[ngreen]

I have two answers with the first reflecting the goals of FIRST, that is to really test your abilities and to learn new things. I encourage those building apps, networking, automating processes, doing statistical calculations, etc.

And second, ideally for my team, I feel like three things needed to happen within scouting which is to utilize the FIRST FMS stats fully (develop automated processes and visualizations to pick out not only the best teams, but overlooked teams for potential 2nd picks), develop qualitative intelligence of the teams (through pit scouting, watching matches, drive team interactions, etc), and form bonds with the other teams.

You can do some pretty amazing things with the FIRST ranking data, a copy of Tableau, and some Excel magic (and also R). Our quantitative scouting ended up being scraping ranking data (which includes auto, defenses, goals, and scale points), calculating an OPR-like value for each of those, and visualizing in Tableau. It is very simple to filter and sort in Tableau if you like a more exploratory way to identify teams, or you can pre-build your analysis.

We looked at the data Friday night (after 8 matches) and Saturday (after 11). In retrospect, I would have liked to share information earlier between the quantitative and qualitative scouts. We did this at the end of the day but could have done it another time and had an extra iteration before the scouting meeting. By sharing information, I mean that from the data you can start to see which teams would be best to watch more closely (particularly for things that aren't captured well in the data -- like breakdowns, driver skill, etc), and that from observations you may find some teams that don't pass the eye test that isn't captured in the data. For example, I watched a robot that rated 14th by OPR-like stats in one of their final matches seem slow and indecisive.

Every team is capable of scouting in this way. Certainly, teams with more data have an advantage, although I think slight as sometime it doesn't make the picture clearer than aggregate data and the eye test. Next step to use the free data fully is to pull all the match data and analyze it. A team's ability to capture the tower was an additional thing we looked for in the best teams (with low goals being important, but not counting as much in goal score).

I regret this year not having as many students working with the data for scouting, given the educational opportunity. We did switch systems following our first regional where we were paper-based. I'd like all the scouting team students next year to know how to extract the data from the website, be able to do basic tasks in Excel, be able to build their own dashboards/plots in Tableau, and more but it is a start.