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Early MFL10s 2017 ADPs with rankings and risk analysis.

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These data tables will give a look at the current MFL10 ADP and Risk .    I wrote about using my MFL 10 data in a post last year.       See this link MFL Data Past Post Read Me
The Next 6 Charts show QB, RB, TE and WR Data from the current MFL10 ADPs see 
Pos Num = ADP of the Player within their position
ADP Num = ADP within all 150 Players looked at
Player, Team, and Position. 
Scaled Public Ranking from 100 to 0 (Best - Green and Worst -Red)
Very Early Risk Number (My Risk Analysis from 0 no Risk to 100 Highest Risk). I try to incorporate, elements for the player and team. I will fold in SOS and injury history data later













A landscape view of the current MFL10 ADPs by position. 
Red circle marks the end of the 12th TE or QBRed Arrows mark the RBs rounds of 12Yellow Arrows mark the WR rounds of 12The first 12 TEs are off the board on average in round 10 The first 12 QBs are drafted on average by round 10 as well.The first 12 RBs at round 3, next 12 at round 6 and next 12 RBs by round 9.The f…

Peek into Chapter 5 from my Drafting Textbook. Clues for Drafting; Team Analysis and Distribution of PPR Points to each Position.

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Chapter 5. Clues for Drafting; TeamAnalysis and Distribution of PPR Pointsto each Position.
In fantasy football, players are on teams, thus team analysis is a necessary backdrop for
our 2017 drafts. In figure 5-1, I present a team view of all 32 team's PPR points scored
from 2013 to 2016. The data is color coded each years' top and bottom PPR scoring
teams.


I have color coded the team names with a light red coloring to point out teams that have
been in the bottom in each of the 4 years. Those teams are BUF, JAC, LAR, MIN, and
SF. As a whole, these teams have been underperforming for years. Be aware of drafting
lower level players from these teams.


The opposite of the underperforming teams were those teams that have been performing
higher than most other teams across the 4 years. They are colorized in light green and are
NE, NO, PIT, SD, and SEA. Players from those teams need a deeper look for a sleepers.

Certainly,  teams doing well in the last year or 2 years must be consider…

Running Backs and their 2016 Passing Targets and Rushing Attempts. Scaled Numbers with Rushing to Pass Ratios, Bias Analysis

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Working my Chapter X1 Data in my Textbook on Drafting. Shooting for the 2017 First Edition in May on Amazon. 
Drafting Textbook Data Figures.
In these tables, I looked at the Running Backs and their 2016 Passing Targets and Rushing Attempts.

I calculated a Scaled Scoring System for 0 to 100 and assigned the players their numbers of Rushing vs Passing.

I also calculated a Rushing to Passing Ratio Stat and assigned each player an R/P number

Finally, all of the 2016 active Running Backs were sorted by their R/P number and their biases determined.

Passing Biased - RBs that had a Passing Score higher than their Rushing Score.

Rushing Biased - RBs that had a Rushing Score Higher than their Passing Score

Balanced - RBs whose 2 Scores were close to each other.







Extra Treat Figures Team Efficiency 2016. Guess Where the Patriots and Flacons were?

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Sometimes my figures get so pretty that I got to share with the world.

Love Love my Team Efficiency Figure based on my Data going into my Textbook!

Enjoy



2013 to 2016 Seasonal Averages of Player's PF* _____ *(my performance figure. I do I weekly calculation with the position and scaled players production to a scale of 0 to 100).

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Working my Chapter 13 Data in my Textbook on Drafting. Shooting for the 2017 first edition in May on Amazon.  

I guess I am excited as I go through the data and wanted to share some fun facts for your 2017 Drafting. Let your mind flow through the data! Enjoy!

FYI- The PF* is my performance figure. I do I weekly calculation with the position and scaled players production to a scale of 0 to 100. Thus you can compare all players together. 

*This is a great weekly advantage that the "other" sites can not deliver 

In my Textbook I will have the complete weekly PF look into the 2016 17 week season! Below is the Seasonal average of PF for each major player! 

****  These PFs make great TIER Boundaries ****




















One figure from my Chapter 6 in my textbook due May 2017. 2016 RB and WR positions in terms of scaled to average of EOS PF vs PS ADP levels

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Working my Chapter 6 Data in my Textbook on Drafting. Shooting for the 2017 first edition in May on Amazon.  

I guess I am excited as I go through the data and wanted to share some fun facts for your 2017 Drafting.

Figure 42 in my Chapter 6 focuses attention on a comparison between the 2016 RB and WR positions in terms of scaled to average. We can now define success as above the average, positive numbers. Negative numbers will note failures. This figure contains the numbers of successes above the average over the 48th RBs and WRs. The dashed black line denoted the success failure breakpoint. The rounds are divided by the pink dotted lines. The actual positions and their successes are displayed within each round.

The two patterns numerically are; RBs 8, 8, 3 and 7 successes and WRs are 8, 9, 6 and 3 successes.

The y-axis is the scaled End of Season Performance (Dec 2016) vs the preseason ADP level (Sept 2016)

I conclude that in 2016;
The WRs were best early and riskier later. The RBs we…

2016 ADP (180th ADP or Less) Sept 2016 vs End of Season Fantasy Points Scored

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FYI
Working on updating my Textbook on drafting and have been drilling down deep into the data. Here is the first figure and draft write up for my Chapter 6 redo in my Drafting Textbook. ===============================Chapter 6. Clues for Drafting; ADP vs. Seasonal Player Performance
I analyzed the relationship of the QB, RB, TE, and WR players ranked by their pre-season ADP (PS-ADP to about the 180th player number – total position except DEF and K) and their end-of-season long PPR points scored (ES PPR) to determine how strong the finish was for each position PS-ADP vs. the ES-PPR. The first figure of this data of the PS-ADP vs. ES-PPR from the years 2016 is presented in Figure 36.
The first quest was to determine what was the differences in the players on an ADP draft list 180th or less or players greater than a 180th ADP level.  (ADP 2016 and earlier historical data is available free at several websites, I randomly picked one and used it through the chapter)
In Figure 36 in the top…