🛢️🚢 Strait of Hormuz Crisis 2026

How the US-Iran War Disrupted Global Oil Markets & Maritime Trade

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📌 Project Overview

On 28 February 2026, US and Israeli forces conducted strikes on Iranian military infrastructure. In response, Iran closed the Strait of Hormuz — the world's most critical oil chokepoint — disrupting approximately 20% of global oil supply.

Within days, Brent crude surged from ~$77 to over $104/barrel, sending shockwaves through fuel prices across 14 countries and threatening the stability of global maritime trade.

This project investigates three interconnected research questions using data science, machine learning and geopolitical analysis:

#	Research Question	Approach
1	🛢️ How severe was the oil price shock?	Time series analysis of daily Brent & WTI prices
2	🌍 Which countries were hit hardest?	Country-level vulnerability & economic impact analysis
3	🚢 What does this mean for global sea trade?	Historical correlation + 3-scenario forecasting

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🔑 Key Findings

Finding	Result
Brent crude price surge	+35.4% ($76.97 → $104.25/barrel)
Strait of Hormuz status	Closed/Restricted for 6 of 16 tracked trading days
Hardest hit country (fuel)	Pakistan (+20.7% retail price increase)
Worst GDP contraction	Iran (-8.0%) — despite being an oil producer
Highest maritime risk	South Korea (57.5/100) and China (54.4/100)
ML model accuracy	88.9% (Gradient Boosting, StratifiedKFold CV)
Key ML insight	GDP impact (81.1%) dominates vulnerability — not oil import dependency
Base case trade forecast	-5.5% global sea trade volume decline in 2026

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📊 Key Findings Gallery

🛢️ Oil Price Shock

🌍 Country Level Impact

📅 War Timeline

🚢 Sea Trade Historical Patterns

🔗 Correlation Analysis

🎯 Composite Risk Scores

📈 2026 Forecast Scenarios

🤖 ML Model — Feature Importance

📋 Intelligence Report

🔑 Key Findings Summary

💡 Conclusions

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🏗️ Project Structure

Strait-of-Hormuz-Crisis-2026/
│
├── 📓 Global_Oil_Maritime_Trade_Analysis.ipynb  ← Main notebook
├── 📋 README.md                                  ← This file
└── 📁 key_findings/                              ← All chart outputs
    ├── chart_01_oil_price_shock.png
    ├── chart_02_country_impact.png
    ├── chart_03_war_timeline.png
    ├── chart_04_sea_trade_patterns.png
    ├── chart_05_correlation.png
    ├── chart_06_risk_scores.png
    ├── chart_07_forecast.png
    ├── chart_08_model.png
    ├── chart_09_intelligence_report.png
    ├── chart_10_key_findings.png
    └── chart_11_conclusions.png

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📦 Datasets

Dataset	Source	Coverage
Global Petrol Prices — US-Iran War 2026	Kaggle (zkskhurram)	14 countries, Feb–Mar 2026
Volume of Goods Transported by Sea	Kaggle (fareselgohary003)	210 countries, 2000–2022

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🛠️ Tech Stack

Languages & Environment

Data & Analysis

Machine Learning

Visualisation

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📓 Notebook Structure

Phase	Description
🔧 Phase 0	Setup & Configuration
📦 Phase 1	Data Loading & Validation
🔍 Phase 2	Exploratory Data Analysis (4 sub-sections)
🔗 Phase 3	Combined Analysis & Risk Scoring
🤖 Phase 4	Forecasting & ML Modelling
📊 Phase 5	Final Intelligence Report
💡 Phase 6	Conclusions & Insights

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🤖 Models Used

Model	CV Accuracy	Notes
Gradient Boosting	88.9% ✅	Selected as best model
Random Forest	70.0%	Strong but lower CV score
Logistic Regression	Baseline	Lower performance

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⚠️ Disclaimer

This project is produced for educational and portfolio purposes only.
It does not constitute financial, investment, or geopolitical advice.
All data sourced from publicly available datasets on Kaggle and the World Bank.

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👩🏾‍💻 Author

Lindiwe Songelwa Data Scientist · Developer · Insight Creator 📍 Gauteng, South Africa 🇿🇦

Platform	Link
💼 LinkedIn	linkedin.com/in/lindiwe-songelwa
🐙 GitHub	github.com/Lindiwe-22
🏅 Credly	credly.com/users/samnkelisiwe-lindiwe-songelwa
📓 Kaggle	kaggle.com/lindiwe22

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© 2026 Lindiwe Songelwa · All rights reserved
Reproduction or redistribution without written permission is prohibited.