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Unread 05-02-2017, 13:49
Caleb Sykes's Avatar
Caleb Sykes Caleb Sykes is offline
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How to use FRC Events data to determine gear ability

Considering how important gear scoring will be this year, we should figure out the best way to use FIRST's scoring data to come up with a gear contribution for each team. However, since we aren't actually directly provided with the number of gears scored each match, we will have to get creative with using the data provided to us. Let's try to find the best way to use this info to create one or more useful gear contribution metrics. I want to start this conversation early so that we can have some level of standardization between common data analysis tools.

Here is the data we will have to work with (although this may be updated before competition): http://docs.frcevents2.apiary.io/#re.../score-details

The most relevant categories we have to work with are:
rotor1Auto
rotor2Auto
rotor1Engaged
rotor2Engaged
rotor3Engaged
rotor4Engaged
rotorRankingPointAchieved (Quals only)
autoRotorPoints
teleopRotorPoints
rotorBonusPoints (Playoffs only)

Note that the last 4 categories can be found from the first 6.

The easiest suggestion I have would be to create a "scored gears" contribution which can be found by assigning a number of scored gears to each rotor. Essentially, rotor1Engaged= 1 scored gear, rotor2Engaged = 3, rotor3Engaged = 7, and rotor4Engaged = 13. An alternative to this method would be to subtract 1 scored gear from each of these because every alliance has a free gear which will be scored in the grand majority of matches. Doing this would make rotor1Engaged = 0 scored gears, rotor2Engaged = 2, rotor3Engaged = 6, and rotor4Engaged = 12.

I don't actually have a very strong opinion on which of these to use, as linear regression methods should provide exactly the same results just with an offset of 0.33 for each team. I do however want standardization, so let's try to come to a consensus and stick with it.

I have some other ideas churning in my head that I'll probably post soon, but I'm curious to hear other ideas for how we can best utilize this information.
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