Galileo 2012!

[flippy147852]

Originally Posted by JABot67

Edit: I don't know very much about what teams have have a triple balance dingus since many probably have added them at competitions, but here's a short list (of robots that I know for sure have a dingus) that people can add on to: 25, 33, 148, 2054, 2337, 3322. 1718 has brakes on their train that stop robots from sliding around on the bridge; this turned out to be very useful for triple balancing at MSC. Wow, I don't even know if fellow Michigan teams like 1918 and 573 have these devices. Please add on to this list!

We have had a kickstand on our robot since Troy, although we have triple balanced without any form of balance assist in less than 20 seconds (with 85 and 910). Our kickstand has also been tested, and we have a triple balance with it (with 4002 and 453). We *should* have some other tricks up our sleeves for next week though

[Ryan Wilmes]

Originally Posted by Clinton Bolinger

This is what our scouters got so far:

868 Long

Originally Posted by XaulZan11

Clinton, 2169 is wide and 868 is long but not the full 38 inches (I suspect they are around 28x32 or so).

We technically are long, but we are only about 28X26, so nearly a square.

[Bjensen2928]

Originally Posted by Clinton Bolinger

This is what our scouters got so far:

8 Long
16 Long
25 Long
33 Wide
48 Long
103 Long
125 Long
148 Wide
180 Wide
237 Long
358 Wide
399 Wide
527 Wide
573 Long
744 Long
772 Long
801 Wide
815 Long
868 Long
1208 Wide
1323 Long
1350 Wide
1538 Long
1574 Long
1671 Wide
1714 Wide
1718 Wide
1732 Wide
1918 Wide
2016 Wide
2054 Long
2169 Wide
2220 Long
2337 Long
2377 Wide
2439 Long
2486 Long
2928 Long
3196 Wide
3322 Wide

Hope it helps.

-Clinton-

Edit: 2928 Wide,
thats what helped us with triple balancing in Seattle. (Olympic Field)

[Travis Hoffman]

48 has a stinger/kickstand. Simple cylinder firing vertically down. Tested/practiced, not used (yet) in actual matches.

Originally Posted by BJC

48 - long

[Daniel Brim]

69 - Mecanum
231 - Long
269 - Wide
281 - Mecanum
342 - Mecanum
384 - Long
744 - Long

Will post more tomorrow evening as I continue to go through teams/scour the internet for photos and videos of each.

[jyh947]

Ok, Galileo, let's fill this scouting sheet out!

[BJC]

^ That's much better.. I filled in what was on the earlier list.

[KevinGoneNuts]

I remember people who came and took pictures of our robot but where did you find these images? I'm just really curious. Haha Thanks

[Travis Hoffman]

Hey, we might be getting a bit cluttered here, but can we also get type of drivetrain along with the other info on each bot?

For example, 48 is 6WD (key info to know).

Optional info: 2-speed, 8" pneumatics, no center drop

*****

The difference between a 4WD wide and 6/8WD wide is not insignificant where bridge balancing is concerned.

Of course, if we'd start a Galileo pictures thread like the others, maybe a lot of that info would be self-explanatory from the pics!

EDIT - OK - the Google Doc linked in Post 56 above is awesome. We should all be editing that. Thanks!

[nuggetsyl]

Just saw the video of 3322 shooting 6 balls in auto. Clever I loved it.

[Joe Ross]

Similar to what I did in previous years, I ran through 200 simulated qualification match schedules (with 9 matches per team, using the FIRST match generator).

I used each team's highest adjusted opr at any event to choose that team's "best event". Then, for that event, I used their unadjusted OPR for their contribution to a match. I also used the hybrid OPR, bridge OPR, teleop OPR to help calculate the standings. For the co-op bridge, I summed the co-op OPR for all 6 robots in the match and compared that to a threshold. When back-testing against regionals, if the threshold was chosen to be close to the number of actual co-ops at the regional, it had a relatively high correlation to the actual results on the co-op bridge. Almost all regionals had a correlation co-efficient of between 0.6 and 0.85. However, at the Michigan State Championship, the correlation coefficient was only 0.3. I believe this is because almost all of the robots there were able to balance so the balances that didn't happen weren't be cause of the robots, but because of luck. I used this method for calculating the co-ops, trying to get a co-op percent of around 60% (higher then most regionals, but lower then MSC). Overall, this isn't a very good way to do it, as it punishes teams at early regionals and regionals where teams did not co-op that much. However, it's included to help simulate the randomness of the rankings this year. All OPR data is from Ed Law's spreadsheet.

