Week 4 Targets and Touches

Week 4 Targets and Touches

Week 4 Targets and Touches. My weekly routine is analyzing various fantasy football metrics including:

  • Snaps per Second of Offensive Possession. See Below

  • Week 4 Snaps Report

  • Targets and Touches

  • Vegas Over Under Lines

  • Defense Against the Position

  • My Rankings with Uncertainty Analysis. (Coming Saturday)

We must deal with decisions under uncertainty in fantasy football.

**A range of potential futures can be identified at level three uncertainty. A limited number of key variables (See Above) define that range, but the actual outcome may lie anywhere within it. There are no natural discrete scenarios.

** https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/strategy-under-uncertainty#

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Week 4 Team Target Averages and Scaled Targets vs League Average

Week 4 Targets and Touches. I always begin in a top down approach and in this case, I focus onto the top target generating teams. Clear value in PPR scoring! I then highlight the extremes from High (green) and Low (red) of all the NFL teams.  Green X marks the High Target Efficiency teams.

I also consider the amount of data and our floor is not solid with just four weeks of data but the more weeks then the better for these metrics. I used average targets and targeting efficiency (targets per second) as an way to highlight team targets over the last 4 weeks. 

DAL is the clear top at 51.4 target efficiency and Dak has been delivering. WAS is number 2 at 41.1 with CAR at 32.4 and CIN at 34.1 and Burrow is pass-happy and will add value to pass-catchers on CIN (Tee Higgins?). If Burrow can move forward he will be a solid playoff QB. Watch.

DAL/WAS/CAR/CIN/NE/PHI/ATL/LAC  are also pass-happy teams. Add Value to their pass-catchers! Note the Green X marking the tops in Team Targeting Efficiency. These are the team to focus on pass-catcher depth. 

The flip-side are BAL, MIN, CLE, IND, LV, SEA, and DET.  Substract value from their WRs. Rushing is more favored. Stock-pile RB handcuffs etc. These teams at or below -0.5 in scaled average targets. Caution in PPR leagues and DFS plays. I note the SEA is in this list as they are a highly competitive team. 

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Scaled Team Target Averages vs Targeting Efficiency Weeks 1 to 4

Week 4 Targets and Touches. The visual view of the team targets is shown below. I like to graph data points in comparison of the league average. This allows me in a glance to see what teams were above or below average of Targets.

Additionally, I colorized the bars with green vs red. Consider the reasons why and is this week going to be different? Finally, use Vegas and Defense against the Positions (DAPS) to investigate that question! 

I present Scaled Team Target Averages first to showcase Teams across the league vs league targeting averages. We must know the extremes for our finger-tip knowledge in line-ups and DFS plays. 

KEY Extremes in Green and Red Bars of High to Low Targeting Teams. Move in PPR leagues toward the green and away from red teams on average. (Yes other data can and will modify that trends but we start here first). 

Additionally, consider the why? What is going on in the top and bottom teams? Game Scripts etc. and is there a change this week?

Additionally, team targeting efficiency is interesting for some team such as HOU which is low in target averages but efficiency with their passing. The opposite is CAR/LAC which are high in average targets but low in targeting efficiency? Questions remain. Is HOU going to improve vs CAR/LAC going to decline? Watch. 

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Targeting Week 1 to 4 vs Team Positional Usages and Week Differences

Week 4 Targets and Touches. I continue a drill down to see each team’s positions in terms of targets weeks 1 to 4, usages and improving/declining by DIFF metrics. The actionable data here is what you can deduce from the trends.

Additionally, This landscape view is superior to what happened last week only. This broad view is a skill needed to improve your Fantasy Football Playing.

I look for extremes and unusual/surprising metrics. In these data, Teams are going to grade out higher in WRs (more of them) so if a team is overusing its RB or TE then the WR usages will be lower and standout.

Also, I include a visual bar graph of the team positional usages as well. Give this a soft scan for developing opinions for DFS and lineups. Each block of data included 4 teams at a time. Find the interesting!

