Week 9 Targets and Touches

John Bush
November 9, 2019

Week 9 Targets and Touches

This report, Week 9 Targets and Touches uses metrics on Team, Position, and Player targets and rushing attempts. The more opportunity is the higher the chances for collection of your Team’s fantasy points. This information is meant for deeper thinking and note-taking. If you have deeper benches these metrics allow you to jump into new player shares early for gambling. That is how I use deep benches. I continue to rotate players at the bottom.

Lineup Diary

I would use these Week 9 Targets and Touches metrics with my rankings and snap reports to finalize the week 3 lineups. This process is not automatic and easy. I am urging all players to dig deep into their decisions. There is plenty of software to automatically set-line ups. I suggest using a notebook and record your process. This lineup diary can be useful for you to spot weaknesses or strengths in your game by the week or season.

Rankings Link:fantasy-football-week-10-rankings

Snaps Report Link: week-9-snaps-report

A Visual Plot of Target Averages Vs Weeks 1 to 9

I have discussed my top-down approach to data analysis. These bigger views allow a deeper feel for the deeper data. Below is the table of Team Target Averages using the first 8 weeks of target data. Week 8 Targets and Touches.

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The following table in metrics Blue to Red (Highs to Lows) shows each Average of Team Targets is shown and CAR/LAR/ATL/CIN/NYG/NE/PHI/NYJ/LAC/DAL have been the season’s leaders so far!

Additionally, the Scaled Team Averages show each Team’s metric vs the League average. Key on the extreme teams for DFS plays this week.

Plot to See Team Scaled Target Averages Weeks 1 to 9

Visualize the High vs Low Passing Teams. Commit to memory for increased speed to analyze lineups and DFS plays.

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A Plot of DIFF and LATE/EARLY Targeting Metrics By Teams

Tracking Team changes are useful for your lineups and DFS plays. The colorization of week 1 to 9 target averages for each team allows a scan of the trends for that team.

The DIFF metric is also included and that measures changes within a team’s last 2 games. Note ATL/CIN/NE/NYJ/DAL were a higher targeting team in the last 2 weeks. On the other hand CAR/HOU/CHI/ARI/OAK/BUF/LAR were the teams that have declined within the last 2 weeks.

The last column is the Late vs Early Targeting metric that captures the last 4 weeks vs first 5 weeks. I sorted the team column beside the DIFF and LATE/EARLY by high to low LATE/EARLY numbers.

Note TB/HOU/CIN/LAC/MIN/TEN have improved in targeting recently.
LAR/ATL/KC/PIT/ARI/DEN/BUF/OAK have declined recently.
Why? New Trend?

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Targeting Rate Weeks 1 to 9 Team Level

Targets Per Snap gives a speed based input into a Team’s targeting activity. Faster targeting should imply more Fantasy Points generated. Key into those players on the faster teams.

NO/KC/MIA/ATL/DEN/NYJ/CIN/OAK are the top fast targeting team. I note the teams I did not expect in here. MIA/NYJ/CIN are the teams with poor win records but their pass-catchers could be a key asset from these teams.

BAL/HOU/BUF/SF/PHI/SEA/IND/ARI/LAR are the opposite types of teams. On average the pass-catchers from these teams might be under-used and could improve until favorable game scripts!

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The Plot of Team Scaled Targeting Rate Weeks 1 to 9

Note the Teams within the metric landscape. Consider as a factor in your week 10 decisions

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The Plot of Team Scaled Targeting Rate Differences In the Last 2 Games and Late vs Early Difference

Focus on the recent and longer-term changes within Team targeting rates.

DEN highest 2 game improvements! New QB? Also, see MIN/GB/JAX/TB/NYG/LAE/SEA/PHI/SF as improving. NO/KC/DAL/LAC/ARI all declined in targeting rates.

Note the longer-term changes in NO/DEN/DAL/LAC/JAX/TB for improvement while declines in CIN/OAK/PIT/BAL/TEN/KC/MIA.

Juggle these metrics with other data streams!

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Teams With Positional Targeting Metrics Weeks 1 to 9

I provide a broad landscape of data. These tables include:

Weeks 1 to 9 Target Averages.
Average Targets.
DIFF (Difference in Average Targets for that Team’s Position from the Last 2 Games)
Late vs Early DIFFs (last 4 weeks vs first 5 weeks of data-Big Changes)
%TT (Percentage for that Position’s Targets vs Total Team Targets-Usage Metric)
A plot of each team’s positions and their %TT

I use the DIFF to see recent changes. Why? The %TT metric displays the positional usages and level of importance for the Team.

