https://hackerpaper.kaipfister.de/p/1109.2825/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=38008703urn:hackerpapers:mention:1109.2825:38008703Wed, 25 Oct 2023 03:07:56 GMT<p>Or like modeling basketball games as random walks? https://arxiv.org/abs/1109.2825</p><p><a href="https://hackerpaper.kaipfister.de/p/1109.2825/">Paper and discussion history</a>. A mention is not an endorsement.</p>physics.data-anhttps://news.ycombinator.com/item?id=12867220urn:hackerpapers:mention:1109.2825:12867220Thu, 03 Nov 2016 19:36:20 GMT<p>Fantastic comment! In fact, it seems that sports games, or at least NBA games, can be described accurately and consistently using (slightly modified) random walks. Put differently: Outcomes are indeed random and there&#x27;s not much machine learning you can do here. Source: https://arxiv.org/abs/1109.2825 And here&#x27;s a slightly more exciting description of a talk one of the authors gave on that topic at UMass Amherst last year: https://www.physics.umass.edu/seminars/statistics-of-basketb... EDIT: I was too stupid to realize that the paper linked above actually supports the parent&#x27;s opinion, i.e.…</p><p><a href="https://hackerpaper.kaipfister.de/p/1109.2825/">Paper and discussion history</a>. A mention is not an endorsement.</p>physics.data-an