New FRC Stat: aWAR

[Nathan Streeter]

First, I'd like to recognize Dan Niemitalo for being the one to create most of this spreadsheet for a statistic that he invented, called Performance Index. Here is where he introduces that: http://www.chiefdelphi.com/forums/sh...rmance+inde x. Thanks also go to Ed Law and Mark McLeod as all the raw data from this spreadsheet comes from their spreadsheets.

My goal for aWAR is to be a season-long statistic that accurately ranks all FRC teams based on all-around performance... It is primarily based off of the new standardized district point model, but also implements the tweaks mentioned in the bullets below (devised and implemented by Dan Niemitalo and I). aWAR stands for aggregate Wins Above Replacement and is based on the concept of WAR from baseball... Wins Above Replacement.

What is really unique about aWAR is that it is scaled to a useful range... Similar to the concept of a "Replacement-Level" found in WAR in baseball, 0 indicates a "replacement-level team" which we defined to be one that goes something like 5-7, is on the cusp of being picked in elims (hence replacement-level), and may or may not win an award. Based on this 0-point, it is then scaled so that the top teams usually get an aWAR of around 7 (12-0 record... 7 Wins Above Replacement). A team that has an aWAR of about 4 probably went about 9-3 at the regional/district level.

The changes made from the 2014 district point model include:
- Omission of the 1st and 2nd year team benefit. This is in no way because I dislike this element of the point system (I actually like it a lot!), but because it exists primarily to help younger teams get to the next level of competition. With aWAR I'm just trying to rank teams based on skill, this element would be counter-productive for that.
- Includes a weight for OPR (primarily to differentiate among top-tier teams... is: 16 * IndividualTeam'sEventOPR/MaxOPRofSeason, thus being comparable in significance to alliance selection)
- Pro-rates for 12 qual matches so that variation due to # of qual matches is reduced (thus a team that goes 6-2 in 8 qual matches would be treated as if it went 9-3 in 12 qual matches).
- Includes essentially 3 events: a team's best two regional/district events and the average of their performance at DCMP and CMP events.
- Multiplies points earned at DCMP and CMP by 1.7x so that mid-tier teams that do well at the regional/district level but struggle at higher levels aren't punished for having competed against stronger teams.
- Uses a weighted average of the (up to) 3 events, helping teams that have proved consistency by competing at a particular level over multiple events. This weight is: 1x for one event, 1.11x for two events, and 1.18x for three events. I, personally, really like how this balance works out in the rankings.
- Includes another 10 points for Einstein Finalist and 20 points for Einstein Winner (these are then multiplied by the DCMP/CMP 1.7x multiplier)
- Based on the concept of replacement-level, subtracts out 12 points (putting the replacement-level team at 0; teams above that level would have a positive aWAR while teams below that level would have a negative aWAR).
- Then scales the raw points to fit a max of about 7 by dividing the "subtotal" by 15.
- For multi-season aWAR, the aWAR from the past 4 seasons are averaged, with higher weight being put on more recent seasons (32%, 29%, 23%, 16%).

I hope to update this spreadsheet weekly to include 2014 data... I'll need to add the infrastructure to do this, and then bring in data from Ed Law's spreadsheet every week. I also hope to include rWAR (robot Wins Above Replacement), which would include only robot-performance-related data (i.e. few or no awards)... I doubt that will happen soon, though!

The spreadsheet should be attached... it's a massive 30+ mb though, so don't expect a speedy download! :-) There are three tabs that you're intended to use (or tinker with)... The "Team Lookup" can be used just to look up one team at a time. The "aWAR" tab has the aWAR calculations from the past 6 years along with the Weighted Average of aWAR as of 2013. Feel free to sort by anything and/or filter by states/regions/countries! Lastly, you can use the "Point System" tab to tweak the system in various ways and see what happens! I would recommend if you're trying to really see the dynamics of the system, pick a region and season you're familiar with, and sort... watch what happens at each level of the rankings (but especially top and middle levels).

Please feel free to provide feedback... While I do generally like how aWAR is calculated currently, I would definitely be interested in improving it! If you find bugs, improvements, or recommendations, please mention it!

I tried putting it up in CD-Media under white papers, but that was over an hour ago with no result yet... hopefully that'll come through eventually. :-) So for now at least I started this thread and uploaded a copy of the spreadsheet here: https://app.box.com/s/l6f9tgciw929415om2z0.

Top-50 by 4-year Weighted Average of aWAR:
1 1114 7.08
2 2056 7.03
3 469 6.78
4 987 6.67
5 254 6.50
6 67 6.28
7 33 5.95
8 148 5.90
9 118 5.83
10 1986 5.75
11 359 5.66
12 1717 5.62
13 341 5.50
14 1676 5.40
15 111 5.33
16 16 5.30
17 1983 5.18
18 233 5.07
19 2054 5.03
20 610 4.94
21 1538 4.94
22 1918 4.90
23 1477 4.85
24 217 4.81
25 2169 4.81
26 1718 4.66
27 2826 4.61
28 27 4.60
29 1519 4.53
30 2415 4.52
31 525 4.51
32 2016 4.48
33 330 4.40
34 365 4.38
35 1218 4.37
36 234 4.31
37 2590 4.23
38 245 4.21
39 2337 4.20
40 11 4.19
41 1678 4.18
42 25 4.16
43 180 4.10
44 103 4.03
45 1241 3.99
46 973 3.99
47 624 3.96
48 2471 3.92
49 2474 3.80
50 3138 3.80

Top 50 from 2013, by aWAR:
1 469 7.41
2 1986 7.11
3 1538 7.04
4 1114 6.91
5 33 6.78
6 987 6.72
7 2056 6.63
8 2169 6.50
9 118 6.41
10 1983 6.35
11 148 6.32
12 610 6.26
13 862 6.17
14 254 6.12
15 1477 6.09
16 2590 6.08
17 2054 5.90
18 359 5.83
19 1241 5.75
20 67 5.69
21 11 5.64
22 3476 5.59
23 1718 5.53
24 868 5.49
25 1717 5.47
26 1678 5.46
27 1676 5.44
28 20 5.41
29 128 5.41
30 4814 5.29
31 2415 5.29
32 341 5.12
33 2474 5.07
34 1918 5.07
35 3539 5.06
36 245 5.02
37 2052 4.98
38 2468 4.89
39 2959 4.89
40 1519 4.84
41 948 4.83
42 2729 4.83
43 126 4.81
44 234 4.79
45 1806 4.76
46 3997 4.76
47 1334 4.75
48 27 4.75
49 3824 4.72
50 3990 4.67