I calculated the results for each of the 200 simulated qualification schedules, and then looked at some statistics from the aggregate results.

Since the standings are much more complicated this year, and the co-op bridge is so important, and there isn't a very good way to simulate it, I looked at both the ranks, the number of qualification points, and the number of wins.

Everyone should attend Karthik's presentation at the championships where he covers "Why 'OPR' is a flawed indicator in Rebound Rumble".

The following were the values that were used in the simulation

Team 	OPR	Teleop	Hybrid	Bridge	Coop
25	30.27	16.65	7.39	6.22	0.75
180	29.14	11.70	10.57	7.34	0.88
399	28.33	15.30	3.78	8.74	0.51
2169	28.04	22.38	7.78	-2.13	0.41
16	27.43	13.09	11.47	2.94	0.84
33	26.41	18.94	4.54	2.92	0.63
2054	24.54	9.78	6.76	8.01	0.66
48	24.38	8.49	10.03	5.86	0.53
3322	24.33	12.87	7.29	4.17	0.91
103	23.48	13.07	7.00	3.36	0.56
1918	22.90	12.33	3.75	6.82	0.57
148	21.97	13.73	4.61	2.11	0.71
1323	21.52	13.61	6.42	2.01	0.77
801	20.65	14.19	4.59	2.33	0.63
1671	20.45	11.19	10.25	0.72	0.15
2337	20.19	5.89	9.74	4.56	0.56
8	19.68	6.56	4.19	8.66	0.60
573	19.58	5.50	7.81	6.27	0.61
1538	19.33	7.23	6.77	5.17	0.71
1714	19.20	12.27	5.99	0.95	1.38
2928	18.65	11.68	3.20	3.49	0.72
1718	18.23	9.75	8.23	0.28	1.48
744	18.20	10.62	7.27	0.49	0.34
1208	18.15	10.66	5.73	1.97	0.79
772	18.15	12.26	6.86	-1.03	0.53
358	17.91	5.18	4.10	8.56	0.56
1574	17.76	6.57	7.80	3.58	0.25
342	17.71	6.39	7.96	3.63	-0.04
868	16.46	10.69	5.85	-0.08	0.32
2016	16.35	6.86	6.06	3.42	0.62
1350	16.20	6.72	3.92	5.94	0.19
2377	16.20	6.51	4.75	5.36	0.25
1732	15.65	5.57	4.54	5.54	1.15
125	15.28	8.63	5.62	1.37	0.55
1425	15.10	7.05	5.54	2.50	0.48
527	14.91	1.93	6.50	6.30	0.48
3196	14.55	6.04	7.57	0.99	0.35
3103	14.31	1.41	7.99	5.29	-0.11
231	14.14	6.17	0.87	7.34	0.47
1747	14.01	3.57	5.53	4.91	0.07
