<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>FIFA World Cup 2026 | Marc Schalberger</title><link>https://mschalberger.github.io/tag/fifa-world-cup-2026/</link><atom:link href="https://mschalberger.github.io/tag/fifa-world-cup-2026/index.xml" rel="self" type="application/rss+xml"/><description>FIFA World Cup 2026</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Tue, 09 Jun 2026 00:00:00 +0000</lastBuildDate><image><url>https://mschalberger.github.io/media/icon_huea4c2c30a4f75ae13f649c1a215d5c7a_68535_512x512_fill_lanczos_center_3.png</url><title>FIFA World Cup 2026</title><link>https://mschalberger.github.io/tag/fifa-world-cup-2026/</link></image><item><title>Media Coverage of the FIFA World Cup 2026 Prediction Project</title><link>https://mschalberger.github.io/post/bz/</link><pubDate>Tue, 09 Jun 2026 00:00:00 +0000</pubDate><guid>https://mschalberger.github.io/post/bz/</guid><description>&lt;p>Our FIFA World Cup 2026 prediction work received extensive media coverage ahead of the tournament&amp;rsquo;s kick-off on June 11. The project was featured in several German news outlets, including &lt;strong>BZ Berlin&lt;/strong>, &lt;strong>Berliner Morgenpost&lt;/strong>, &lt;strong>BILD&lt;/strong>, &lt;strong>rbb24&lt;/strong>, and &lt;strong>Sportschau&lt;/strong>.&lt;/p>
&lt;h2 id="media-coverage">Media Coverage&lt;/h2>
&lt;ul>
&lt;li>&lt;strong>BZ Berlin&lt;/strong>: &lt;a href="https://www.bz-berlin.de/berlin/berliner-forscher-wissen-schon-wer-die-wm-gewinnt" target="_blank" rel="noopener">Berliner Forscher wissen schon, wer die WM gewinnt&lt;/a>&lt;/li>
&lt;li>&lt;strong>Berliner Morgenpost&lt;/strong>: &lt;a href="https://www.morgenpost.de/berlin/article412240283/berliner-forscher-haben-schon-errechnet-welches-team-die-wm-gewinnt.html" target="_blank" rel="noopener">Berliner Forscher haben schon errechnet, welches Team die WM gewinnt&lt;/a>&lt;/li>
&lt;li>&lt;strong>BILD&lt;/strong>: &lt;a href="https://www.bild.de/regional/berlin/fussball-wm-berliner-forscher-wissen-schon-wer-weltmeister-wird-6a282006751bf6a58a80921e" target="_blank" rel="noopener">Berliner Forscher wissen schon, wer Weltmeister wird&lt;/a>&lt;/li>
&lt;li>&lt;strong>rbb24&lt;/strong>: &lt;a href="https://www.rbb24.de/sport/beitrag/2026/06/interview-ulrich-schneider-wm-tippen-wetten-prognose-statistik-m.html" target="_blank" rel="noopener">Interview zur WM-Prognose und statistischen Modellierung&lt;/a>&lt;/li>
&lt;li>&lt;strong>Sportschau&lt;/strong>: &lt;a href="https://www.sportschau.de/regional/rbb/rbb-statistiker-zur-fussball-wm-wer-titelchancen-hat-und-wer-geheimfavorit-ist-100.html" target="_blank" rel="noopener">Statistiker zur Fußball-WM: Wer Titelchancen hat und wer Geheimfavorit ist&lt;/a>&lt;/li>
&lt;/ul>
&lt;p>The team at the &lt;strong>Freie Universität Berlin&lt;/strong> combined multiple statistical approaches and evaluated approximately &lt;strong>13,000 international matches since 2012&lt;/strong> to generate win probabilities for all 48 competing nations. The methodology integrates &lt;strong>Elo ratings&lt;/strong>, the &lt;strong>Dixon–Coles model&lt;/strong>, and machine-learning approaches including &lt;strong>random forests&lt;/strong>. These estimates feed into a large-scale Monte Carlo simulation that replays the entire tournament &lt;strong>100,000 times&lt;/strong>.&lt;/p>
&lt;p>Key model outputs for the 2026 World Cup:&lt;/p>
&lt;table>
&lt;thead>
&lt;tr>
&lt;th>Team&lt;/th>
&lt;th>Win Probability&lt;/th>
&lt;/tr>
&lt;/thead>
&lt;tbody>
&lt;tr>
&lt;td>🇦🇷 Argentina&lt;/td>
&lt;td>~14%&lt;/td>
&lt;/tr>
&lt;tr>
&lt;td>🇪🇸 Spain&lt;/td>
&lt;td>~13%&lt;/td>
&lt;/tr>
&lt;tr>
&lt;td>🏴 England&lt;/td>
&lt;td>~12%&lt;/td>
&lt;/tr>
&lt;tr>
&lt;td>🇩🇪 Germany&lt;/td>
&lt;td>~5.5%&lt;/td>
&lt;/tr>
&lt;/tbody>
&lt;/table>
&lt;p>Germany is projected to reach the Round of 32 with approximately &lt;strong>98% probability&lt;/strong> and is expected to score around &lt;strong>11 goals&lt;/strong> over the course of the tournament.&lt;/p>
&lt;p>Beyond reporting the tournament forecast itself, several outlets discussed the statistical methodology behind the predictions, the strengths and limitations of forecasting models in football, and how simulation-based approaches can be used to quantify uncertainty in major sporting events.&lt;/p>
&lt;p>👉 &lt;strong>Explore the full simulation and results here:&lt;/strong> &lt;a href="https://www.wiwiss.fu-berlin.de/wm2026" target="_blank" rel="noopener">https://www.wiwiss.fu-berlin.de/wm2026&lt;/a>&lt;/p></description></item></channel></rss>