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AntTech
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.

AIGraph Neural NetworkSports 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
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?
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 19, 2022 · Artificial Intelligence

How AI Transforms Football Video Analysis: Detection, Tracking, and Event Recognition

This article explores how artificial intelligence techniques such as deep learning, object detection, multi‑object tracking, and coordinate projection are applied to football video analysis to automatically detect the ball and players, map their positions onto the field, and recognize key events like shots and goals.

AIComputer VisionSports Analytics
0 likes · 16 min read
How AI Transforms Football Video Analysis: Detection, Tracking, and Event Recognition
Tencent Cloud Developer
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 StrategyData ScienceRandom Forest
0 likes · 21 min read
Football Match Prediction Using Machine Learning and Betting Strategy Analysis
Efficient Ops
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 AnalyticsWorld Cup
0 likes · 12 min read
Can Python Predict the 2018 World Cup Champion? A Data‑Driven Analysis