By John Bush

Targets Per Snap Week 11 ( 10 to 1 2017)

Targets Per Snap Week11 (10 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 1 to 10?

Interestingly, in the following table, the most concentrated targeting team was CAR, PIT, CHI, and NYJ and the least 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 10 to more players. (SF, DEN, CLE, and IND). Finding a 2nd or 3rd level deep player there may be more valuable than commonly thought!

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Targeting Concentration Per Team- #Players Targeted

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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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TEAM Level Average Targets and Targets Per SNAP By Week

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Team and Positional Level Average Targets and Targets Per SNAP By Week

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Positional Targets Average and Targets Per Snap

Running Back

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TIGHT ENDS

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Wide Receivers

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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 or last week 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? 

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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 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!

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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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Interesting “Non-Popular” Players as noted by the Targets Per Snap Data Patterns

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