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ARI/ATL/BAL/BUF

  • BAL High TEs
  • BUF BAL Low WRs

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CAR/CHI/CIN/CLE

  • CAR Low TE  with High RB
  • CHI/CIN Low WR

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DAL/DEN/DET/GB

  • DET Low WR but High TE
  • GB High RB Low TE

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HOU/IND/JAX/KC

  • KC Low RB vs High TE
  • JAX High RB

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LAC/LAR/LV/MIA

  • LV  Extreme TE and Low WR

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MIN/NE/NO/NYG

  • NE No TE Usage with Extreme WR
  • NO Extreme RB
  • NYG All Positions Used 

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NYJ/PHI/PIT/SEA

  • PHI High TE and Low WR
  • NYJ Low RB Higher TE

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SF/TB/TEN/WAS

  • SF Extreme TE vs Low WR
  • TEN Low RB High TE
  • WAS WR/TE Same

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Targets and Usage Efficiency Within Positions.

Week 4 Targets and Touches. You must also consider the player’s ranking among their position.

High in the team but Low in the league is different than High and High.

That should give your concerns for league lower players in targets. Weak teams are known to have poor depth in PPR scoring. Scan through the positions and find the unusual and extremes. ** Assuming FF data is normally distributed?

 In an extreme value analysis, extreme events are defined to be those observations in a sample which are unusually high, or low, and are therefore considered to occur in the tails of a probability distribution.
Standard statistical methods are designed to characterize the mean behavior of a process or data sample and are therefore not generally useful for capturing this tail behavior.
https://www.lancaster.ac.uk/maths/research/statistics/extreme-value-statistics/

The following positional based tables have been sorted by Total Season Team Targeting Usages vs Average Targets

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Running Backs

  • Top teams in RB Usages are NO/CAR/BUF/JAX/NE/CIN/GB all above 31% in RB usages!
  • Weak RB Usages below 21% coming from TEN/ATL/NYJ/CLE/PIT/KC/BAL
  • Note Dal High Targets but low Usage in RB?
  • WAS/PHI/LAC also relatively high RB Targets vs lower usages. 

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Tight Ends

  • TE Centric Teams (Above 34% Usage) are SF/LV/PHI/DET/KC/WAS/BAL/TEN/NYG.
  • I note WAS and NYG’s TEs are out on the waiver wires if needed.
  • NE/CAR/MIN/ARI/GB/NO/BUF/LAR all below 27% TE Usages.
  • I note the recent TE usage in GB/CAR. Cook in NO hurt?

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Wide Receivers

  • The top WR usage teams are NE/ARI/ATL/MIN/PIT/NYJ/CLE/SEA/TEN who are all above 46%. Key deeper WRs are viable on these teams.
  • Note MIN/CLE/LAR have poor target average yet higher usages
  • DAL/LAC/CIN/KC/WAS are teams with stronger targeting averages yet lower WR usages.
  • SF/LV/PHI/NYG/NO/WAS are poor WR using teams who are using the RB and/or TE to compensate. Beware depth WRs on these teams.

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Team Positional Player Week 1 to 4 Targets, Target Averages, and DIFFs

Week 4 Targets and Touches. I next drill down into these metrics within each Team. Fantasy Football is a weekly Team based game!

Secondly, I added the player usages within their teams for the “pecking order” as well as DIFFs to catch improving or declining players. 

These tables contain:

  • Team
  • Position
  • Player
  • Targets Week 1, 2, 3, and 4
  • Target Averages
  • Last 2 Games vs Early 2 Games DIFFs
  • Weekly DIFFs

I like to use these metrics as a reference in context of Vegas and DAPs. Is the pecking order real? Is the production real and will be replicated this week?

Find the unusual and extreme. I scan and note those. 

My Week 5 Rankings are out tomorrow FYI. 

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Player Based Week 1 to 4 Targeting Usages with DIFFs.