2486	13.87	6.53	4.66	2.99	0.31
815	13.62	4.92	4.67	4.05	0.83
2090	13.48	5.09	6.60	1.87	0.04
533	13.29	6.67	3.83	2.75	0.13
263	13.08	5.97	7.24	-0.13	0.42
2220	12.93	1.67	6.29	5.29	0.81
269	12.79	5.09	5.70	1.99	0.10
2642	12.11	3.78	5.71	2.58	0.29
2439	11.91	3.09	4.36	4.41	0.97
237	11.90	4.87	5.70	1.56	0.71
1108	11.85	3.18	6.82	2.09	0.41
2341	11.54	4.62	1.08	5.97	-0.14
4159	10.67	1.38	5.00	4.75	0.02
4146	10.39	3.44	4.63	3.09	-0.23
4057	10.31	2.31	-2.33	10.33	-0.08
281	9.93	1.93	5.31	2.88	-0.04
69	9.71	4.54	-1.04	5.85	-0.05
1038	8.68	3.09	1.46	3.83	0.25
1011	8.46	6.59	2.80	-0.51	0.33
3453	8.28	2.97	3.88	2.74	-0.12
4099	8.22	1.90	1.58	5.17	-0.14
1305	7.96	0.64	4.37	3.94	0.47
4083	7.91	1.78	0.95	5.54	0.50
3574	7.69	0.22	4.18	2.69	0.73
492	7.47	0.69	4.51	2.30	-0.12
384	7.26	3.04	5.33	-0.70	0.40
3931	6.89	0.84	5.16	0.88	0.08
766	6.80	0.90	1.45	3.69	0.05
1515	6.41	1.38	1.61	3.48	0.25
4031	5.91	1.97	0.41	3.53	-0.20
870	5.18	-2.07	-1.63	9.35	0.35
168	5.07	2.88	0.76	1.11	0.00
1831	4.85	3.89	-0.33	1.22	0.05
3142	4.68	1.04	2.34	1.26	0.53
3784	4.60	2.37	2.40	-0.17	0.22
1583	4.60	1.67	1.87	1.23	0.33
3189	4.47	1.52	1.27	2.64	0.65
771	4.41	1.33	0.77	-0.23	-0.01
1262	4.05	-0.47	3.12	1.21	0.17
3173	3.87	4.29	0.55	-0.69	-0.22
4013	3.81	1.93	-0.76	2.87	0.14
4394	3.57	-0.83	2.19	2.26	0.19
4028	3.36	1.25	1.52	0.60	0.28
296	3.21	0.41	-0.40	3.23	0.18
1212	3.10	2.08	-0.32	1.92	-0.01
4090	3.01	3.96	-0.51	-0.33	-0.13
568	2.28	-0.03	-2.01	4.34	0.03
3981	1.78	2.01	-1.67	1.46	-0.02
4372	1.49	-0.55	0.62	1.43	0.08
4353	1.42	2.65	-0.28	0.11	0.37
3530	1.05	-1.56	0.77	1.85	-0.19
585	1.03	4.19	-1.78	-0.97	0.02
3259	0.83	-0.22	-0.57	1.58	0.60
2704	0.16	1.93	-1.32	-0.49	-0.24
2010	0.02	-2.13	2.36	-0.05	0.27
2339	-0.08	0.05	-2.04	1.52	0.34
3925	-0.50	-0.56	0.34	-0.36	-0.13
2158	-0.55	0.80	-0.56	-0.67	-0.03
151	-1.15	-0.19	0.54	-1.64	0.05
1382	-3.74	-5.07	1.77	-0.15	0.19

