tadiwaben.github.io

📁 Featured Projects

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⚽ The ZimPSL Ultimate Entertainers: Sports Analytics & Web Scraping

A sports analytics pipeline engineered to look beyond standard points tables and mathematically measure spectator value (“entertainment index”) across 8 seasons of the Zimbabwe Premier Soccer League (ZimPSL).

📊 Project Highlights

• Automated Data Scraping: Built custom Python extractors parsing 101 team-season records from historical league tables (2017–2024).
• Feature Engineering: Standardized goal rates, match volatility, and defensive risk metrics into a unified Chaos & Entertainment Index.
• Tactical Profiling: Mapped team playstyles into tactical quadrant matrices to isolate high-stakes, entertaining sides from low-volatility defensive teams.

🖼️ Visual Insights Preview

🛠️ Tech Stack

Python • BeautifulSoup • Pandas • NumPy • Matplotlib / Seaborn

📊 Read Full Analysis Report

💻 View Scraper Code

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ZimAuto Valuation Engine

🚗 ZimAuto: End-to-End Car Valuation & Negotiation Engine

An institutional machine learning application designed to resolve pricing opacity and asymmetry in the Zimbabwean secondary automobile market. The system automatically scrapes marketplace listings, models non-linear vehicle depreciation with target log scaling, and serves interactive bargaining guidance.

📊 Performance Highlights

• Variance Explained ($R^2$): 0.790 (~79% of cross-market price variance explained)
• Predictive Accuracy (MAE): ~$5,112 USD average baseline dollar error across all vehicle segments
• Dataset Scope: 3,000+ cleaned vehicle records scraped across regional classifieds (ZimAuto, ZimClassifieds)
• Statistical Governance: Real-time residual Z-score filtering ($\pm3\sigma$) to catch data anomalies and structural risks

🛠️ Key Technologies

Python • BeautifulSoup • XGBoost • Optuna • Scikit-Learn • Gradio • Render 👉 Read Full Analysis | Live Demo