{"id":7313,"date":"2018-03-14T15:34:15","date_gmt":"2018-03-14T19:34:15","guid":{"rendered":"https:\/\/www.furman.edu\/news\/2018\/03\/20\/mathematics-and-march-madness\/"},"modified":"2022-11-06T18:56:44","modified_gmt":"2022-11-06T23:56:44","slug":"mathematics-and-march-madness","status":"publish","type":"post","link":"https:\/\/www.furman.edu\/news\/mathematics-and-march-madness\/","title":{"rendered":"Mathematics and March Madness"},"content":{"rendered":"

Research by professors included in New York Times story on Virginia loss\u00a0<\/strong><\/a><\/p>\n

Furman mathematics professor John Harris \u201991 isn\u2019t telling you to pick Pennsylvania to beat Kansas in the NCAA tournament. A 16-seed has never defeated a top seed, after all, so that would be crazy.<\/p>\n

He\u2019s just saying \u2026 think about it.<\/p>\n

\u201cIf someone did want to pick a 16 over a 1, this might be one to consider,\u201d Harris says.<\/p>\n

Harris doesn\u2019t have insider knowledge about either team, and he\u2019d be the first one to tell you he\u2019s not a college basketball expert. You probably should still think about it.<\/p>\n

That\u2019s because Harris and math department colleagues Kevin Hutson and Liz Bouzarth have done more pondering about how to predict March Madness upsets than anybody you know. For five years now, the three have collaborated with ESPN senior writer Peter Keating, whose \u201cNumbers\u201d column covers the world of statistics and analytics in sports, to create some of the world\u2019s most advanced metrics for predicting tourney upsets.<\/p>\n

The story the numbers tell this year is one of potential peril for the Jayhawks on Thursday afternoon when the action gets under way. Emphasis on potential.<\/p>\n

\u201cWe noticed something interesting about the Kansas-Penn game,\u201d Harris says. \u201cOur model says there is only a four-percent chance of an upset, so it\u2019s very unlikely, but we did notice that the matchup itself is very similar to the Duke-Lehigh matchup from 2012.\u201d<\/p>\n

That year, Lehigh stunned Duke, 75-70, to become one of only eight No. 15 seeds to ever beat a No. 2 seed. Four percent isn\u2019t much of a probability, but it\u2019s a probability. And the nature of probability says a 16 will beat a 1 eventually.<\/p>\n

If you\u2019re looking for more realistic upset options to impress your office mates, the professors recommend focusing on a couple of matchups between 11 and 6 seeds. According to their calculations, San Diego State has a 34-percent chance of defeating sixth-seeded Houston, while they give Loyola a one-in-three shot at taking down Miami.<\/p>\n

Further into the bracket, should Florida State and Xavier both advance to the second round, the analysis gives the Seminoles, seeded ninth, a healthy 42-percent chance to knock off the No. 1 seed Musketeers. Either winner of the Arkansas-Butler first-round game has a decent chance of knocking off second-seeded Purdue, with the No. 7 Razorbacks actually being favored.<\/p>\n

ESPN Insider\u2019s \u201cGiant Killers\u201d project predicts NCAA tournament upsets as defined by one team being seeded at least five spots higher than another, and prior to the 2014 tourney, Hutson, Bouzarth and Harris revolutionized its approach when they developed something that came to be called \u201ccluster analysis.\u201d In their cluster analysis, \u201cgiants\u201d \u2013 the higher seeds \u2013 are lumped into four broad families based on their style of play, as are the \u201ckillers.\u201d<\/p>\n

Past results show trends in certain matchups between families, and as the data builds on itself the ability to predict future outcomes based on past performances theoretically becomes more accurate.<\/p>\n

\u201cThe Arkansas-Purdue matchup in particular is interesting, because in that killer\/giant cluster matchup the killer wins 55 percent of the time,\u201d Hutson says.<\/p>\n

Though their work won\u2019t be used in Giant Killers in 2018, the three are still working with the network and ran data for this edition of the tournament.<\/p>\n

\u201cOne of the things we often tell people to emphasize is we\u2019re not necessarily picking the upset; we\u2019re giving a probability we think the upset will happen,\u201d Hutson says. \u201cTraditionally upsets occur at about a 22-percent rate, so anything that is significantly above that we have as being more probable of an upset.\u201d<\/p>\n

The professors have more than a little history of success to lend credence to their methods. Last year, they gave No. 11 Xavier a 51-percent chance to upset No. 6 Maryland, which the Musketeers did easily. In 2016, their top four most likely first-round upsets all ended up being just that.<\/p>\n

Though their computers look at every possible giant killer matchup through the tournament (\u201cWe make no assumptions. Sixteen seeds are allowed to have hypothetical games against eight and nine seeds,\u201d Hutson says), the pickings were a bit slimmer this year for whatever reason and few potential upsets stand out compared to years past.<\/p>\n

That\u2019s OK. The trio, all college hoops fans, are ready to sit back and enjoy the games instead of analyzing them. Probability indicates, however, that Bouzarth, a North Carolina fan, won\u2019t be enjoying it quite as much this time around.<\/p>\n

\u201cWhen I send out the bracket (pool) e-mail to the department, I always say may the best bracket and the best team win. But last year, my bracket won and my team won,\u201d she says. \u201cAnd I\u2019m a Philadelphia Eagles fan. I am just riding all sorts of sports highs, but I\u2019m kind of nervous it\u2019s all going to come down at some point.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

Research by professors included in New York Times story on Virginia loss\u00a0 Furman mathematics professor John Harris \u201991 isn\u2019t telling you to pick Pennsylvania to beat Kansas in the NCAA […]<\/p>\n","protected":false},"author":265,"featured_media":9244,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[15,50,30],"tags":[],"class_list":["post-7313","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-academic-department-page","category-mathematics","category-top-stories"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/posts\/7313","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/users\/265"}],"replies":[{"embeddable":true,"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/comments?post=7313"}],"version-history":[{"count":0,"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/posts\/7313\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/media\/9244"}],"wp:attachment":[{"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/media?parent=7313"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/categories?post=7313"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.furman.edu\/news\/wp-json\/wp\/v2\/tags?post=7313"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}