Seeds:

	avg	med	mode	min	max	stdev	top8	#1
25	9.24	7	3	1	39	7.68	115	13
180	6.95	4	1	1	31	6.84	137	42
399	19.09	18	19	1	62	11.20	35	3
2169	17.19	15	12	1	74	12.05	47	3
16	8.91	6	1	1	42	8.16	118	31
33	17.12	15	2	1	60	12.29	63	5
2054	14.28	12	6	1	45	10.47	78	10
48	21.94	20	15	1	73	13.76	34	4
3322	10.66	7	6	1	52	9.74	111	18
103	21.16	19	10	1	66	13.24	37	3
1918	23.98	22	12	1	74	14.28	27	1
148	18.77	17	4	1	60	12.69	51	2
1323	16.15	14	7	1	56	10.96	59	6
801	23.28	21.5	24	1	63	13.36	27	2
1671	36.41	36	39	4	91	17.30	6	0
2337	22.65	20	12	1	81	15.08	38	5
8	27.46	26	19	1	84	15.07	19	1
573	21.68	19	11	1	66	14.36	38	1
1538	22.17	21	24	1	75	14.08	32	2
1714	11.96	11	8	1	46	8.82	86	10
2928	22.89	20	20	1	69	13.85	28	1
1718	9.23	7	1	1	53	8.35	117	27
744	38.23	38	38	2	92	18.06	8	0
1208	22.43	21	8	1	69	14.91	44	4
772	27.33	25	29	1	74	16.69	24	1
358	30.08	29	21	2	81	15.59	13	0
1574	38.27	38	29	3	92	18.24	6	0
342	49.95	49	39	5	98	17.55	1	0
868	39.82	38	42	2	86	16.65	2	0
2016	28.79	26	30	1	77	16.34	20	2
1350	46.97	47	25	4	90	19.46	5	0
2377	42.73	42	43	7	99	16.99	1	0
1732	18.41	17	3	1	57	12.57	52	2
125	33.31	30	19	2	83	17.32	11	0
1425	33.48	33	32	5	77	15.89	9	0
527	36.69	36	19	2	82	16.98	6	0
3196	39.17	38.5	39	2	85	17.69	5	0
3103	60.37	62	72	16	97	18.82	0	0
231	39.89	38.5	39	4	87	16.96	5	0
1747	55.95	55.5	49	6	100	18.38	1	0
2486	44.46	44.5	49	3	91	18.11	5	0
815	28.84	27	22	2	68	14.92	15	0
2090	56.98	54	40	14	96	18.27	0	0
533	56.31	56	50	11	99	17.59	0	0
263	43.02	41	41	6	94	17.74	5	0
2220	28.96	28	29	2	77	16.66	19	0
269	54.32	54	60	8	98	19.70	1	0
2642	46.67	47	40	5	92	18.54	1	0
2439	26.46	25	18	2	74	14.51	20	0
237	32.01	29.5	21	1	79	16.50	10	1
1108	41.89	41	55	4	92	18.25	3	0
2341	70.73	72	67	32	100	16.90	0	0
4159	61.21	60	60	19	99	18.41	0	0
4146	72.05	74	71	12	100	18.00	0	0
4057	73.46	75	62	23	100	17.15	0	0
281	66.59	68	89	11	100	19.08	0	0
69	69.06	69	70	18	100	17.31	0	0
1038	59.58	60	75	18	96	19.66	0	0
1011	55.47	55	51	8	96	18.07	1	0
3453	73.08	76	78	25	100	16.14	0	0
4099	76.64	79	84	23	100	16.51	0	0
1305	50.91	50	50	9	92	17.18	0	0
4083	52.95	53.5	69	10	98	18.58	0	0
3574	40.70	38	36	7	88	16.60	1	0
492	77.50	81	88	20	100	16.04	0	0
384	54.69	55	68	12	99	16.84	0	0
3931	65.98	69	83	8	99	18.92	1	0
766	73.23	75	90	27	99	16.03	0	0
1515	66.07	67.5	57	25	99	17.35	0	0
4031	82.84	86	93	37	100	14.14	0	0
870	64.44	65	61	11	100	18.91	0	0
168	75.87	77	79	33	100	15.17	0	0
1831	75.51	78.5	94	15	100	16.95	0	0
3142	55.49	56	44	18	95	17.67	0	0
3784	67.32	67	84	12	100	17.53	0	0
1583	63.83	64.5	77	17	97	17.46	0	0
3189	53.58	54	71	4	96	19.47	2	0
771	78.30	81.5	94	34	100	15.49	0	0
1262	70.14	70.5	65	32	100	16.38	0	0
3173	84.73	88	96	37	100	13.20	0	0
4013	75.65	77	88	25	100	16.47	0	0
4394	71.25	76	84	13	100	18.50	0	0
4028	67.96	69	74	14	98	16.74	0	0
296	73.46	76	87	22	100	17.32	0	0
1212	79.95	83	97	27	100	15.39	0	0
4090	82.47	86	96	30	100	14.84	0	0
568	80.92	84	92	36	100	15.17	0	0
3981	83.95	87	100	44	100	13.40	0	0
4372	81.12	85	85	27	100	14.69	0	0
4353	70.82	72	77	16	100	17.49	0	0
3530	87.48	91	100	39	100	11.77	0	0
585	83.55	87	94	36	100	13.47	0	0
3259	60.52	60.5	68	21	99	17.96	0	0
2704	90.69	95	100	51	100	10.55	0	0
2010	73.76	74	85	21	100	16.41	0	0
2339	72.13	73	67	23	100	17.46	0	0
3925	88.68	92	99	51	100	10.59	0	0
2158	85.91	89	89	47	100	11.95	0	0
151	82.40	86	96	25	100	14.11	0	0
1382	80.68	83	95	34	100	13.73	0	0

