RRepoGEO

REPOGEO REPORT · LITE

devinpleuler/analytics-handbook

Default branch master · commit 1a76865b · scanned 5/27/2026, 11:47:55 PM

GitHub: 1,678 stars · 216 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface devinpleuler/analytics-handbook, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highhomepage#1
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://colab.research.google.com/github/devinpleuler/analytics-handbook/blob/master/soccer_analytics_handbook.ipynb
  • mediumreadme#2
    Add a concise purpose statement immediately after the README title

    Why:

    CURRENT
    ## Soccer Analytics Handbook

Devin Pleuler — April 2020

[](https://colab.research.google.com/github/devinpleuler/analytics-handbook/blob/master/soccer_analytics_handbook.ipynb)

February 2023 Update:
    COPY-PASTE FIX
    ## Soccer Analytics Handbook

This repository provides a practical, hands-on guide for learning and applying data analytics techniques to soccer (football) data, primarily using Python and public datasets.

Devin Pleuler — April 2020

[](https://colab.research.google.com/github/devinpleuler/analytics-handbook/blob/master/soccer_analytics_handbook.ipynb)

February 2023 Update:

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface devinpleuler/analytics-handbook
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pandas
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pandas · recommended 2×
  2. Matplotlib · recommended 2×
  3. Seaborn · recommended 2×
  4. Scikit-learn · recommended 2×
  5. Statsmodels · recommended 2×
  • CATEGORY QUERY
    Looking for a guide to start soccer analytics projects using public datasets.
    you: not recommended
    AI recommended (in order):
    1. Jupyter Notebooks
    2. JupyterLab
    3. VS Code
    4. Pandas
    5. Matplotlib
    6. Seaborn
    7. Plotly
    8. Bokeh
    9. Scikit-learn
    10. Statsmodels
    11. mplsoccer
    12. RStudio
    13. Tidyverse
    14. dplyr
    15. ggplot2
    16. tidyr
    17. data.table
    18. caret
    19. StatsBomb Open Data (statsbomb/open-data)
    20. statsbombpy
    21. Wyscout
    22. Friends of Tracking
    23. Metrica Sports
    24. FBref.com
    25. Beautiful Soup
    26. Scrapy
    27. Kaggle
    28. Understat.com
    29. requests
    30. Transfermarkt.com
    31. Friends of Tracking YouTube Channel
    32. Soccermatics by David Sumpter
    33. Data-driven Football by Jan Van Haaren & Maarten Van Gool
    34. Twitter
    35. Reddit (r/socceranalytics)

    AI recommended 35 alternatives but never named devinpleuler/analytics-handbook. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What Python resources exist for analyzing football match event data?
    you: not recommended
    AI recommended (in order):
    1. Matplotlib
    2. Seaborn
    3. Pandas
    4. Statsmodels
    5. Scikit-learn
    6. mplsoccer
    7. OptaPy
    8. Socceraction

    AI recommended 8 alternatives but never named devinpleuler/analytics-handbook. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of devinpleuler/analytics-handbook?
    pass
    AI named devinpleuler/analytics-handbook explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts devinpleuler/analytics-handbook in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name devinpleuler/analytics-handbook — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo devinpleuler/analytics-handbook solve, and who is the primary audience?
    pass
    AI did not name devinpleuler/analytics-handbook — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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devinpleuler/analytics-handbook — RepoGEO report