WC2026 Soccer Predictor

AI-powered 2026 FIFA World Cup prediction engine. Built entirely on Zerve AI — from 964 historical matches to 10,000 Monte Carlo simulations. France leads at 11%. Try it live!

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WC2026 Soccer Predictor — Can 92 Years of Data Predict the 2026 World Cup?

What question did I ask?

Can I use 92 years of FIFA World Cup match data to predict who will win in 2026 — built entirely inside Zerve AI, from raw data to deployed web app and live API?

What did I build?

A 5-stage AI pipeline built entirely on Zerve:

Stage 1 — Data: Cleaned 964 WC matches (1930–2022). Fixed 18 country names. Used only 90-minute scores — penalty luck shouldn't define strength.

Stage 2 — Elo Ratings: Built 3 versions of the Elo system (used by FIFA since 2018). Basic Elo ranked Morocco #29 despite being FIFA #8 and reaching the 2022 Semi Finals. Fix: blend Elo with live FIFA rankings (60/40). Morocco jumped to #12 — proving historical data alone isn't enough.

Stage 3 — ML Model: Trained a Gradient Boosted classifier on 1930–2018. Blind test on 2022: 42% accuracy vs 33% random — a meaningful +8.85% improvement.

Stage 4 — 10,000 Simulations: Monte Carlo simulation using the official 2026 group draw. France leads at 11%, Argentina 8.99%, Saudi Arabia at just 0.30%.

Stage 5 — Ship It: Created a live prediction API built on Zerve AI, and a Streamlit app on Zerve and deployed a  HTML web app,— all from the same canvas.

Why does it matter?

This project proved Zerve handles the entire data science lifecycle — ingestion, modelling, iteration, deployment, and API — without switching tools. When Italy failed to qualify on April 1, 2026, I updated all 48 teams in real time inside Zerve. That adaptability is what separates AI-native pipelines from traditional workflows.

Built by Vee (Srividya Narayanan) | Powered by Zerve AI

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