QPs:

	avg	med	mode	min	max	stdev	Perfect
25	28.66	29	30	21	36	2.90	1
180	29.19	30	30	22	36	3.06	2
399	25.92	26	26	16	32	3.01	0
2169	25.72	26	26	14	34	3.26	0
16	28.29	28	28	20	36	3.20	2
33	26.46	26	26	16	34	3.30	0
2054	26.97	27	26	20	34	3.26	0
48	24.35	24	24	14	34	3.55	0
3322	28.17	28	28	18	36	3.22	1
103	24.96	25	26	16	34	3.56	0
1918	24.84	24.5	26	14	34	3.67	0
148	25.98	26	24	18	34	3.51	0
1323	26.50	26	26	18	34	3.20	0
801	24.74	25	26	16	32	3.28	0
1671	20.89	20.5	22	11	28	3.60	0
2337	24.16	24	26	13	33	3.88	0
8	24.03	24	26	13	34	3.65	0
573	24.63	24	26	15	34	3.64	0
1538	24.71	24	24	14	34	3.60	0
1714	27.88	28	28	20	36	2.83	1
2928	25.20	26	26	14	32	3.42	0
1718	28.61	28	28	18	35	3.07	0
744	20.82	20	22	10	30	3.97	0
1208	24.85	25	22	16	36	3.75	1
772	23.42	24	24	14	34	3.91	0
358	23.23	23	22	13	32	3.58	0
1574	20.61	20	22	10	28	3.88	0
342	18.19	18	20	8	30	3.46	0
868	20.55	20	20	10	30	3.51	0
2016	23.25	24	22	13	34	3.88	0
1350	19.51	20	20	10	30	4.03	0
2377	20.16	20	20	7	28	3.53	0
1732	26.18	26	26	18	35	3.42	0
125	22.12	22	24	12	30	3.82	0
1425	21.96	22	22	14	30	3.47	0
527	21.15	21.5	22	11	32	3.73	0
3196	20.49	20	18	12	31	3.76	0
3103	16.11	16	16	8	26	3.72	0
231	21.42	22	22	12	30	3.58	0
1747	17.21	17	16	8	30	3.82	0
2486	19.83	20	20	10	32	3.85	0
815	23.38	24	24	14	32	3.46	0
2090	16.85	17.5	18	8	26	3.57	0
533	17.46	18	18	6	28	3.62	0
263	19.76	20	20	10	28	3.65	0
2220	23.22	23	22	14	34	3.85	0
269	17.52	18	16	7	26	4.07	0
2642	19.13	19	18	10	28	3.74	0
2439	24.13	24	26	16	34	3.51	0
237	22.40	22	24	13	34	3.66	0
1108	20.03	20	18	10	29	3.80	0
2341	14.84	14	14	6	22	3.54	0
4159	16.23	16	16	8	24	3.70	0
4146	13.81	14	14	2	28	4.06	0
4057	14.66	15	16	6	24	3.79	0
281	15.06	15	14	4	28	4.00	0
69	15.47	16	16	4	26	3.66	0
1038	17.15	17	18	8	26	3.96	0
1011	17.81	18	18	8	30	3.72	0
3453	13.84	14	16	6	24	3.54	0
4099	13.25	14	14	4	24	3.71	0
1305	18.57	18	18	10	28	3.50	0
4083	18.66	18	18	8	28	3.80	0
3574	20.81	21	22	10	28	3.48	0
492	12.57	12	10	4	24	3.71	0
384	17.61	18	16	8	28	3.45	0
3931	15.24	15	18	6	28	3.88	0
766	14.42	14	14	6	23	3.45	0
1515	15.80	16	16	8	24	3.60	0
4031	12.11	12	12	4	22	3.36	0
870	16.61	16	18	6	28	3.82	0
168	13.62	14	14	4	22	3.61	0
1831	13.79	14	14	2	27	3.90	0
3142	17.93	18	20	8	26	3.62	0
3784	15.34	16	16	4	28	3.89	0
1583	16.31	16	16	8	26	3.55	0
3189	18.59	18	18	8	30	3.92	0
771	12.95	13	10	2	22	3.78	0
1262	14.60	15	16	4	22	3.59	0
3173	11.31	11	10	2	21	3.56	0
4013	14.10	14	16	2	24	3.56	0
4394	14.56	14	14	4	28	4.10	0
4028	15.37	16	14	8	27	3.46	0
296	14.43	14	14	6	26	3.85	0
1212	12.86	12	12	4	24	3.65	0
4090	12.28	12	12	2	23	3.75	0
568	12.92	12	12	4	22	3.65	0
3981	12.19	12	10	2	22	3.40	0
4372	12.44	12	12	4	22	3.46	0
4353	15.01	15	14	6	26	3.70	0
3530	10.54	10	12	4	20	3.37	0
585	12.22	12	12	2	22	3.48	0
3259	17.40	18	18	6	26	3.53	0
2704	9.78	10	8	2	20	3.48	0
2010	13.95	14	12	4	24	3.68	0
2339	14.91	16	16	6	26	3.83	0
3925	10.40	10	10	1	19	3.26	0
2158	11.46	12	12	4	20	3.36	0
151	12.09	12	12	4	25	3.43	0
1382	12.32	12	12	4	22	3.36	0

