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Kingsley is doing a good job of dreaming out, including about virtual reality – which he used while with the Tampa Bay Buccaneers, and machine learning. He does want to keep output from all of this data simple per Lovie’s desires for simplicity.
Data Available
This seems silly to put but... football For those who aren't familiar with football, games are split into plays. Teams alternate offense and defense, and have different players for each side. There are several players for each position who will rotate in and out of the game between plays based on the situation (i.e. your big slow guy might come in if you only need 1 yard to score, but a smaller faster guy if you need a long run). So only 11 people on the field per team at once, but ~52 players on a team roster in total.
You have 4 downs (plays) to gain 10-yard increments and if you can't advance 10 yards in those 4 plays, you turn the ball over to the other team's offense and they try to go the other direction. If you do advance, you get "first down" and 4 more chances to get 10 MORE yards... repeat until you either score (reach the endzone at one of the of the field) or you turn the ball over.
The defensive data that was shared can be split into a few groups:
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- analyzing matchups to see what defensive players perform well regularly against particular formations or personnel types (and not well)
- look at performance across game - does player do better early on, late in game, under pressure?
- is a player more effective in certain locations and can that be leveraged?
- practice schedule prioritization - what players need to work on especially considering what's coming in upcoming game
predictive analytics
- is the other team predictable in what kinds of defensive formations they choose under certain conditions/against certain formations?
- what is the other team likely to do in response to particular game situations? when can we be more certain of that prediction?
- if we see players X Y and Z enter the game on other team, what plays are we expecting to see?
- how does this player perform in comparable environmental conditions (i.e. does he do poorly in cold night games)?
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