Target Trilogy Part 1: Professor's 2015 Team Target Report (Total Targets and Positional Targets)

www.fakepigskin.com/2016/08/08/dynasty-vs-redraft-quarterback-and-tight-end/

This is a link to a great article Dave Cherney and I have written. (Part 2) 

We have Part 3 and 4 to be done in this series. 

If you do both Dynasty and Redraft this is a must read series! 


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Target Trilogy Part 1: Professor's 2015 Team Target Report (Total Targets and Positional Targets) 

Part 2 and Part 3 Thursday and Friday!


These data from my Textbook which I updated and will update again.

Link to my Updated Textbook!


 I present my team level target reports. In Figure 1, I have listed in the first data column labeled as "Targets" the top to bottom of the 2015 NFL Teams in order of highest targets to lowest. The next column labeled as "Num to Avg" details each team's total targets as related to the 2015 league average. 

For example BAL, produced 106 more targets than the average 2015 NFL team while MIN produced -125 total targets below the 2015 NFL average. In the final column labeled "% of Total", I calculated each team's total targets as a percentage of the entire 2015 leagues target numbers. I uses these numbers in my drafting plans to highlight the potential each player make have in 2016. Interestingly, looking at BAL, I have been drafting Steve Smith as much as possible late. I think the price I am paying is good simply because the BAL team can crank out the targets. I play in PPR and this data is very helpful. 

On the other-hand, I am avoiding the MIN WRs because the price they require does not fit in with a team that was 125 targets below the average. I can not risk drafting those WRs. I would use these data to give extra credit to teams stained in green (good) and avoid players from teams stained in red (below average). Obviously a number 1 WR, RB or TE from a poor teams can give good production. I use this data to limit their ceiling in my drafting.

Figure 1

Slide1 The next series of figures (2 to 4), present my team target data by position (RB, WR, and TEs). This data is in the same format as described previously. I would use this data in the same general ways. Lets this data push your attention into the teams that use either specific position at high levels (High Num to Avg) and avoid players from the teams that do not use the position well (Low Num to Avg). 

 In Figure 2, I present the 2015 RB team target data. Combine this data with your knowledge of the current ADP landscapes. For example, the RBs in PHI (+66 Num to Avg) are being drafted later that other RBs. I have focused on them when the draft price is right as I predict Ryan Mathews and Darren Sproles will return value for you last round picking. 

The opposite issue is seen in CAR, Jonathan Steward, the main RB comes from a team that did not use passing to the RB as a way to move the ball. CAR was the league lowest and produced a -49 targets below league average. I would devalue him in PPR leagues but not as much in standard scoring leagues.

FIGURE 2

Slide2 The 2015 data is next presented for the WRs by team in Figure 3. The same format continues in this figure. In PPR leagues, WRs are critical as they usually represent a high majority of a team's targets. Figure 3 is a goldmine of data. I would build my draft board and highlight the teams stained in green and denote caution from the WRs from teams stained in red. 


 The highest production in targets from team WRs was seen in the NYJ team with a Num to Avg of +110. Note the next highest team was HOU with a +80. So on average with 17 games, the NYJ WRs was spotted 2 PPR points per game more than any other team. I am therefore targeting Brandon Marshall and Eric Decker in my drafts. I have even slightly over-paid for them because the data points to a conclusion that the NYJ team will use their WRs alot this year as well. 

 TEN had the lowest WRs corp. The WRs are being drafted much lower this year. I have drafted TEN WRs but only in the last draft round. They are a gamble for this year. Another comment is that KC was second lowest. Jeremy Maclin is being drafted fairly high this year, I have not bite that bait! He was been too over priced for me. I would suggest caution in all WRs from the lower ranked teams.

Figure 3 Slide3

In the last figure, Figure 4, I present the data for team TE targets. The amazing fact that jumps out to me is the +82 that TEN generated by Delanie Walker. The next highest team is NE with a +49. I have been if going early for TE drafting picked up Delanie Walker. Having a 1 PPR point or more weekly advantage is a good reason to draft him.  

The NYJ team had the worst Num to Avg of a -94 score. I see some hype point to improvement of the TEs in the NYJ team. I would urge caution and would not over-pay for any TE from NYJ!

Figure 4 Slide4

Summary

Use these data as guides to focus your attention independent of the current player hype! Use wisely! This data was generated by me and original published in my Drafting Textbook available on amazon.

Thursday- Part 2 will display the % of Positional Team Usages 

Friday- Part 3 will compare Current MFL ADP 2016 with the Team's 2015 Usage! 


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