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Unread 07-04-2013, 09:38
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2789_DrT 2789_DrT is offline
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AKA: Janice Trinidad, Ph.D.
FRC #2789 (TEXplosion)
Team Role: Mentor
 
Join Date: Mar 2011
Rookie Year: 2009
Location: Manor, TX
Posts: 15
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Re: need help with defense with formulas for match scouting

Point differentials and number of blocked shots only tell part of the story because a couple variables affect point differentials and some of the best defensive tactics don't involve directly blocking shots.

It's also hard to identify all the teams that are prepared to play excellent defense because some teams who play great defense in the elimination rounds actually play offense throughout the qualification matches.

In addition to a good drive train, good blocking devices, and a heads-up disciplined drive team, teams that are ready to play good D are backed up by very good scouting systems. When my team allied with FRC 118 in the Lone Star elimination rounds, we had the opportunity to look at their scouting data and we were amazed by the amount of valuable qualitative data they collect on teams. FRC 118 has a very high scoring machine, but they can switch to very effective defensive play and can coach allies to up their defensive game because of their scouting data.

Seeing their system inspired us to revamp our scouting system prior to our next Regional and it has helped TREMENDOUSLY. In addition to all the quantitative data that teams collect, our scouts also gather favored robot drive patterns, favored feeds, places where robots shoot and accuracy at each spot, etc. This info helped our drive team strategize with our alliance (Exploding Bunny Appreciation) to upset some really high scoring alliances at the Alamo Regional.

Moral of the story: If you want to quickly ID some teams that are preparing to play excellent defense in the elimination rounds, send a super scout into the stands to peek at the data that other scout teams are collecting on robots. In addition to quantitative data, look for qualitative data that's designed to give drive teams a clear picture of the driving habits of their competitors and systems that get that data to the drive teams in time for them to prepare for upcoming matches.
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2013 Alamo Regional Winner (with 2468 and 4063)
2013 Lone Star Regional Winner (with 118 and 148)
2013 Hub City Regional Finalist (with 16 and 4063)
2012 Utah Regional Entrepreneurship Award
2011 Chesapeake Regional Entrepreneurship Award