Speedscout16 Scouting App (And R Analysis Code)

[Jacobo3170]

This year I developed an iOS scouting app called Speedscout16 for any team looking for a simple and easy scouting solution. (It was also recently ported to Android by David Turner 1756). It allows scouters to effortlessly email (or airdrop…) their scouting data as a collection of CSV spreadsheets. (Picture of example spreadsheet attached...)

Along with this app, my team will also be using this R code to analyze the collected data. If you are new to R (like me) here is how you would run this code:

1. Download both R and R studio) onto your computer.
2. Download the code “As ZIP” from Github
3. Designate your working space/directory where you will store both the code and statistics (e.g. Your desktop) and drag the downloaded folder to this location. (Change the name from “2016-R-Code-master” to “2016 R Code”)
4. Create a folder in this location (step 3) called “FRC 2016 All Raw Data” and move all of your raw Speedscout16 data into it
5. Open only the .R script named “FRC 2016 Master.R” in R Studio (left click and select “Open with” -> R Studio) and change “myDir” to your designated hard drive location (Created in step 3)
6. Load the .RData function “to.numbers” into your environment (“Open with” -> R Studio) and select “Yes”
7. Download the “Calibrate” Package for plotting (R Studio -> Tools -> Install Packages - > “calibrate” -> Install)
8. With “FRC 2016 Master” open in R Studio, check the box next to “Source on save”
9. Save “FRC 2016 Master” (If errors such as “50 more errors” and “*teamnumber* already exists” come up in the terminal, disregard them).
10. (Click on “Plots” to see graph of every team’s Defensive capabilities and their average shooting pts per match)

[Dkt01]

Thanks for sharing, Jacob! At the Central Illinois Regional, Argos used the app and some scripts I wrote to collect gmail messages from the app into a Google spreadsheet (code available on Github). I left my laptop running off-site to monitor our gmail account for new scouting data which we could then use to strategize in upcoming matches.

Our scouters found the app easy to use and much more enjoyable than our previous paper method, so I ported an Android version(code available on Github) that we will be using in conjunction with Jacob's iOS version at Midwest Regional and Championships. The two apps produce the same data, so any parsing and collection tools can run on data from both versions.

Good luck teams!