Seed Distributions for March Madness 2019: A Tool for Bracketologists

Round of 64 Upsets

In 29 of the past 34 tournaments (1985 through 2018), one or more teams seeded 13, 14 or 15 have won a game in the Round of 64. Our research on causal inference using observational data ([1],[2]) has been adapted to look at key statistics that may predict upsets for these seeds. From 2003 through 2018, we used the Balance Optimization Subset Selection model (BOSS) to select two teams each year. Of the resulting 32 teams selected (out of a possible 192 teams that could have been selected), 11 ended up being upsets. During this time period, there were a total of 25 upsets. Below is a table, constructed using the BOSS model, which contains the two teams selected each years (from 2003 to 2018) that share the characteristics of previous upsets. We also report the actual upsets that occurred during this time period. Note that in 2018, No. 16 UMBC upset No. 1 Virginia. However, our method does not focus on No, 16 upsets.

For 2019, the BOSS model picked St.Louis (13) over Virginia Tech (4) and Abilene Christian (15) over Kentucky (2). Given that the model tends to pick No. 13 and No. 14 teams for upsets, this is the first time since 2012 a No. 15 was selected as a long shot pick.

Year Upsets Chosen by BOSS Actual Upsets
2019 (13) St. Louis, (15) Abilene Christian TBD
2018 (13)Buffalo, (14)Wright State (13)Buffalo, (13)Marshall
2017 (13)Vermont, (14)New Mexico State None
2016 (13)Iona, (14)Buffalo (13)Hawaii, (14)Stephen F. Austin, (15)Middle Tennesse State
2015 (14)Georgia State, (14)UAB (14)Georgia State, (14)UAB
2014 (13)New Mexico State, (13)Delaware (14)Mercer
2013 (13)Lasalle, (14)Davidson (13)Lasalle, (14)Harvard, (15)FGCU
2012 (14)Belmont, (15)Lehigh (13)Ohio, (15)Lehigh, (15)Norfolk State
2011 (15)Akron, (15)LIU-Brooklyn (13)Morehead State
2010 (14)Ohio, (15)Morgan State (13)Murray State, (14)Ohio
2009 (13)Cleveland State, (13)Portland State (13)Cleveland State
2008 (13)Sienna, (13)Oral Roberts (13)Siena, (13)San Diego
2007 (13)Albany, (13)Holy Cross None
2006 (13)Bradley, (14)Xavier (13)Bradley, (14)Northwestern State
2005 (13)Vermont, (14)Niagara (13)Vermont, (14)Bucknell
2004 (13)UI-Chicago, (13)Texas - El Paso None
2003 (13)Tulsa, (14)Troy (13)Tulsa


[1] Nikolaev, A.G., Jacobson, S.H., Cho, W.K.T., Sauppe, J.J., Sewell, E.C., 2013 “Balance Optimization Subset Selection (BOSS): An Alternative Approach for Causal Inference with Observational Data,” Operations Research, 61(2), 398-412.

[2] Sauppe, J. J., S. H. Jacobson, and E. C. Sewell, 2014, “Complexity and Approximation Results for the Balance Optimization Subset Selection Model for Causal Inference in Observational Studies,” INFORMS Journal on Computing, 26(3), 547–566.

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