Week 4 Targets and Touches. The team based data is good for within but how does the player stack up across the league at the position?

Again, a highly used player on a league low team is not as solid as you could think. Extremes are your friends in the data game!

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Running Backs Week 4 Targets 

Extremes are of interest.

  • For example,
  • Kamara dropped -10 targets?
  • Burkhead -9 vs White is back +8

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Tight Ends Week 4 Targets 

  • Examples
  • Waller +8 
  • Kittle +15
  • Ertz -5 

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Wide Receivers Week 4 Targets 

  • Examples
  • Crowder back +10
  • Cooper +4
  • Ridley -8
  • McLaurin +6
  • Jeff Smith +9 (who?)

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Running Back Touches with % Rushing vs Receiving (ATTs vs Targets)

Week 4 Targets and Touches.  RBs are the most difficult position in fantasy football to calculate because they both rush and catch. That fact then opens more possibilities within the game. Therefore, we must consider that extra dimension for RBs especially in PPR leagues. 

The easy RB to figure is one that does both catch and rush. The harder RBs are the pass-catcher only types as they are game script dependent. Thus if you have a pass catcher RB (ie Edmonds 71% catching), you must consider the way that game might go. See Vegas and DAPs as a foundation for your thinking. 

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Team Level RB Rushing Attempts vs Targets with Rush/Pass Ratios

Week 4 Targets and Touches.  We must understand the nature of each team towards its use of RBs in rushing and passing.

Firstly, I calculated each Team’s Rush/Pass Ratio and Sorted all teams by that metric.

Next, I did normalize the data so we can directly compare the RB Rushing and Targeted numbers on a 0 to 100 scale.

Thus, TEN is figures are 88 on RB rushing and 7 on Targeting RBs (they not pass to RBs much) vs NYG who are figured at 5.3 rushing vs 53 targeting RB (extreme bias).

  • The ALL IN RB Rushing Teams are colorized in Green and are BAL/TEN/CLE
  • The Pass Happy RB Teams are NYG/MIA/SF/TB in Red
  • The bar graph below the table emphasizes the extremes in the data. 

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Team Level Rushing Attempts vs Targets with Averages. 

It is important to determine each RBs activity in rushing vs pass-catching. Observing the trends is essential for considering this week’s performance. 

These tables contain

  • Team
  • Player
  • Rush ATTs Weeks 1 to 4
  • Rushing Average
  • Targets Weeks 1 to 4
  • Target Averages.

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I go through these data tables by asking questions and determining the answers. Each Players must be addressed.

Time intensive for sure. If you want it on a platter you are not reading this then. Its ok because I do these articles for me as well as my readers. It makes me do the work. I tell my students chop the wood then you get the fire not get the fire first then someone produces the wood? 

Let me narrate for example looking as these metrics. Who is each RB? Rusher/Pass Catcher? Both One or the Other or Neither?

ARI- Drake is the Rusher while Edmonds is the pass catcher. I have heard Drake is a bust. He is a 17 ATT a week guy that may be on a team that scores using other positions. I suspect he is a game script bound rusher and has limited use on tough weeks. But now you know that and now you can use him in favorable situations. It is great that you know this as your league mates just know they drafted a RB early and he is not scoring.

Note in BUF, Singletary Owners should worry about Moss as he is the same RB as Singletary. Weeks 1 and 2 they were the same and with Moss out Singletary assumes the complete show. Sell High or be ready for a decline? Estimate the odds of these events.

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RB Seasonal Rushing vs Targeting Average with Weekly Difference.

We must monitor recent metrics for each player.

I use these seasonal averages to define the RB (Rusher and Pass Catcher/Rusher Only/Pass Catcher Only). The data includes highlighted players who are the rushers only with an orange color for reference.

I also note improving or declining players.

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Top Rushers vs Top Targeted Running Backs Weeks 1 to 4

Note the interesting. Harris in NE for example.

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