiewang820, @manvirsingh96, @vincentho32)
Package Name: socceranalysis
One-Line Description of Package: With this package, you can quickly obtain summary statistics for a particular team, identify outliers based on market value, rank players by goals per game and display different plots with soccer data.
Repository Link: https://github.com/UBC-MDS/socceranalysis_python
Version submitted: v1.0.0
Editor: Flora Ouedraogo (@florawendy19), Gaoxiang Wang (@louiewang820), Manvir Kohli (@manvirsingh96)
, Vincent Ho (@vincentho32)
Reviewer 1: Morris Chan
Reviewer 2: Daniel Cairns
Reviewer 3: Vikram Grewal
Reviewer 4: Yaou Hu
Archive: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

---

Description

socceranalysis is a powerful Python package designed to make it easy to analyze and understand soccer statistics. With its set of functions, you can quickly obtain summary statistics for a particular team, identify outliers based on market value, rank players by goals per game and display different plots.

The package is built in a way that allows user to easily customize the functions to their own interests, giving them the flexibility to analyze the data in a way that is most meaningful to them. Whether you're a coach, a sports journalist or an analyst, socceranalysis will help you unlock the insights hidden in your soccer data and make more informed decisions.

Scope

• Please indicate which category or categories this package falls under:
  • Data retrieval
  • Data extraction
  • Data munging
  • Data deposition
  • Reproducibility
  • Geospatial
  • Education
  • Data visualization*

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  • Who is the target audience and what are scientific applications of this package?
    The target audience is anyone who is interested in analyzing soccer data. It can be coaches, sports journalists, analysts or fans.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?
    There is a package on PyPi named pyrankingfifa to get the current ranking of the FIFA team. We also have a similar ranking function and three other functions that can help users to get the summary statistics, outliers and visualizations of numerical features.

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[YHuUBC]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

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For packages also submitting to JOSS

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Final approval (post-review)

• The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing: 1 hour

---

Review Comments

Congratulations on creating such an interesting package. Your package is well-developed and fun to use.

I have the following suggestions for your reference:

1. Your package has passed all tests, and the CI-CD workflow functions well, but such information is not easy to find for a user; maybe you could include these badges on your README.md.
2. Your package's readthedocs website has no example usage information. Please double-check the link.
3. Following the usage example indicated in your package's README.md, rankingplayers function does not work.
   from socceranalysis.rankingplayers import * data = pd.read_excel('soccer_data.xlsx') rankingplayers(data, "Goals_total", "Assists_Total")

The ModuleNotFoundError appears:
`---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
Cell In[9], line 1
----> 1 from socceranalysis.rankingplayers import *
2 data = pd.read_excel('soccer_data.xlsx')
3 rankingplayers(data, "Goals_total", "Assists_Total")

ModuleNotFoundError: No module named 'socceranalysis.rankingplayers'
​`

4. When using your package, Altair package that you imported has some warning.
   FutureWarning: iteritems is deprecated and will be removed in a future version. Use .items instead.
   You may take a look at it for the benefit of future users.
5. You explained very well how your package fits and relates to the existing Python ecosystem. I was wondering if there is any package that has similar functions as your package. If so, how is your package different from others? If not, you might highlight your package's uniqueness on your README file.

Great job! It is a pleasure reviewing your package.

[morrismanfung]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• A statement of need clearly stating problems the software is designed to solve and its target audience in README.
• Installation instructions: for the development version of the package and any non-standard dependencies in README.
• Vignette(s) demonstrating major functionality that runs successfully locally.
• Function Documentation: for all user-facing functions.
• Examples for all user-facing functions.
• Community guidelines including contribution guidelines in the README or CONTRIBUTING.
• Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a pyproject.toml file or elsewhere.

Readme file requirements
The package meets the readme requirements below:

• Package has a README.md file in the root directory.

The README should include, from top to bottom:

• The package name
• Badges for:
  • Continuous integration and test coverage,
  • Docs building (if you have a documentation website),
  • A repostatus.org badge,
  • Python versions supported,
  • Current package version (on PyPI / Conda).

NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• Short description of package goals.
• Package installation instructions
• Any additional setup required to use the package (authentication tokens, etc.)
• Descriptive links to all vignettes. If the package is small, there may only be a need for one vignette which could be placed in the README.md file.
  • Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)
• Link to your documentation website.
• If applicable, how the package compares to other similar packages and/or how it relates to other packages in the scientific ecosystem.
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Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole.
Package structure should follow general community best-practices. In general please consider whether:

• Package documentation is clear and easy to find and use.
• The need for the package is clear
• All functions have documentation and associated examples for use
• The package is easy to install

Functionality

• Installation: Installation succeeds as documented.
• Functionality: Any functional claims of the software been confirmed.
• Performance: Any performance claims of the software been confirmed.
• Automated tests: Tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
• Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)
• Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.
  A few notable highlights to look at:
  • Package supports modern versions of Python and not End of life versions.
  • Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

For packages also submitting to JOSS

• The package has an obvious research application according to JOSS's definition in their submission requirements.

Note: Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

The package contains a paper.md matching JOSS's requirements with:

• A short summary describing the high-level functionality of the software
• Authors: A list of authors with their affiliations
• A statement of need clearly stating problems the software is designed to solve and its target audience.
• References: With DOIs for all those that have one (e.g. papers, datasets, software).