Wins:

	avg	med	mode	min	max	stdev	Perfect
25	7.56	8	8	4	9	0.99	31
180	7.41	8	8	4	9	1.13	34
399	7.20	7	7	4	9	1.10	27
2169	7.30	7.5	8	3	9	1.21	27
16	7.14	7	8	4	9	1.18	27
33	7.01	7	8	3	9	1.28	21
2054	6.97	7	7	4	9	1.16	12
48	6.40	6.5	7	2	9	1.35	8
3322	6.74	7	7	3	9	1.25	11
103	6.46	6	7	4	9	1.18	7
1918	6.46	7	7	3	9	1.45	12
148	6.38	6	7	3	9	1.29	11
1323	6.37	6	6	3	9	1.29	11
801	6.18	6	6	3	9	1.36	5
1671	6.18	6	6	2	9	1.35	3
2337	6.05	6	6	2	9	1.41	5
8	5.80	6	6	2	9	1.51	1
573	6.16	6	7	3	9	1.38	7
1538	5.82	6	6	2	9	1.41	5
1714	5.48	6	6	2	9	1.33	2
2928	6.04	6	6	2	9	1.35	5
1718	5.51	5	5	2	9	1.41	1
744	5.48	5	5	2	9	1.44	2
1208	5.52	5.5	5	1	9	1.50	3
772	5.77	6	5	1	9	1.55	5
358	5.66	6	7	1	9	1.44	3
1574	5.62	6	6	2	9	1.37	1
342	5.68	6	6	1	9	1.38	1
868	5.26	5	5	2	8	1.42	0
2016	5.34	5	6	2	9	1.55	5
1350	5.19	5	5	2	9	1.56	4
2377	5.36	5	6	1	8	1.41	0
1732	5.04	5	5	1	9	1.54	1
125	5.08	5	5	1	8	1.48	0
1425	5.30	5	6	2	9	1.44	1
527	5.05	5	5	0	9	1.58	2
3196	5.08	5	5	1	8	1.37	0
3103	4.85	5	5	1	8	1.46	0
231	4.94	5	6	1	8	1.46	0
1747	4.71	5	5	1	9	1.48	1
2486	4.87	5	5	0	8	1.48	0
815	4.66	5	5	1	9	1.47	1
2090	4.75	5	4	1	8	1.48	0
533	4.66	5	5	1	9	1.59	1
263	4.58	4	4	1	8	1.38	0
2220	4.66	5	5	1	8	1.63	0
269	4.60	5	5	1	9	1.55	1
2642	4.83	5	6	1	9	1.43	1
2439	4.54	5	5	1	9	1.64	1
237	4.66	5	5	0	8	1.53	0
1108	4.51	4	4	1	8	1.49	0
2341	4.33	4	4	1	8	1.42	0
4159	4.49	5	5	1	8	1.59	0
4146	4.26	4	5	0	8	1.51	0
4057	4.09	4	4	1	8	1.55	0
281	4.11	4	4	0	8	1.43	0
69	4.23	4	5	1	8	1.46	0
1038	3.94	4	4	0	7	1.51	0
1011	3.85	4	4	1	8	1.42	0
3453	3.70	4	3	1	8	1.40	0
4099	3.70	4	4	0	9	1.43	1
1305	3.61	4	4	0	7	1.37	0
4083	3.72	4	3	0	8	1.44	0
3574	3.72	4	4	0	7	1.33	0
492	3.45	3	3	0	7	1.43	0
384	3.59	3	3	1	8	1.35	0
3931	3.64	4	4	1	7	1.41	0
766	3.47	3	3	1	7	1.26	0
1515	3.23	3	3	0	7	1.35	0
4031	3.37	3	3	0	7	1.40	0
870	3.27	3	4	0	8	1.51	0
168	3.17	3	3	0	7	1.39	0
1831	3.04	3	3	0	7	1.41	0
3142	3.11	3	3	0	8	1.35	0
3784	3.04	3	3	0	6	1.35	0
1583	3.10	3	3	0	7	1.35	0
3189	2.93	3	3	0	7	1.51	0
771	2.81	3	2	0	7	1.46	0
1262	3.06	3	3	0	7	1.41	0
3173	2.92	3	3	0	6	1.37	0
4013	2.79	3	3	0	7	1.33	0
4394	2.96	3	2	0	7	1.45	0
4028	2.80	3	2	0	8	1.36	0
296	2.80	3	2	0	6	1.43	0
1212	2.80	3	2	0	8	1.47	0
4090	2.93	3	3	0	6	1.42	0
568	2.75	3	3	0	6	1.31	0
3981	2.57	3	3	0	6	1.24	0
4372	2.30	2	2	0	7	1.34	0
4353	2.46	2	2	0	5	1.27	0
3530	2.49	2	2	0	7	1.37	0
585	2.39	2	2	0	6	1.31	0
3259	2.52	2	2	0	6	1.32	0
2704	2.17	2	2	0	6	1.26	0
2010	2.25	2	2	0	7	1.38	0
2339	2.45	2	3	0	6	1.40	0
3925	2.22	2	2	0	5	1.27	0
2158	2.19	2	2	0	5	1.27	0
151	2.18	2	2	0	7	1.27	0
1382	1.63	2	2	0	5	1.12	0

