AWS Machine Learning Blog

Category: Sports

Predicting soccer goals in near real time using computer vision

In a soccer game, fans get excited seeing a player sprint down the sideline during a counterattack or when a team is controlling the ball in the 18-yard box because those actions could lead to goals. However, it is difficult for human eyes to fully capture such fast movements, let alone predict goals. With machine […]

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Predicting qualification ranking based on practice session performance for Formula 1 Grand Prix

If you’re a Formula 1 (F1) fan, have you ever wondered why F1 teams have very different performances between qualifying and practice sessions? Why do they have multiple practice sessions in the first place? Can practice session results actually tell something about the upcoming qualifying race? In this post, we answer these questions and more. […]

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Using log analysis to drive experiments and win the AWS DeepRacer F1 ProAm Race

This is a guest post by Ray Goh, a tech executive at DBS Bank.  AWS DeepRacer is an autonomous 1/18th scale race car powered by reinforcement learning, and the AWS DeepRacer League is the world’s first global autonomous racing league. It’s a fun and easy way to get started with machine learning (ML), regardless of […]

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Predicting Defender Trajectories in NFL’s Next Gen Stats

NFL’s Next Gen Stats (NGS) powered by AWS accurately captures player and ball data in real time for every play and every NFL game—over 300 million data points per season—through the extensive use of sensors in players’ pads and the ball. With this rich set of tracking data, NGS uses AWS machine learning (ML) technology […]

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Football tracking in the NFL with Amazon SageMaker

With the 2020 football season kicking off, Amazon Web Services (AWS) is continuing its work with the National Football League (NFL) on several ongoing game-changing initiatives. Specifically, the NFL and AWS are teaming up to develop state-of-the-art cloud technology using machine learning (ML) aimed at aiding the officiating process through real-time football detection. As a […]

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Gaining insights into winning football strategies using machine learning

University of Illinois, Urbana Champaign (UIUC) has partnered with the Amazon Machine Learning Solutions Lab to help UIUC football coaches prepare for games more efficiently and improve their odds of winning. Previously, coaches prepared for games by creating a game planning sheet that only featured types of plays for a certain down and distance, and […]

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The fastest driver in Formula 1

This blog post was co-authored, and includes an introduction, by Rob Smedley, Director of Data Systems at Formula 1 Formula 1 (F1) racing is the most complex sport in the world. It is the blended perfection of human and machine that create the winning formula. It is this blend that makes F1 racing, or more […]

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Increasing engagement with personalized online sports content

This is a guest post by Mark Wood at Pulselive. In their own words, “Pulselive, based out of the UK, is the proud digital partner to some of the biggest names in sports.” At Pulselive, we create experiences sports fans can’t live without; whether that’s the official Cricket World Cup website or the English Premier […]

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Accelerating innovation: How serverless machine learning on AWS powers F1 Insights

FORMULA 1 (F1) turns 70 years old in 2020 and is one of the few sports that combines real-time skill with engineering and technical prowess. Technology has always played a central role in F1; where the evolution of the rules and tools is built into the DNA of F1. This keeps fans engaged and drivers […]

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Delivering real-time racing analytics using machine learning

AWS DeepRacer is a fun and easy way for developers with no prior experience to get started with machine learning (ML). At the end of the 2019 season, the AWS DeepRacer League engaged the Amazon ML Solutions Lab to develop a new sports analytics feature for the AWS DeepRacer Championship Cup at re:Invent 2019. The […]

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