<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Real-Time on Murat Eksi</title><link>https://murateksi.com/tags/real-time/</link><description>Recent content in Real-Time on Murat Eksi</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 20 Nov 2023 10:00:00 +0100</lastBuildDate><atom:link href="https://murateksi.com/tags/real-time/index.xml" rel="self" type="application/rss+xml"/><item><title>Real-time ML for the Bundesliga</title><link>https://murateksi.com/case-studies/bundesliga-real-time-ml/</link><pubDate>Mon, 20 Nov 2023 10:00:00 +0100</pubDate><guid>https://murateksi.com/case-studies/bundesliga-real-time-ml/</guid><description>Context The Deutsche Fußball Liga (DFL), which operates the Bundesliga and 2. Bundesliga, runs a digital products group called DFL Digital Sports. They license real-time match data and insights to broadcasters, clubs, and betting partners worldwide.
They wanted to add machine-learned match signals, like expected goals, shot quality, pressing intensity, to the live data feed. The requirement was sub-two-second latency from event on the pitch to signal on the broadcast graphic.</description></item></channel></rss>