[Gary Dillard]

Hmmmmmmmmmm SPAM was #1 seed at both of their regionals, finalist in one and winner in the other, 2nd highest OPR & World ranking in the division, Joe's simulation seems to like them, yet noone posting seems to think they are a contender. They must be flying under the radar. I have a feeling that they may have kept a few tricks in their bag just for the Championship. It's been 10 years since their last Einstein appearance; could this be their year?

[George1902]

Originally Posted by Gary Dillard

They must be flying under the radar.

I don't mind that too much, actually...

Good luck, everyone!

[Rashek]

I just wanted to post what my research has showed me about the teams on Galileo. I came up with this data by going down the entire listof the field. Next I looked up these teams on FRC Spyder. Anytime that scored 200+ in any of the categories I wrote down. After I figured out those teams I copied the information onto an excel spreadsheet.

The numbers I used were a mix from each of the competitions. For example: Say a team went to three competitions. At Competition A they had their best teleop points. At Competition B they had their best hybrid. At Competition C they had their best balancing. So I would used the teleop from A, the hybrid from B, and the balancing from C.

Next I added all the numbers together in order to come up with a grand total of points. I then arranged the grand totals in descending order. I came up with the following:

Team # HP BP TP Grand Total
2054 227 200 289 716
33 195 130 380 705
1918 235 140 269 644
25 175 120 329 624
2337 234 150 239 623
1718 166 150 260 576
2016 205 140 209 554
3322 166 100 285 551
180 175 120 209 504
2169 155 30 317 502
103 136 110 223 469
48 154 70 240 464
1323 132 50 240 422
801 116 90 215 421
399 93 110 206 409
868 148 50 211 409
772 137 50 204 391
148 97 50 208 355

I am well aware of the fact that FRC Spyder doesn't count the elimination matches, and therefore this spredsheet isn't 100% accurate. This is my first time doing anything like this so any feedback woul be greatly appreciated.

[flippy147852]

Originally Posted by Rashek

Next I added all the numbers together in order to come up with a grand total of points. I then arranged the grand totals in descending order. I came up with the following:

Team # HP BP TP Grand Total
2054 227 200 289 716
33 195 130 380 705
1918 235 140 269 644
25 175 120 329 624
2337 234 150 239 623
1718 166 150 260 576
2016 205 140 209 554
3322 166 100 285 551
180 175 120 209 504
2169 155 30 317 502
103 136 110 223 469
48 154 70 240 464
1323 132 50 240 422
801 116 90 215 421
399 93 110 206 409
868 148 50 211 409
772 137 50 204 391
148 97 50 208 355

I like the Michigan bias, first of all (6 of the top 10 are Michigan teams ) That being said, BP isn't a very accurate metric without adding some sort of coopertition compensation. I don't have the data in front of me right now, but I am sure that the rankings would change with coopertition.