Team 488’s hard working scouts collected all of the match data from Friday which we used for strategy and alliance selection on Saturday. We decided full scouting on Saturday wasn’t worth the effort, so unfortunately the data doesn’t perfectly reflect a team’s overall performance, but is interesting and a pretty accurate method of ranking.
It would have been difficult to evaluate exactly how many points a ringer robot would score in a match because the points changed so quickly with alliance members forming rows etc, so we only recorded number of ringers scored. To turn these numbers into a comparison of actual scoring potential we used two different statistics, average base, and average max score. The base score consisted of lifting points, plus two points for eachringer. This would bias the overall score in favor of lifters, so we also looked at average max score which assumed that all of the ringers the robot placed were in a row. This is an interesting statistic as it can favor ringers more, but also not really describe the ability of alliances to jointly create rows. Overall with defense and alliance organization we felt that the average max score was a pretty balanced indicator of score.
That being said, our data showed some interesting things.
Here is the list of teams and their corresponding max score per Friday data. Out of the top spots 2, 3, 6, and 8 were all held by teams that primarily lifted.
Rank Team AvgMaxScore
1 1540 37.5 (seed 2)
2 997 37 (seed 4)
3 488 28.5 (seed 6)
4 272 18.33333333
5 1571 18
6 1891 16.8
7 948 13 (seed 1)
8 1280 13
9 2149 11
10 1318 9.4
11 1595 8.2
12 957 7.2
13 1778 7
14 1823 7
15 1425 6.333333333
16 1510 6.333333333
17 2142 6
18 1087 4.8
19 956 4.4
20 360 4.333333333
21 2249 4
22 2222 3
23 2148 2.666666667
24 2046 2.6 (seed 8)
Notice seeds 3, 5, and 7 are not in the top 24 for points scored, something I heavily attribute to (my personal opinion) horrible matching algorithm.
If you sum the max scores for the 8 alliances, you get a pretty good predictor of the finals performances, with the statistical upset of 1294, 1425, and 2122 winning against 360, 2046, and 2149. They even went on to beat the regional winners 997, 272, and 1087 in a very close 62-61 point game before they came back to advance to the finals.
Rank SumMaxScore Aliance-
1 60.13 997 272 1087
2 57.5 1778 1540 948
3 46.1 1318 1595 488
4 25.53 1013 1510 1571
5 18 1359 1983 1891
6 17.93 360 2046 2149
7 15.7 1887 114 1280
8 8.73 1294 1425 2122
Top teams by average ringers placed per match:
Rank Team AvgRingersPerMatch
1 1540 3.83
2 272 3.33
3 1571 2.8
4 948 2.6
5 1595 2.6
6 1318 2.2
7 360 2
8 1425 2
9 1510 1.66
10 956 1.4
Top teams by average points from lifting:
Rank Team AvgLiftPoints
1 997 36
2 488 27.5
3 1891 15
4 1280 12
5 2149 10
6 1778 6
7 1823 6
8 957 6
9 2142 5
10 948 3
Overall I think lifting, defense, and agility became very important aspects of the game. In our final matches some of the best ringers at PNW were playing primarily defense, and the ability robots have to quickly approach and climb ramps was key to those lifting points. Many matches with very good ringer robots ended up with one or two ringers on the rack and a brutal fight for lifting points at the end.
I came to Portland with some expectations about the game, and was overall pleasantly surprised. I was expecting low ringer scores and lifting to dominate, but the difficulty of driving and lifting provided for some high scores through a great variety of strategies, but also low scoring and incredibly close and suspenseful games played by some of the best teams at the event. The combination of lifting, forming long rows, and placing spoilers make the ability for 10 seconds at the end of the game to change everything, and forced the drivers and alliances to work together to make some very quick and important decisions.
If anyone has questions, or is looking for any specific data let me know. We will be attending San Jose and will hopefully be collecting the same scouting data.
