Standings are aimed to be released by the end of every Tuesday.
In the 2019 Season, we have 30 technical upsets in 169 ranked matches (82.25% success rate) across 23 events. Additionally, there have been four JV matches entered into the Records.
The Gonzalez System is a computer ranking model similar to Elo and is a rating exchange system based on research performed by World Rugby. It has been adapted by the NCDA to the demands of College Dodgeball, but can be tuned and customized endlessly to incorporate accurate data. It has been used to help determine seeds for the Nationals bracket since Nationals 2014, and was used exclusively for the Nationals 2017 and 2018 bracket.
Technical Upset Spotlight
A technical upset in the Gonzalez System is when a lower rated team defeats a higher rated team. The overall success rate of the system is currently 80.41% based on 336 technical upsets in 1715 ranked matches played since 2010-09-25.
There were no technical upsets since the last standings update…jk.
MSU def Towson 3-2 (OT)
47.507 def 52.993, exchanging 0.774
We had a bevy of overtime results this past weekend, two of which resulted in upsets. The Spartans got a signature win they were desperately looking for over second ranked Towson. Overall, this ranks in the 91st percentile of overtime upsets based on the rating gap, and ranks as the #8 overall overtime upset all time.
Ohio def VCU 4-0
43.939 def 45.938, exchanging 1.200
The Bobcats picked up their first ever win over VCU in dominating fashion. Overall, the upset falls in the 49th percentile and ranks 171st all time.
UK def OSU 2-1 (OT)
39.620 def 41.071, exchanging 0.573
Our other overtime upset came when Kentucky defeated Ohio State on day one of WAR III. Kentucky’s upset falls in the 37th percentile, and ranks 38th in overtime upsets all time.
Net Rating Changes
To (hopefully) no one’s surprise, MSU was able to survive WAR III and walk away with a good amount of points. Their fellow in-state rivals CMU and SVSU also walked away with a positive net gain from the event. MSU’s three wins brought them up to 7-6 on the year, and pushed them up to #5 in the nation (see below). In total, all Michigan teams had a net gain of 2.785 points which was the most out of the other region teams.
Towson took on what was arguably the most difficult schedule of the weekend and fared well. With a solid 0.816 point gain, they provided more of a cushion between them and JMU, and helped narrow the gap against #1 GVSU. Fellow East Coast schools VCU and PSU did not garner the same bump as Towson, as both schools received a net loss following defeats to Ohio.
As for the Ohio region schools, teams either had marginal gains or fairly significant drops. Miami, BGSU, CSU, and Akron all had positive net gains while Ohio, Kent, and OSU saw their rating totals drop. A 2-1 weekend for UK helped give them a slight boost to jump up to #16 overall, while BSU dropped one spot as a result of their losses.
|↑ from 7||5||48.281||MSU|
|↓ from 5||6||48.119||CMU|
|↓ from 6||7||47.263||Miami|
|↑ from 10||9||44.738||VCU|
|↓ from 9||10||43.883||Kent|
|↑ from 15||14||40.679||UNG|
|↑ from 16||15||40.622†||UNT|
|↑ from 19||16||40.534||UK|
|↑ from 20||19||39.767||WKU|
|↓ from 14||20||39.625||OSU|
|↑ from 29||27||37.547||CSU|
|↓ from 27||28||37.466||UMD|
|↓ from 28||29||37.442†||DePaul|
|↑ from 37||36||33.203||BW|
|↓ from 36||37||32.413||BSU|
Movement as of 2019-01-29
* denotes a provisional rating (< 6 matches)
† denotes a team that has not played three games this season, the required minimum games needed to qualify for Nationals.
Strength of Schedule Spotlight
Strength of Schedule is typically used as a measure to determine what level of competition each team is facing relative to their peers. The way to read it is fairly simple, the higher the average opponent rating, the tougher your schedule.
|Rank||Team||Avg. Opp. Rating|
See the Resource Center for more documentation.
Records, Master Spreadsheet: 2005-Present
Records, Individual Docs: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019
Systems: Gonzalez Current
Spec Document: Gonzalez System Spec Doc
Prediction Calculation: Gonzalez Predictor