Dashboard / Repos / Nba Predictor

Nba Predictor

F 50 completed
Web App
web_app / python · tiny
26
Files
1,744
LOC
1
Frameworks
6
Languages
OverviewFiles & MetricsGit ActivityCall GraphSecurityReports

Pipeline State

completed
Run ID
#359029
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
42.55
Framework unique
—
Isolation
—
Last stage change
2026-05-10 03:35:10
Deduplication group #52921
Member of a group with 14 similar repo(s) — canonical #28067 view group →
Top concepts (1)
Web Backend
All rows above produced by Repobility · https://repobility.com

AI Prompt

I want to build a web application that predicts NBA games and provides insights to users. Can you set up the basic structure using Flask? The app should be able to read configuration from a YAML file and potentially use JSON for data handling. I need the core logic to be in Python, and the frontend should use HTML and CSS templates. Please structure it so it's ready for deployment, considering the provided file structure.
python flask web-app nba prediction data-analysis html css yaml json
Generated by gemma4:latest

Catalog Information

This project is a web application that predicts NBA games and provides insights to users.

Description

The NBA Predictor is a web-based tool that uses machine learning algorithms to forecast the outcomes of NBA games. It leverages data from various sources, including game statistics and team performance metrics, to provide accurate predictions. The application aims to assist sports enthusiasts in making informed decisions about their fantasy teams or simply to enhance their viewing experience.

الوصف

هذا المشروع هو تطبيق ويب يقوم بتنبؤ نتائج مباريات إن بي إيه ويوفر معلومات للمستخدمين. يستخدم هذا التطبيق خوارزميات التعلم الآلي لتنبؤ النتائج، ويستفيد من البيانات من مصادر متعددة، بما في ذلك الإحصائيات والبيانات المتعلقة بفريقين. يهدف هذا التطبيق إلى مساعدة محبي الرياضة على اتخاذ قرارات مدروسة حول فرقهم الخيالية أو مجرد تحسين تجربتهم أثناء مشاهدة المباريات.

Novelty

5/10

Tags

sports-prediction machine-learning data-visualization nba-data game-outcome-prediction

Technologies

beautifulsoup flask gunicorn numpy pandas scikit-learn

Claude Models

claude-opus-4.6

Quality Score

F
49.7/100
Structure
39
Code Quality
71
Documentation
29
Testing
0
Practices
65
Security
100
Dependencies
60

Strengths

  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected

Weaknesses

  • Missing README file \u2014 critical for project understanding
  • No LICENSE file \u2014 legal ambiguity for contributors
  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment
  • 160 duplicate lines detected \u2014 consider DRY refactoring

Recommendations

  • Add a comprehensive README.md explaining purpose, setup, usage, and architecture
  • Add a test suite \u2014 start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a linter configuration to enforce code style consistency
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

5.6h
Tech Debt (D)
A
OWASP (100%)
FAIL
Quality Gate
A
Risk (20)
Repobility's GitHub App fixes findings like these · https://github.com/apps/repobility-bot
Unknown
License
5.3%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
76.0%
html
17.9%
css
3.0%
json
1.8%
yaml
0.7%
text
0.6%

Frameworks

Flask

Concepts (1)

Source: Repobility analyzer (https://repobility.com)
CategoryNameDescriptionConfidence
Repobility · severity-and-effort ranking · https://repobility.com
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

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