#310 Stevens Tech (10-14)

avg: 678.83  •  sd: 67.92  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
319 Edinboro Win 11-7 1121.05 Feb 24th Bring The Huckus 2024
256 Salisbury Loss 8-11 554.18 Feb 24th Bring The Huckus 2024
245 Skidmore Win 9-5 1507.13 Feb 24th Bring The Huckus 2024
382 Lehigh-B Win 8-7 412.63 Feb 24th Bring The Huckus 2024
108 Vermont-B Loss 7-15 875.03 Feb 25th Bring The Huckus 2024
267 SUNY-Geneseo Win 14-12 1092.44 Feb 25th Bring The Huckus 2024
343 Connecticut-B Win 7-6 674.33 Mar 2nd Philly Special 2024
272 Rowan Loss 5-7 528.64 Mar 2nd Philly Special 2024
259 Brandeis Loss 7-12 394.42 Mar 3rd Philly Special 2024
130 Penn State-B** Loss 3-13 779.42 Ignored Mar 3rd Philly Special 2024
272 Rowan Win 12-8 1297.94 Mar 3rd Philly Special 2024
240 SUNY-Albany Loss 9-11 738.58 Mar 3rd Philly Special 2024
319 Edinboro Loss 4-11 54.16 Mar 23rd Garden State 2024
234 Haverford Loss 6-7 874.52 Mar 23rd Garden State 2024
272 Rowan Win 8-7 981.78 Mar 24th Garden State 2024
407 West Chester-B Win 7-3 467.56 Mar 24th Garden State 2024
382 Lehigh-B Loss 10-11 162.63 Mar 24th Garden State 2024
187 College of New Jersey Loss 5-15 563.42 Apr 13th Metro NY D III Mens Conferences 2024
- New York Tech** Win 15-4 412.93 Ignored Apr 13th Metro NY D III Mens Conferences 2024
- Manhattan Win 12-7 678.82 Apr 13th Metro NY D III Mens Conferences 2024
139 Army Loss 7-15 748.35 Apr 27th Metro East D III College Mens Regionals 2024
213 Ithaca Loss 8-15 510.83 Apr 27th Metro East D III College Mens Regionals 2024
181 SUNY-Cortland Loss 10-17 664.15 Apr 27th Metro East D III College Mens Regionals 2024
205 Vassar Loss 5-15 505.54 Apr 28th Metro East D III College Mens Regionals 2024
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
What's the algorithm again?
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
Is there a longer explanation of all this?
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)