Team 3929 Scouting Sheet

One thing that lots of people hate about paper scouting is the difficulties of handling tons and tons of sheets of paper. Team 3929 tried to combat this problem by making one compact and effective sheet for each team. Not only would this limit the amount of papers needed, but it would also make it easier to find data on a particular team.

This is a great sheet! Our team is on the fence between using a web app or pencil and paper so this may turn the tide. Great work!

I am no expert on scouting, but doesn’t that sheet look cramped? Would the scout have to record the frisbee count after the match is over? To me, it is better to have enough space in the boxes for the scout to make tally marks for frisbees during the match, this makes it easier for them to focus on what is going on on the field.

You’re right. It does look a bit cramped but when you print it out, it’s more than enough space for tallies.

This is a nice, complete, compact, sheet; I like it. Do you put the data into a computer for analysis & comparison between teams? If so, what do you use? And what did you use to generate it? It looks Excel-ish, but it’s worth an ask.

For those concerned about space for hash marks – reduce the width of some of the columns that can’t possibly need a slew of tallies (like all of the auto goal columns and the pyramid goal) and use the space to add width to the 3 other teleop goals. It’s not as pretty, but functionality has it’s own aesthetics, right? :rolleyes:

Thanks! We do not use computers or any other means to mass-analyze data. That’s one of the benefits of having one sheet per team. It reduces the need for a system to rank teams. When we have pick-lists meetings, we go through each team and put them into one of three categories based on their stats and gameplay: bottom, middle, or top. We then split each of those three categories into bottom, middle, or top.

And, yes, we did use Excel to make this sheet.

Computers can be helpful to calculate averages for individual teams, though. Which is one of the things we use to put teams into the first-level strata.

What do you do to help reduce the inevitable differences in “driving level 3” between different scouters? And looking at the sheet again, I realized that I missed that you don’t record any defense; how come?

I’m of the opinion that qualitative information about each robot is more useful that this numerical data. We used to use custom Nintendo DS programs to scout, then loaded the data into an excel spreadsheet. The problem with that is that doesn’t help at all during the competition, only during alliance selections. Even then, it doesn’t tell you much about how the robot plays and how well it can fit with your alliance.

This is what the notes section is for.

Our students are well aware that pick lists are based off of qualitative and quantitative data.

I think neither is sufficient. I want a shooter compatible with my shooter, but I also want the highest-scoring shooter when there’s more than one that’s compatible with ours. And if there are two that are about equally-high scoring, I want to know which one is more accurate (meaning they may have time to do something else).

I don’t want a 2nd 42-point autonomous robot on my alliance if they’re picking up the same extra 4 frisbees that we pick up. But I quite possibly might want to pick them anyway if they’re almost as good a teleop scorer as the best one available…

Lots and lots of choices. It’s pretty easy to get more data than you can usefully analyze; unfortunately we’ve been pretty “good” at that over the years. :ahh: But every year we get better, and part of what’s helped us end up with more useful information (instead of extraneous data) is figuring out how to quantify factors & get them into a spreadsheet for further analysis.

I agree that number-crunching with computers can be very helpful and it is something we might look into doing on Friday night. Average score and shooting percentage are two very important stats that can be difficult to deduce from raw data.

Also, for the “driving level”, the numbers are loosely based off the numbers of years that person has been driving (1= first year, 2= second year, 5= greater than four years!, however this is more of a qualitative stat than it is a quantitative one.

This beats the heck out of any other paper only scouting system I’ve seen before, kudos to that.

I notice that you’re trying to keep track of fouls, how do you plan on doing so? Since they went to the real time scoring with fouls last year, they no longer announce the fouls at the end of a match. We found that even experienced scouts were unable to track all of the other robot actions going on and still be on top of the fouls the entire time. Technical fouls are still easy because they are announced at the end of the match. Not sure if we’ll be tracking fouls this year. While it is important, we’d rather have no data and not have the scouts worried about it than have very misleading data which misrepresents teams’ actions.

Quantitative data at least serves as a good check against qualitative data. Scouts of all ages are more likely to write glowingly of a veteran powerhouse underperforming as they are likely to be derogatory towards a rookie that may actually serve as a great 2nd pick.

I guess I’m confused by the alliance/opponent part at the top left. This is meant to track a team’s progress throughout an event, up to 12 qualification rounds, right? Why is there not a listing for the 12 different alliance/opponent groupings? Or leave out the alliance/opponent frame altogether?

Emmett, Taylor is correct here. While you don’t have much space left on the front, it is easy to get double sided sheets printed. If you move pit scouting to the back of the sheet, you can allow more space for alliance partners/opponents for each match.

The reason to do this is to check quickly without the match schedule, which strong/weak teams the team being scouted played with/against. This allows you to figure out if results from a given match are due to strong defensive bots, floor loaders stealing discs, etc…

Good point, I totally missed that! Thanks Taylor! Akash, good point about moving pit scouting to the back. We might also move the field drawing to the back too, giving more space for notes. We can also use the extra space on the front to increase the sizes of some of the boxes, giving more space for tallies, as Mike suggested.

I’m sure sharing the source excel file will also be appreciated. My team will see your work so far. I hope it ignites their interest in scouting.

After we update it with the previously mentioned corrections, I will upload the Excel file.

I’m really glad that this sheet was received so well by the community. As a second year team, scouting was not a priority last year, but we’re hoping to make it better this year.

This was our 2012 sheet:


and 2010:

If you go through 2010 through 2012, you can see the evolution of what our scouts like.

I really like the way your sheet is organized. With the values for a given qualifier in a clumn, it should be easy to pick out increasing trends. I think it also looks a lot easier to compile at a glance than the sheets we have been using.

Our scouting sheets are primarily to support alliance selection and to correlate some calculated parameters we track. We have another scout doing “match scouting” which is where we specifically target partners and opponents and the behaviours they can offer.

Overall, I really like your sheet and will ahve my scouts check it out. I love the 1 sheet/team pencil paper method and have found it very effective. Beware in alliance selection that you don’t accidentally loose a sheet. Make sure you have a couple of team lists to cross reference.

If you expect to write on that field diagram during the match you’ll probably be better off keeping it on the front. Back-n-forth page flipping will complicate your scouts’ job.