- Why Trevor Lawrence is the Greatest QB I’ve Ever Scouted
- 7 Round 2021 NFL Mock Draft
- NFL Eliminator Challenge: Week 17
- Time to Shine or Ride the Pine: Week 16 Start or Sit
- Week 15 Targets and Touches
- NFL Eliminator Challenge: Week 16
- Week 15 Snaps Report
- Week 15 Rankings With Uncertainty
- Week 14 Targets and Touches
- CFB DFS Week 16 Preview – Day Slate
Week 3 Targets and Touches Report
- Updated: October 2, 2020

Week 3 Targets and Touches
Week 3 Targets and Touches My weekly routine is analyzing various fantasy football metrics including:
- Snaps per Second of Offensive Possession. See Below
- https://www.fakepigskin.com/2020/09/23/snap-report-week-2/
- 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.
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See my article below!
Snap Report Weeks 1, 2, and 3
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Week 3 Team Target Averages and Scaled Targets vs League Average
Week 3 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! Highlighting the extremes from High (green) and Low (red) of all the NFL teams.
I also consider the amount of data and our floor is not solid with just three weeks of data but the more weeks then the better for these metrics. I used totals as an way to highlight Team targets over the last 3 weeks.
DAL is the clear top at 139 targets and Dak has been delivering. CIN is number 2 at 136 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.
PHI, ATL, and KC are also pass-happy teams. Add Value to their pass-catchers! Note the drop off in the scaled target metrics of 15 KC to BUF and CHI at 9!
The flip-side are BAL, MIN, CLE, NE, and LAR. Substract value from their WRs. Rushing is more favored. Stock-pile RB handcuffs etc. These teams at -17 in scaled targets. Caution in PPR leagues and DFS plays.
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Scaled Team Targets Weeks 1 to 3
Week 3 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 Targets 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?
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Targeting Week 1 to 3 vs Team Positional Usages and Week 3 vs 2 Differences
Week 3 Targets and Touches. I continue a drill down to see each team’s positions in terms of targets weeks 1 to 3, 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
For example BAL loves its TEs? Yes as they are used at 29% of team targets. Andrews will bounce back. But BAL’s WRs then are going to be starved for targets and deeper WRs will have lesser value.
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CAR/CHI/CIN/CLE
CAR does not use its TEs.
CLE uses RB and TEs vs WRs.
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DAL/DEN/DET/GB
GB nice use of RBs
DEN likes TEs
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HOU/IND/JAX/KC
IND uses RBs
KCs nice TE usage
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LAC/LAR/LV/MIA
LV really uses TEs and Forgets about its WRs?
MIA uses RBs/TEs
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MIN/NE/NO/NYG
NE never used TE
NO loves RBs
NYG focus less on WRs
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NYJ/PHI/PIT/SEA
PHI strong TE usage thus weak WR usage.
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SF/TB/TEN/WAS
SF/TB really weak WRs but nice on RBs.
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Targets and Usage Efficiency Within Positions.
Week 3 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 Usages with week 3 vs 2 differences. X marks the DIFF that is extreme. Focus on the why?
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Running Backs
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Top teams in RB Usages are NO/SF/NE/IND/TB/GB/CAR/LV all above 26% in RB usages!
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Weak RB Usages below 17% coming from TEN/HOU/BAL/DEN/LAR/ARI/WAS
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NE/DAL/LAC/WAS/DEN improving?
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CAR/MIA/CIN declining?
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Tight Ends
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TE strong using Teams are LV/PHI/TEN/BAL/SF All above 27%
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Weaker TE using Teams are NE/CAR/BUF/ARI/ATL who are below 14%. Concern for Hurst in ATL?
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Improving TE Using Teams? BAL TB CHI DET SEA GB. Note Foles in CHI to Graham? Gronk getting TE love in TB etc.
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Declining TE uses occurring in LV MIA HOU and CIN. CIN elected not to use its TE in week 3?
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Wide Receivers
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The top WR using teams are BUF/ARI/NE/ATL/ATL/CAR/LAR all being above 67% in WR targeting usages. Note NE had an extreme week 2 so maybe a mirage!
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The lowest teams in WR usages (avoid their deep WRs?) are LV/SF/NO/PHI/TB. Note the gap between the bottom 3 and then next 2. Brees is short throwing to RBs/TEs and MT has been out. He does not trust other WRs even Sanders?
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DAL/LAC/PHI/LV improving
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NE/CAR/PIT/NYJ/DEN/MIA declining. Note the Thursday night game of DEN vs NYJ here.
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Team Positional Player Week 1 to 3 Targets, Team Usages, and DIFFs
Week 3 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 ad DIFFs to catch improving or declining players.
These tables contain:
- Team
- Position
- Player
- Positional Targeting Usages
- Targets Week 1, 2, and 3
- Total Targets
- Week 3 vs 2 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. My Week 4 Rankings are out tomorrow FYI.
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Player Based Week 1 to 3 Targeting Usages with DIFFs.
Week 3 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 3 Targets and Touches.
