REPOGEO REPORT · LITE

kochlisGit/ProphitBet-Soccer-Bets-Predictor

Default branch main · commit 49fb86be · scanned 6/13/2026, 9:17:45 AM

GitHub: 538 stars · 157 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 kochlisGit/ProphitBet-Soccer-Bets-Predictor, 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

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

OVERALL DIRECTION

highreadme#1

Add a clear, concise project overview to the README's beginning

Why:

CURRENT

# New Version (Release 03-17-2026)

COPY-PASTE FIX

ProphitBet is an interactive Machine Learning application designed to predict soccer match outcomes, assisting sports bettors with data-driven insights. Utilizing advanced ML methods like Neural Networks and Random Forests, it analyzes team form and match statistics, delivered via a user-friendly Streamlit web interface.

mediumhomepage#2
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
Add the URL to your live Streamlit application or project website here.
```

lowreadme#3

Add a 'Key Features' section to the README

Why:

COPY-PASTE FIX

## Key Features

*   **Machine Learning Predictions:** Utilizes Neural Networks, Random Forests, and Ensemble Models to predict soccer match outcomes.
*   **Statistical Analysis:** Analyzes team form and computes comprehensive match statistics.
*   **Interactive Application:** Provides a user-friendly interface for exploring predictions and insights.

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 kochlisGit/ProphitBet-Soccer-Bets-Predictor

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

XGBoost

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

XGBoost · recommended 2×
LightGBM · recommended 2×
CatBoost · recommended 2×
scikit-learn · recommended 2×
Optuna · recommended 2×

CATEGORY QUERY
How to build a machine learning model for predicting soccer match results accurately?
you: not recommended
AI recommended (in order):
1. Football-Data.co.uk
2. StatsBomb Open Data
3. Opta Sports
4. Wyscout
5. InStat
6. Transfermarkt
7. Premier League
8. La Liga
9. Pandas
10. NumPy
11. XGBoost
12. LightGBM
13. CatBoost
14. Logistic Regression
15. Random Forest
16. Support Vector Machine (SVM)
17. scikit-learn
18. Optuna
19. Hyperopt
20. GridSearchCV
21. Flask
22. FastAPI
23. Docker
24. Heroku
25. AWS Lambda
26. Google Cloud Functions
AI recommended 26 alternatives but never named kochlisGit/ProphitBet-Soccer-Bets-Predictor. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are effective Python tools for sports betting predictions using advanced ML algorithms?
you: not recommended
AI recommended (in order):
1. scikit-learn
2. XGBoost
3. LightGBM
4. CatBoost
5. TensorFlow
6. Keras
7. PyTorch
8. pandas
9. Statsmodels
10. Optuna
11. Hyperopt
AI recommended 11 alternatives but never named kochlisGit/ProphitBet-Soccer-Bets-Predictor. 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 kochlisGit/ProphitBet-Soccer-Bets-Predictor?
pass
AI did not name kochlisGit/ProphitBet-Soccer-Bets-Predictor — 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?
If a team adopts kochlisGit/ProphitBet-Soccer-Bets-Predictor in production, what risks or prerequisites should they evaluate first?
pass
AI named kochlisGit/ProphitBet-Soccer-Bets-Predictor explicitly
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 kochlisGit/ProphitBet-Soccer-Bets-Predictor solve, and who is the primary audience?
pass
AI did not name kochlisGit/ProphitBet-Soccer-Bets-Predictor — 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?

Embed your GEO score

Drop this badge into the README of kochlisGit/ProphitBet-Soccer-Bets-Predictor. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/kochlisGit/ProphitBet-Soccer-Bets-Predictor.svg)](https://repogeo.com/en/r/kochlisGit/ProphitBet-Soccer-Bets-Predictor)

HTML

<a href="https://repogeo.com/en/r/kochlisGit/ProphitBet-Soccer-Bets-Predictor"><img src="https://repogeo.com/badge/kochlisGit/ProphitBet-Soccer-Bets-Predictor.svg" alt="RepoGEO" /></a>

Pro

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kochlisGit/ProphitBet-Soccer-Bets-Predictor — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite