📈Scouting Analysis

Obviously, the first step is the collection of raw data. Without this strong foundation, no amount of formatting will help out your team. As previously stated, my favorite method is paper scouting. I believe it is more reliable and gives more notes (for information about why this is important, see Analysis).

It is always best to have a dedicated scouting sheet so the scouters know what to fill in. Obviously it needs to have the points scored for the game, but to get a better idea of the team it is a good idea to include their defense, penalties, and their misses/failures.

Of course the actual scouters are equally as important. We find that unenthusiastic scouters give unenthusiastic scouting. Therefore, it is best to find scouters that want to scout, or else some of the data will be subpar. Another source of subpar data is overtired scouters. If possible, scouting should be split into two shifts of 6 to give some rest to the scouters, and so they’re not sitting around the whole time.

With this data, sort it into files by team to input the data and access it later (again during analysis).

By far the most annoying, frustrating, tedious process of all. Essentially this step is just typing all the data into a spreadsheet, which can take an unreasonably large amount of time. A large part of this relates to the content of the spreadsheet. Our spreadsheets are meant to do as much of the computation as possible. This entails manually linking scores in the case of defense, and large amount of scrolling to find specific teams. Overall, this is the most important step. As tedious and pointless as this may seem, while standing on the field trying to pick teams, this is critical. The data should be on one main computer, and preferably be inputted throughout the competition to keep better track of the teams. This way you can use your data throughout the competition to boost your score.

This step brings all your data and forms it into a usable pick lists. Though it’s true that the spreadsheet can do this part, even the most perfect spreadsheet can’t output the best picklist. For example, if a team is using their backup drive team, then their data may be bad even if they are really good. This is why human interaction is necessary.

After the qualification day, the team always meets at night and discusses the teams, whether in a picking position or not. We look over the data, using the notes to get a better idea of the robots, and form our list. The notes let us know whether we can work with the team and how they interact with others; if they don’t work well with you, don’t pick them.