[C^3] 2016 CA Regionals Analysis

With the start of several new prediction accounts last year, I thought I’d start something like that for California, but with a slightly different twist. Instead of predictions, C^3 will be focused on analysis, using hard data such as OPR and match results to analyze teams, events, and overall trends. Raw data will be linked to at the end of each post for anyone interested.

Before I begin, a quick explanation on the name: C^3 stands for California Competition Calculations–a phrase that a friend and I decided was a decent balance between sounding nice and making sense. [1] As the name implies, C^3 will be focused on California events, but it may extend to other things if I have time.

To start it off, I thought I’d bring up some data on the 2016 season from the 7 CA regionals. The text ended up rather small, but the order of events listed is always casd-calb-cama-cada-cave-capl-casj, with quals before playoffs.

2016 Regionals Recap

Defense selection was surprisingly steady over the weeks, with a few exceptions (e.g. moat was very common at Sac quals). CDF, ramparts, sally port, and rock wall were definitely the favorites of their respective categories, with the rough terrain not appearing at all during SVR playoffs.


Breaching success in quals did increase as the weeks went by, but breaching success in playoffs hit their max during week 1 at San Diego, at 97%.


Similarly, capturing, challenging, and scaling success in quals increased, but the max percentage of teams that challenged/scaled came during the San Diego playoffs. (note that scaling percentages do include “penalty scales”)


Score breakdowns show another small increase over the weeks, but with the largest increases in playoff scores, especially by the winning alliances. The average playoff winning margin also increased each week (with the exception of Orange County), suggesting that the top-tier pulled even farther ahead as the competitions went on.


And that’s it for now! Let me know if you find any errors in this, if you have any feedback about this format, or if there’s something in particular you’d like to see in the future. I’m currently working on one about the correlation between in-season and off-season performance, so look out for that one, which will hopefully come out before Chezy Champs, but have nothing planned after that.

[1] The other names we came up with included Speed of Insight / Speed of Insight Cubed, C3PO (couldn’t figure out the O), -1 / i^2 (for ___ insights, but CA doesn’t start with an i unfortunately), 2.7x10^25 (speed of light cubed), or e / mc^2 (couldn’t figure out the m).

Raw data: 2016_regional_data.csv (4.13 KB)

2016_regional_data.csv (4.13 KB)

2016_regional_data.csv (4.13 KB)

Very interesting, I expected to see scaling increases more as the season progressed due to teams adding scaling to their robots. But it seems to have stayed relatively the same.
I also wonder what this data would look like for Michigan.

These are great statistics! Thanks for putting all the hard work.


+2 . Thanks Rachel!

BTW, using “C^3” is excellent. It should not get confused with “CCC” which is the short version of Capital City Classic.

I look forward to following this thread as 2016-2017 develop!

I’m having trouble interpreting the second set of graphs (Breaching success, quals and Breaching success, playoffs). In casd quals, the breaching success of the drawbridge is ~20%. Does this mean that the opponent defenses were breached in 20% of the matches in which the drawbridge was selected? Does this mean that the drawbridge was selected in 20% of matches in which a breach occurred? Or are you conflating breaches with weakenings?

Judging by TBA’s insights page, the graph shows the percent of times that the defense was damaged of all the times that it was on the field, at each event. With the exception of the black line, which shows the overall breach rate.

Yes, this is correct. Sorry for the bad wording on my part–it should say weakening not breaching for the colored lines.

Thank you to everyone else for your comments. I’m glad you guys like this!