¿Qué hace realmente emocionante a un partido de fútbol? Cuando hablamos de un gran partido solemos pensar inmediatamente en muchos goles. Sin embargo, en Sports Analytics la producción ofensiva puede analizarse desde una perspectiva mucho más amplia utilizando estadísticas avanzadas. En este proyecto desarrollé un Match Excitement Score (MES) , un índice que resume la actividad ofensiva de cada encuentro del Mundial FIFA 2026 mediante una combinación de métricas tradicionales y avanzadas. Todo el análisis fue realizado en Python utilizando Pandas y Matplotlib, compartiendo además el notebook completo para que cualquier persona pueda reproducir los resultados. ¿Cómo se construyó el Match Excitement Score? El índice integra seis variables ofensivas disponibles en el dataset: ⚽ Goles 📈 Expected Goals (xG) 🎯 Total de disparos 🥅 Disparos a puerta 🔥 Big Chances 📍 Toques dentro del área rival Cada variable fue estandarizada mediante Z-score y posteriormente ...

Which FIFA World Cup 2026 Match Should You Watch Again? After every FIFA World Cup, one question always comes up: Which matches are worth watching again? Instead of answering this question based on personal opinion, I decided to analyze every match from the FIFA World Cup 2026 using Python, Pandas and Matplotlib. The objective was simple: Find the matches with the most goals. Identify the strongest defensive performances. List every game that required extra time. Show every match decided by a penalty shootout. The result is a collection of custom visualizations generated entirely with Python using the FIFA World Cup 2026 dataset. ⚽ Highest Scoring Matches If you enjoy attacking football and goal-filled games, this ranking is the perfect place to start. Using the official match results, I ranked every match by the total number of goals scored by both teams. The visualization highlights the ten highest-scoring matches of the tournament. NOTE : Englan...

Can Data Measure Football Excitement? Ranking FIFA World Cup 2026 Matches with Python When fans remember a great football match, they usually think about unforgettable goals, dramatic comebacks and emotional moments. But from a Sports Analytics perspective, another question appears. Can we measure how exciting a football match was using only data? In this project I analyzed the FIFA World Cup 2026 using Python , Pandas and Matplotlib to create a simple metric called Excitement Score . Dataset The analysis uses the Football World Cup 2026 Dataset from Kaggle containing: Match events Expected Goals (xG) Possession Shots Shots on target Big Chances Player information Momentum Dataset: Football World Cup 2026 Dataset Building the Excitement Score Goals alone do not tell the whole story. I combined multiple offensive statistics into a simple metric. Excitement Score = Shots + (Big Chances × 2) + (Goals × 3) The weights are intentionally simple and ...