Robolyst Robolyst

12492 Blender Bots

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San Jose, CA, USA Since 2016

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Events
18
Career
49–49–1
Awards
4
1st place
2

Season profile

2025–2026 Decode
Compared against
Best score one match, not an average
85th percentile 264
#1,265 of 8,263
OPRc
86th percentile 56.7
#1,129 of 8,303
OPR
87th percentile 68.9
#1,083 of 8,303
Strength
85th percentile 53.9
#1,262 of 8,303
Consistency lower is better
20th percentile 21.4
#6,659 of 8,301
Total Luck
86th percentile · lucky +8.5
#1,132 of 8,303

Event by event

Strength margin of error
88.869.249.730.210.6South Bay League Meet 1 — Strength 22.9 ± 5.8South BaySouth Bay League Meet 2 — Strength 59.5 ± 11.8South BaySouth Bay League Meet 3 — Strength 58.6 ± 12.4South BaySouth Bay League Tournament — Strength 74.5 ± 7.8South Bay

A line that climbs across the season is a robot that got better; a flat one with a wide band is a rating that hasn't been measured on enough matches to trust yet.

South Bay League Meet 1 Nov 1 USCANOSBM1

Best score 118 Q17
Strength 22.9 #11 of 16 here
Consistency 14.2 #5 of 16 here
Total Luck -1.8 fair
Where the points came from auto 3.0 teleop 19.0 OPRc 22.0

South Bay League Meet 2 Dec 12 USCANOSBM2

Best score 157 Q15
Strength 59.5 #5 of 16 here
Consistency 26.4 #14 of 16 here
Total Luck +6.2 lucky
Where the points came from auto 14.9 teleop 44.4 OPRc 59.3

South Bay League Meet 3 Jan 17 USCANOSBM3

Best score 147 Q4
Strength 58.6 #5 of 16 here
Consistency 27.8 #9 of 16 here
Total Luck +17.4 very lucky
Where the points came from auto 18.0 teleop 46.5 OPRc 64.5

South Bay League Tournament Feb 7 USCANOSBLT

Best score 264 Q10
Strength 74.5 #5 of 16 here
Consistency 17.4 #5 of 16 here
Total Luck +12.2 lucky
Where the points came from auto 21.2 teleop 59.9 OPRc 81.1

Each event's numbers are fit from that event's qualification matches; the season profile averages them across the events played. What every column means →