An injury in a weakly used position is not as critical as a strongly used position. Highly used positions imply the high significance of players. Also, a change in players in weakly used positions can inspire new performances within the team and you can catch on before others.

Focus on the extremes and unusual %TT!

ARI_ATL_BAL_BUF

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CAR_CHI_CIN_CLE

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DAL_DEN_DET_GB

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HOU_IND_JAX_KC

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LAC_LAR_MIA_MIN

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NE_NO_NYG_NYJ

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OAK_PHI_PIT_SEA

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SF_TB_TEN_WAS

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Summary Data Table and Plots of Positional %TT

These figures highlight the landscapes for each position. The extremes will be of critical interest. Highest in Green and Lowest in Red! Move-in PPR to the higher targeting teams.

These positions are sorted by %TT and that key us to the value of each position to their team.

Note the Red and Green Blocks to highlight the longer term changes in RB importance with the Teams as based on Late vs Early Differences.

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ARI/CHI/PIT/NYJ/WAS/JAX/GB/MIA/LAC are Team’s where the RB position is very valuable in the passing game.

Running Backs

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SF/BAL/OAK/PHI/KC/NYG/TEN/CAR/ATL are Team’s where the TE position is very valuable in the passing game.

Tight Ends

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TB/DET/CIN/CLE/LAR/HOU/NE/BUF are Team’s where the WR position is very valuable in the passing game.

Wide Receivers

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Player Centric Target Metrics within Team Environments

Following up on the positional analysis above, I turn to player level metrics for a deeper understanding. I sorted players by %TT within the position. Find the extremes and pecking order for injury.

A great reference for Week 10 in case of injury, just come back here and see the next man up. Also in high use situations, stashing key handcuffs is a solid approach in deeper bench teams.

Now is the time to set your teams for the playoffs!

Team
Position
Players
Weeks 1 to 9
Average Targets
%TT
Late vs Early

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Player Average Targets and %TT by Position

I also like to see the player within the position outside the team. What is the player’s success relative to others in that position in terms of %TT? One might propose that this list is the order of handcuffs as well. CMC’s handcuff could be worth more than 6% than Karma’s handcuff etc. Just a mental exercise to craft stashes in deeper leagues.

I love to generate the various levels of Target metrics to “catch” all the data for interest. I use to think about my teams, drop/adds/and lineups. All players should chase multiple data streams to develop a full landscape in my thinking.

One might jot down key observations by teams, positions and or players. Then try to fit these elements together. Practice and note in your playing diary (Handicap your own decisions). Please let’s move away from the tire line “They told me to do it”!

Own your line-ups!

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RBs

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TEs

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WRs

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Team Level Running Back Average Touch Metrics

As RBs can rush as well as pass-catching, we must look into the combined role they have on a team. The “touches” metric tracks this RB activity and enables a deeper view of the Team’s RB usages.

This table presents the Team Level Running Back Average Touches from Weeks 1 to 8.

High RB Touch Teams- Blue Stained

DAL/JAX/DEN/SEA/HOU/TEN/CAR

Low RB Touch Teams- Red Stained

TB/ATL/MIA/BUF/OAK/DET/BAL/KC

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Plot of Team Touch Averages

Nice Team RB Touch Profiles. Judge the team differences for handcuffs, DAL is number one and Pollard may be the top handcuff to have etc!

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Plots of Last 2 Game DIFFs, and Late vs Early Season Touches

DIFFs capture recent changes – Purple Line. Above 0 increasing Touches/Below 0 decreasing RB Touches. Look for extremes and unusual patterns. Focus on improving Teams!

Average Touches, Scaled Touches, and DIFFs. These metrics are a landscape view of the leagues and teams. High Touching Teams would have significant RBs in PPR while Low Touching Team would not. Focus on RB committee structure and pecking order in case of injury as these new players should inherit a nice situation.

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Players RBs (Within Teams) Touches Weeks 1 to 9, Average Touches, and % Team Touches

Looking within Teams for RB pecking orders, DIFFs in touches, and Averages in Touches. These give us clarity for the Teams RB crew. Look for new improving players or declining players. Note the extremes and then add or drop players accordingly.

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Players RBs (Touches Weeks 1 to 9, Average Touches, %TT, DIFFs, Late vs Early Metrics)

Players have been sorted by %TT from High to Low (Green to Red). Focus on all the layers for handcuffs and those RBs with independent value as well! Use DIFFs to catch new players on the field etc. Use the Late vs Early to “see” big changes.

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Extremes in Late vs Early in RB Touches

Concerns for Michel Montgomery/A Jones/Lindsay/Fournette etc

Interesting improvements from Connor/Samuels/Drake/Singletary/Bell/Gordon etc