Note DJ vs Elliot. Both highly used in their teams but a clear difference in all league RBs (23 vs 11 targets). Big fish in little pond situation. Consider when DJ will be highly targeted might still be lower than Zeke!
Improving- Ekeler is back? 1 to 4 to 11 last week? That seems good but my concern is the why? Caution too good to be real? Is 4 the real and 11 the extreme?
We as Fantasy player have to understand that issue or you end up always surprised!
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Tight Ends Week 3 Targets and Touches.
- Kelce 6 to 14 to 7 targets. 7 the average? Why the 14?
- Hurst at ATL 5 to 8 to 3 targets?
- Waller 8 to 16 to 4?
- Year of high variation? If so beware your point chasing last week vs this week. Focus on the matchups!
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Wide Receivers Week 3 Targets and Touches.
- Allen back? 8 to 10 to 19 targets?
- OBJ 10 to 6 to 6. Low Top?
- Thielen 8 8 to 5?
- Stroll through the data and make notes!
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Week 3 to 2 Differences Player Targets
Week 3 Targets and Touches. We all need to catch the improving or declining players. Early in the season it is murky on what players are going to be seasonal winners or losers. We as Fantasy Player unfortunately have to jump in sometimes too quick but that is this game.
I use the DIFF as a prediction tool in context of course of the why to add to or prune away from my teams. DFS plays can also be modified as well.
Below are the extremes in week 3 to 2 DIFF of improving and declining players. Use as needed.
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Running Back Touches with % Rushing vs Receiving (ATTs vs Targets)
Week 3 Targets and Touches. RBs are the most difficult position in fantasy football because they 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
We must understand the nature of each team towards its use of RBs in rushing and passing. I calculated each Team’s Rush/Pass Ratio and Sorted all teams by that metric. 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 94 on RB rushing and 0.1 on Targeting RBs (they not pass to RBs much) vs NYG who are figured at 0 rushing vs 58 targeting RB (extreme bias).
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The ALL IN RB Rushing Teams are colorized in Blue and are TEN/BAL/LAR/CLE/WAS/PIT/ARI/and LAC
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The PASS Happy RB teams are at the bottom (red brown) and are NYG/JAC/HOU/NO/CIN/CAR/TB/DAL
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Team Level Rushing Attempts vs DIFFs
I broke down and pulled out the Team level RBs rushing attempts and present that in the following table. The data are colorized for easy visualization. Additionally, I calculated the ATT DIFFs to catch improvements or declines.
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RB RUSHING
- PIT/MIN/MIA/NE/KC all had nice RB rushing improvements week 3
- IND/ ATL/GB/LAC/LV/DAL/BAL/DEN all had declines in week 3
- CLE IND TEN LARLAC GB LV are all the tops in rushing
- HOU JAC NYG BAL DEN BUF CIN are at the bottom of rushing teams.
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RB PASSING
- NO TB SF CAR DAL NEIND and GB are at the top of RB targets
- HOU BAL TEN ARI NYJ DEN PIT MIN WAS CHI NYJ are at the bottom of RB passing activity.
- NE LAC DAL DEN WAS all improved in Week 3 RB targeting
- TB CAR CIN MIA all had declines in RB passing activity.
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RB Week 3 vs 2 DIFFs in Rushing vs Targeting
The next figures hammer the DIFF data and I sorted the table by rushing attempt DIFFs from high to low and the improving teams are clearly shown for consideration.
———————————————————–Week 3 to 2 Bar Graph of ATTs vs Targets
I do note the reciprocal nature of the gain in team rushing vs declines etc. The game script do force teams to change and this graphical confirms that issue. Thus, game scripting is a strong avenue for predictions of team RB usages.
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Player Level Total RB Rushing Attempts with Targets
The following tables contain:
- Team
- Player
- Week 1 to 3 Rushing Attempts
- Week 1 to 3 RB Targets
- Average ATTs
- Average Targets
Scroll through the team data and draw conclusions. Not ever finding is actionable but trends and biases are good to know!
For example in ATL Brian Hill surprised in week 3 with 9 rushes and 3 targets vs Gurley? Mirage? I picked up Hill in some leagues given that I had “churn” spots open. Watch and hope player!
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Player Based Average RB ATTs and Targets
I collected the player data and listed each RB by their Attempts and Targets of the season. Colorized and sorted average rushing attempts form High to Low.
Henry Jacobs CMC Zeke and Sanders are all the top RB in rushes
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My Box and Whisker Plots Reveal Key Number for RB Rushes and Targets
What numbers are meaningful? In stats, that is the question. I use a fast and frugal approach to answer that question, Box and Whisker Plots. The BAWs plot the landscape of the data and set the levels of extremes within a population.
Thus in Target Averages for 3 Weeks, any RB that is above the Box number (3 target average) is in the top of the league and above the whisker of 6 is in the extreme!
Extremes in target averages are Zeke, Sanders, Jones, Kamara, and Davis. Now you know!
In rushing attempts, the BAW levels are 10 rushing attempts for the top level and extreme levels are at 22 averages – Henry and Jacobs!
Thanks for reading and use wisely. Do not share with your league-mates 😉