Otherpublic

FIFA World Cup USA vs Paraguay ML Prediction Model

by Quant Kavin·June 8, 2026·1 file

About this project

Pulls recent international match history for USA and Paraguay via the football-data.org free API, engineers rolling form features (win rate, goals for/against, goal difference) over an 8-game window, and trains a logistic regression to output head-to-head win probabilities for their June 12 World Cup 2026 Group D opener. Includes feature coefficient analysis and a rolling form comparison chart.

#machine-learning#fifa-world-cup

Files

1 File

Sign in to view this file

Viewing files on ForgeHub is free. Sign in or create an account to open the interactive viewer and download files.

Sign in to view

Activity

Description updatedJun 8, 2026
Added usa_vs_paraguay_win_prob.ipynbJun 8, 2026
Project createdJun 8, 2026

Comments

Sign in to comment.
Loading comments...

Related Projects

FIFA Cup France vs Senegal ML Prediction Model

Multi-feature logistic regression with competition importance weighting (World Cup and tournament matches weighted up to 3× higher than friendlies) and exponential recency decay applied to match history pulled from football-data.org. Wraps the model in Platt scaling via CalibratedClassifierCV for better-calibrated probabilities, pulls squad size from the teams endpoint as a depth feature, and runs a sensitivity analysis sweeping the WC weight multiplier across 7 values. Outputs form trend charts, competition mix breakdown, aggregate stat comparisons, and a sensitivity curve for their June 16 World Cup 2026 Group I matchup.

1 file
Quant Kavin

Quant Kavin

Jun 8, 2026

FIFA World Cup Brazil vs Morocco Prediction Model

Fetches full match history for Brazil and Morocco from football-data.org and applies exponential time-decay weighting to prioritize recent form. Builds Poisson attack/defense strength ratings to generate a scoreline probability grid, trains a logistic regression on recency-weighted differential features, then blends both models into a final win/draw/loss probability for their June 13 World Cup 2026 Group C clash. Outputs a scoreline heatmap, blended probability bars, and expected goals comparison.

Other1 file
Quant Kavin

Quant Kavin

Jun 8, 2026

Apple WWDC Price Prediction Options Project

AAPL WWDC 2026 — Event-Day Volatility Arbitrage A quantitative options strategy built around Apple's annual WWDC keynote (June 8, 2026). The core idea is implied vs realised volatility arbitrage — options markets have historically overpriced AAPL's expected 1-day move on keynote day, creating a structural edge for volatility sellers. By collecting 11 years of WWDC event-day returns (2015–2025), comparing them against the ATM straddle implied move, and backtesting a short straddle strategy, we quantify that edge and size it using the Kelly Criterion. Quant concepts used: implied volatility, realised volatility, volatility risk premium, ATM straddle pricing (call + put ÷ spot), 1-day IV derivation (annual IV ÷ √252), Shapiro-Wilk normality testing, skewness and kurtosis analysis, Kelly Criterion position sizing (½ Kelly for safety), short straddle and iron condor payoff mechanics, Sharpe ratio, and max drawdown. Libraries: yfinance (data), pandas + numpy (analysis), scipy.stats (distribution testing), matplotlib + matplotlib.animation (static and animated charts), pillow + ffmpeg (GIF and MP4 export).

Other1 file
Quant Kavin

Quant Kavin

Jun 7, 2026