By John Bush

Targets Per Snap Weeks 9 to 1 2017

Targets Per Snap Weeks 9 to 1 2017 analysis starts with a landscape view of each team’s total number of players targeted by the week. 

How player concentrated are each team’s targets in weeks 6 to 9?

Interestingly, in the following table, the LEAST concentrated targeting team was CAR, PIT, CHI, and NYJ and the MOST concentrated targeting team was PHI. 

I used this data to look for adding players or in trades.

The teams at the top of the graph are distributing their targets in weeks 6 to 9 to more players. (PHI, DEN, OAK, and SEA HIGH). Note that CAR, PIT, CHI, and NYJ might be sources for most vaualable 3rd level players that thought!

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Targeting Concentration Per Team- #Players Targeted

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Number of Players By Team Targeted By Position, Week and Team Player Usages

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Team Usages of Each Position by Player Counts, Weekly, and Seasonal Total

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 Running Backs

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Tight Ends

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Wide Receivers

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Positional Targets Per Snap and Changes from Weeks 6 to 9 vs Early Season (W2 to 5) 

How has the Team’s Targets per Snap changed? Why? Two important questions!

Fantasy Players get locked into ideas and patterns from the early season (Confirmation Bias) as well as last week (Point Chasing Recency Bias). 

**”Confirmation bias also called confirmatory bias or myside bias is the tendency to search for, interpret, favor, and recall information in a way that confirms one’s preexisting beliefs or hypotheses. It is a type of cognitive bias and a systematic error of inductive reasoning. People display this bias when they gather or remember information selectively, or when they interpret it in a biased way. The effect is stronger for emotionally charged issues and for deeply entrenched beliefs.” ** Wikipedia Confirmation Bias

Look closely at all the critical team depth charts with all this data and keep your early season Bias in mind to be ready to change and move onward!

This material is required metrics for your bye week replacements coming up!   What team needs your investments from drop/add pool? 

Running Backs

DEN, IND, KC, and BUF Upticks in RB Targets/Snap!

LAR, NO, SEA, PIT and JAX going down!

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Tight Ends

IND, CLE, JAX, NO, CIN and CAR up

GB, LAC, BUF, NYG, MIN and SEA down

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Wide Receivers

TEN, BUF, DET and GB (Hum) up

MIA, LAR, and CHI down!

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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!

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

The data need 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

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Tight Ends

 

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Wide Receivers

 

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Team Positions and Players Normalized Targets Per Snap (100 to 0) With 9 Week 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?

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