TARGETS Per SNAP Week 13

Slide1

By John Bush

TARGETS Per SNAP Week 13

Targeting Concentration Per Team- #Average Team Targets By Week

  • Landscape view of each team’s total number of players targeted by the week. 
  • Sorted by Week 12 Data! 
  • How player concentrated are each team’s targets?

Slide02

slide03.png

DEN, SF, CLE, OAK, TB, and PHI have spread the target to large numbers of players per weeks.

PIT, HOU, NYJ, CAR and TEN have concentrated their passing targets. 

____________________________________________

Targets Per Snap Week 13 (12 to 1 2017)

  • AVG Targets/Players By Week and Team

  • Sorted by Week 12 Data

Slide05

Slide06

PIT sits alone at 5.6 Targets per player followed by MIA and HOU. Those 3 teams are clearly in tiers above the other teams! 

——————————————————————

Team Targets Per Player Usages of Each Position by Weekly and Seasonal Totals

The Targets Per Snap Data was Normalized to a scale of 0 to 100 (Low to High) and color coded! Team Usages were calculated and displayed. 


Slide08

Slide09

slide10.png

Slide11

Slide12

Slide13

slide14.png

Slide15

——————————————————————–

Positional Targets Averages and Usage By Team and Weeks 8 to 12 (Recent)

Running Back

Slide17

Slide1

SF, GB, NO, BAL, and PHI Have used the RB in the Passing Game

ATL, TEN, HOU, and MIN have used the RB very little in the Passing Game

——————————————————————–

TIGHT ENDS

Slide20Slide21

IND is clearly a separate tier in TE usages! SEA, TEN, HOU, KC, NE, and CLE are using the TE higher than most

PIT, NO, GB, CHI, and BAL have not been using the TE a lot! 

——————————————————————-

Wide Receivers

Slide23Slide24

ATL and MIN are at the top of the league!

IND, KC, SF, and CLE have been under-utilizing the WRs. 

——————————————————————-

Players Normalized (100 to 0) Targets Per Snap By Week and Avg! 

My normalized numbers allow judgments across teams and positions in trades, adds, drops or lineups! Not if a player has one snap and is the targeted they will earn a perfect score of 100. See Taiwan Jones! You must downplay such extreme data as the sample size is too small.

By Placing the Data on a 0 to 100 (worst to best scale) we can judge across the positions as well as internally within a team or position!

Trade help? I would not trade an RB or for a TE with a lesser average unless they figure to explode in the playoffs!

The data needs context! You must think about what data I present! I would certainly use recent data to predict this week but a landscape view is the context for a deeper based though out plan!

——————————————————————–

Running Backs

Slide26Slide27Slide28Slide29Slide30

 ———————————————————————————-

Tight Ends

Slide32Slide33Slide34Slide35

 ——————————————————————

Wide Receivers

 Slide37Slide38Slide39Slide40Slide41Slide42Slide43

——————————————————————–

Team Positions and Players Normalized Targets Per Snap (100 to 0)  Week 7 to 12 Averages

Team context is the final view needed for your decision! What is the position of the player you are considering? What is their recent role and usage?

Slide45Slide46Slide47Slide48Slide49Slide50Slide51Slide52Slide53Slide54Slide55Slide56Slide57Slide58TARGETS Per SNAP Week 13 Slide59Slide60Slide61Slide62TARGETS Per SNAP Week 13 Slide63TARGETS Per SNAP Week 13 Slide64Slide65Slide66TARGETS Per SNAP Week 13 Slide67TARGETS Per SNAP Week 13 Slide68Slide69Slide70Slide71TARGETS Per SNAP Week 13 Slide72Slide73Slide74Slide75TARGETS Per SNAP Week 13Slide76

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>