Ncaa Eval
B+ 89 completed
Ai Ml
unknown / markdown · medium
1,068
Files
111,807
LOC
1
Frameworks
8
Languages
Pipeline State
completedRun ID
#297933Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
CatalogedDecision
proceedNovelty
60.40Framework unique
—Isolation
—Last stage change
2026-05-10 03:34:36Deduplication group #47460
Member of a group with 14 similar repo(s) — canonical #2600 view group →
Top concepts (12)
Repositorytestingpresentationapibusiness_logicdata_accessinfrastructureStrategySearchTestingUser ManagementAnalytics
If a scraper extracted this row, it came from Repobility (https://repobility.com)
🧪 Code Distillation
Browse all specs →Sample distilled functions (click for full spec)
runExecutes the pytest test suite within the environment specified by VENV_PREFIX, passing the context object as an input. It returns nothing directly, instead controlling the program's exit status based on the test runner's exit code. If the optional allow_no_tests flag is true and the test runner exi
commit_checkExecutes a command using the provided context object to check commit messages against a remote repository. It takes a context object and an optional remote name, defaulting to "origin". The function outputs nothing but performs a check, warning if any commits in the specified range fail the commitiz
init_devInstalls development dependencies using pipenv and optionally sets up pre-commit hooks. It accepts a context object and a boolean flag to skip pre-commit setup. The function returns nothing and its primary side-effect is executing shell commands to modify the environment and project setup.
AI Prompt
Create an evaluator tool for self-assessing NCAA March Mania Kaggle Competition models. I need it to handle data ingestion by syncing NCAA game data from Kaggle (1985–2025) and ESPN, including smart caching. The tool must support feature engineering with sequential stats, graph-based centrality, batch ratings like SRS and Elo, and opponent adjustments. It should feature a plugin-based model registry for both stateful (like Elo) and stateless models. For evaluation, implement walk-forward cross-validation using metrics such as Log Loss, Brier Score, ROC-AUC, and ECE. Finally, build an interactive Streamlit dashboard that includes a Backtest Leaderboard, Model Deep Dive, Bracket Visualizer, and Pool Scorer pages, and also support tournament simulation via analytical and Monte Carlo methods.
python streamlit kaggle machine-learning ncaa evaluator eda sports-analytics pytest
Generated by gemma4:latest
Catalog Information
This project is an evaluator tool for self-assessing NCAA March Mania Kaggle Competition models.
Description
The cz_conventional_commits project is a Python-based tool designed to evaluate and improve the performance of NCAA March Mania Kaggle Competition models. It provides a framework for model evaluation, allowing users to assess their models' strengths and weaknesses. The tool can be used by data scientists and machine learning enthusiasts to refine their models and achieve better results in the competition.
الوصف
هذا المشروع هو أداة تقييم لتقدير أداء نماذج NCAA March Mania Kaggle Competition. يعد الأداة من أدوات البرمجة الموجودة في لغة بايثون، وتقدم إطارًا للتقويم والتحليل، مما يسمح للمستخدمين بتقدير قوة نموذجهم وضع حدائق على نقاط الضعف. يمكن استخدام الأداة من قبل المهندسين البيانيين والمهندسين الآليين لتعزيز أداء نماذجهم وتحقيق نتائج أفضل في المسابقة.
Novelty
5/10Tags
model-evaluation ncaa-march-mania kaggle-competition machine-learning data-science
Technologies
numpy pandas plotly pydantic scikit-learn streamlit typer
Claude Models
claude-opus-4.6 claude-sonnet-4.6 claude-sonnet-4.5
Quality Score
B+
88.8/100
Structure
89
Code Quality
89
Documentation
90
Testing
85
Practices
83
Security
100
Dependencies
90
Strengths
- CI/CD pipeline configured (github_actions)
- Good test coverage (103% test-to-source ratio)
- Code linting configured (ruff (possible))
- Consistent naming conventions (snake_case)
- Good security practices \u2014 no major issues detected
- Properly licensed project
Weaknesses
- 602 duplicate lines detected \u2014 consider DRY refactoring
- 1 'god files' with >500 LOC need decomposition
Security & Health
6.6h
Tech Debt (A)
Medium
DORA Rating
A
OWASP (100%)
Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/
PASS
Quality Gate
A
Risk (0)
GPL-3.0
License
3.2%
Duplication
Languages
Frameworks
pytest
Symbols
variable185
method177
function138
constant83
class65
property8
protocol2
Concepts (17)
| Category | Name | Description | Confidence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Provenance: Repobility (https://repobility.com) — every score reproducible from /scan/ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| design_pattern | Repository | Found repository-named files | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| arch_layer | testing | Detected testing layer | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| arch_layer | presentation | Detected presentation layer | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| arch_layer | api | Detected api layer | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| arch_layer | business_logic | Detected business_logic layer | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| arch_layer | data_access | Detected data_access layer | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| arch_layer | infrastructure | Detected infrastructure layer | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| design_pattern | Strategy | Found strategy/policy-named files | 60% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | Search | Detected from 46 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | Testing | Detected from 318 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | User Management | Detected from 8 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | Analytics | Detected from 51 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | Authentication | Detected from 15 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | Configuration | Detected from 46 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | Database | Detected from 40 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | Logging | Detected from 12 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business_logic | File Management | Detected from 6 related files | 50% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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BinComp Dependency Hardening
All packages →12 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Ninvoke3.0.3 · 0 gadgets · risk 0.0Njoblib1.5.3 · 0 gadgets · risk 0.0Nnetworkx3.6.1 · 0 gadgets · risk 0.0Fnumpy2.4.4 · 6,596 gadgets · risk 0.0Fpandas3.0.2 · 6,381 gadgets · risk 0.0Nplotly6.7.0 · 0 gadgets · risk 0.0Fpyarrow23.0.1 · 8,505 gadgets · risk 0.0Npydantic2.12.5 · 0 gadgets · risk 0.0Frapidfuzz3.14.5 · 3,370 gadgets · risk 0.0Nrich14.3.4 · 0 gadgets · risk 0.0Ntqdm4.67.3 · 0 gadgets · risk 0.0Ntyper0.24.1 · 0 gadgets · risk 0.0