Final approval (post-review)

• The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing:

1 hour

Review Comments

1. Great package for basic data wrangling. While the package is heavily soccer-themed, the functionalities are quite general. Maybe you could consider expanding the target audience of the package as these functions are all potentially useful on other contexts.
2. Some functions are not necessary in the package as the same procedures can be easily done with similar amount of codes. Do consider either dropping them or improving them by adding more unique features tied to the package.
3. Examples in https://soccer-analysis-python.readthedocs.io/en/latest/example.html seem to be unfinished.
4. Maybe you could consider using another plotting library such as seaborn to reduce the chance of having issues related to incompatibility with altair.
5. As the number of functions is still small in the package, do consider putting them into the same .py file for simplicity.

Well done! I wish you all the best in your journey of software development :)

[DanielCairns]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• A statement of need clearly stating problems the software is designed to solve and its target audience in README.
• Installation instructions: for the development version of the package and any non-standard dependencies in README.
• Vignette(s) demonstrating major functionality that runs successfully locally.
• Function Documentation: for all user-facing functions.
• Examples for all user-facing functions.
• Community guidelines including contribution guidelines in the README or CONTRIBUTING.
• Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a pyproject.toml file or elsewhere.

Readme file requirements
The package meets the readme requirements below:

• Package has a README.md file in the root directory.

The README should include, from top to bottom:

• The package name
• Badges for:
  • Continuous integration and test coverage,
  • Docs building (if you have a documentation website),
  • A repostatus.org badge,
  • Python versions supported,
  • Current package version (on PyPI / Conda).

NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• Short description of package goals.
• Package installation instructions
• Any additional setup required to use the package (authentication tokens, etc.)
• Descriptive links to all vignettes. If the package is small, there may only be a need for one vignette which could be placed in the README.md file.
  • Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)
• Link to your documentation website.
• If applicable, how the package compares to other similar packages and/or how it relates to other packages in the scientific ecosystem.
• Citation information

Usability

Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole.
Package structure should follow general community best-practices. In general please consider whether:

• Package documentation is clear and easy to find and use.
• The need for the package is clear
• All functions have documentation and associated examples for use
• The package is easy to install

Functionality

• Installation: Installation succeeds as documented.
• Functionality: Any functional claims of the software been confirmed.
• Performance: Any performance claims of the software been confirmed.
• Automated tests: Tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
• Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)
• Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.
  A few notable highlights to look at:
  • Package supports modern versions of Python and not End of life versions.
  • Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

Final approval (post-review)

• The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing:

1

Review Comments

Really neat package. Works exactly as described with no issues. I've noted a few of my thoughts below on future improvements / quality of life fixes but none are serious.

1. I got an error trying to use the direct installation as specified in your "installation" section, but pip install socceranalysis works as expected.

2. Would be nice to not have to download your dataset manually

3. Could add more badges - they make it look professional!

4. Can I have more information about the dataset itself? What's the source? What years does it cover / how recent is it? Any copyright or usage issues with the data I should be concerned about? etc.

5. If would be useful to list somewhere (either in the documentation or as a function) which stats are available as function inputs. You functions assume we know 1. what stats are available and 2. how the column headers are formatted

[xFiveRivers]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• A statement of need clearly stating problems the software is designed to solve and its target audience in README.
• Installation instructions: for the development version of the package and any non-standard dependencies in README.
• Vignette(s) demonstrating major functionality that runs successfully locally.
• Function Documentation: for all user-facing functions.
• Examples for all user-facing functions.
• Community guidelines including contribution guidelines in the README or CONTRIBUTING.
• Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a pyproject.toml file or elsewhere.

Readme file requirements
The package meets the readme requirements below:

• Package has a README.md file in the root directory.

The README should include, from top to bottom:

• The package name
• Badges for:
  • Continuous integration and test coverage,
  • Docs building (if you have a documentation website),
  • A repostatus.org badge,
  • Python versions supported,
  • Current package version (on PyPI / Conda).

NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• Short description of package goals.
• Package installation instructions
• Any additional setup required to use the package (authentication tokens, etc.)
• Descriptive links to all vignettes. If the package is small, there may only be a need for one vignette which could be placed in the README.md file.
  • Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)
• Link to your documentation website.
• If applicable, how the package compares to other similar packages and/or how it relates to other packages in the scientific ecosystem.
• Citation information

Usability

Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole.
Package structure should follow general community best-practices. In general please consider whether:

• Package documentation is clear and easy to find and use.
• The need for the package is clear
• All functions have documentation and associated examples for use
• The package is easy to install

Functionality

• Installation: Installation succeeds as documented.
• Functionality: Any functional claims of the software been confirmed.
• Performance: Any performance claims of the software been confirmed.
• Automated tests: Tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
• Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)
• Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.
  A few notable highlights to look at:
  • Package supports modern versions of Python and not End of life versions.
  • Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

Final approval (post-review)

• The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing:

---

Review Comments

• The usage section in your readme could use more detail in terms of what specifically will occur when you use the functions. It makes sense when you read through the documentation, but a higher-level overview of what the outputs will give would be nice.
• The functions should incorporate downloading the data set automatically, the user should not have to do extra steps to use the package. Maybe have a data folder in your repo.
• If you include a link to download the data set, it would also be good to run through what the data set contains and how it relates to your package.
• To make the website and readme file flow a little better, it would be better to embed the links so that your do not have long urls.
• The example usage is not complete on your website, might be worth finishing that section.