Sports Analytics

AntTech

Jun 20, 2024 · Artificial Intelligence

Predicting Football Match Outcomes with Graph Neural Networks and Large Language Models: The “Smart Guess Football” Project

During the 2024 European Championship, TuGraph engineers built an interactive system called “Smart Guess Football” that combines graph computing, graph neural networks, transformers and large language models to model player relationships and predict match outcomes, achieving up to 71% accuracy on limited test matches.

AILarge Language ModelSports Analytics

0 likes · 7 min read

Predicting Football Match Outcomes with Graph Neural Networks and Large Language Models: The “Smart Guess Football” Project

Model Perspective

Feb 24, 2024 · Fundamentals

Can You Predict Soccer Match Outcomes with a Simple Poisson Model?

This article presents a statistical approach to forecasting football match results by calculating league-wide average goals, deriving offensive and defensive indices for each of the 20 teams, adjusting for home‑field advantage, and applying the Poisson distribution to estimate score probabilities.

Poisson distributionSports Analyticsfootball prediction

0 likes · 9 min read

Can You Predict Soccer Match Outcomes with a Simple Poisson Model?

Tencent Cloud Developer

Dec 2, 2022 · Artificial Intelligence

Football Match Prediction Using Machine Learning and Betting Strategy Analysis

The study applies machine‑learning models—including logistic regression, SVM, random forest, deep neural networks and a DNN‑SVM ensemble—to 17‑dimensional team features and 51‑dimensional bookmaker odds, achieving up to 54.5% match‑outcome accuracy, proposing a profit‑condition betting strategy and extending the approach to stock‑price forecasting.

Betting StrategySVMSports Analytics

0 likes · 21 min read

Football Match Prediction Using Machine Learning and Betting Strategy Analysis

Model Perspective

Nov 24, 2022 · Fundamentals

Where Should You Shoot? Uncovering the Optimal Soccer Goal Positions with Geometry

This article models soccer shooting using simple geometric assumptions, divides the field into three zones, derives hyperbolic trajectories for optimal shooting points, introduces shooting‑equivalent lines, and shows that the best shooting spots are not always closest to the goal.

Sports Analyticsgeometrymathematical modeling

0 likes · 4 min read

Where Should You Shoot? Uncovering the Optimal Soccer Goal Positions with Geometry

Efficient Ops

Jun 21, 2018 · Fundamentals

Can Python Predict the 2018 World Cup Champion? A Data‑Driven Analysis

This article demonstrates how to use Python, pandas, and Jupyter Notebook to explore a comprehensive World Cup dataset, clean and enrich the data, visualize win and goal statistics for all teams, and finally predict the top three contenders for the 2018 tournament.

PythonSports AnalyticsVisualization

0 likes · 12 min read

Can Python Predict the 2018 World Cup Champion? A Data‑Driven Analysis

Qunar Tech Salon

Oct 25, 2015 · Big Data

Analyzing NBA Player Movement Data with Python: Extraction, Visualization, and Metrics

This article demonstrates how to retrieve NBA play‑by‑play movement data via the stats.nba.com API, transform it into a pandas DataFrame, enrich it with player names, visualize player trajectories on a basketball court, and compute travel distances, speeds and inter‑player distances using Python libraries.

Movement TrackingNBAPython

0 likes · 19 min read

Analyzing NBA Player Movement Data with Python: Extraction, Visualization, and Metrics