Paper: 2008 Team 1114 Championship Database

2005: White Paper Discuss: Karthik’s 2005 Championship Scouting Database
2006: paper: 2006 Niagara FIRST Public Championship Scouting Database
2007: paper: 2007 Championship Event Scouting Database, presented by Team 1114

This is pretty amazing. Thank you very much for releasing this information. I’ll be sure to pass it on to our scouts, and take a thorough look at it myself. This is a wonderful tool.

crap…holy crap … amazing tool :slight_smile:

And I love the interface! Talk about user friendly! You all rock! Great job! :slight_smile:

Thanks to 1114 for making this wonderful resource available once again!

In case anyone wants to make corrections to their local copy, 134 was champion at NH and 16th pick.

I <3 statistics.

Excelent job as always Karthik…

One bit of incorrect data I found though. Team 134 is listed in the database as not having made the eliminations at BAE. They actually won the regional with 121 and 40.

Extremely useful tool…I’ll be using it heavily at championships.

FYI- Some of the teams going to the championship don’t have championship rankings and percentages. I was looking through the teams and noticed that.

Well, those scores are really nice and the table and database have a great quality.
Still, I think you should be careful with the conclusions from the database about the teams.
If you have a look at our scores, for example. The scores for the Seattle Regional are lower for us than for the Portland Regional.
Even though, our team was 5-2-0 in the qualification rounds in Portland, we didn’t play 3 of those matches due to technical issues!
In contrast, in Seattle, we were quite dominating, scoring a lot of points and ending up as an alliance-captain and finally as the winner of the regional. During the tournament we didn’t break down. In the finals we had a large contribution and didn’t lose any game.
We greatly improved between those two regionals (teams that saw both regionals will tell you that), but the database does not really reflect that.
This is again caused by the OPR that are not reflecting at all what percentage of scoring a team does and closer data about the team itself. I think our scouting system gives us more, and detailed information about the teams themself, even though it needs more time to be evaluated…

I am just saying that our team is a good example of the disadvantages for these kinds of statistics

Team 1983 - The Skunkworks

Agreed. But I’m sure that the top teams who will be selecting know how to scout well and not to rely just on past statistics like this.

The tool itself is awesome but should only supplement strategy and scouting meetings along with your own up-to-date data from scouting in your division.

Great job once again Karthik.:slight_smile:

This is why, in the past, we have not posted these statistics. They are not perfect. But they are the best thing anyone has come up with to determine a teams contribution using only match scores. At championship, as we do at every regional, we’ll be counting every point scored (or lost) by each robot. Nothing beats numbers.

These stats are definitely a better gauge of a teams performance than believing what a team says about there own performance. You said that in Portland you were scoring a lot of points in qualifying, yet your average alliance score was 30.5. Based on this information, I would say your statement was a little optimistic. I don’t blame you for it, everyone does it. It’s just an example of why we like to use numbers.

It is possible that I am wrong here and you put up 30+ points every match and your partners were taking penalties. If that is the case, I guarantee that our scouts and many others will take notice of you on Galileo. No matter what your OPR was on this spreadsheet.

Good luck. We’ll see you on the field.

great stuff

wish i heard about it before i compiled mad data off blue alliance for my division…

o well.

anyone have any stats on penalties drawn by robots, or alliances?

not gonna lie, i learn more about a team by how many points they lose, then score