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PPR Power Rankings Part 2

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PPR Power Rankings Part 2

By Dr. John Bush (Twitter @Prof_Fantasy1)


Fun Research in my textbook!

Winning Your Fantasy Football Drafts: A Comprehensive Textbook: June 2019 Edition [Print Replica] Kindle Edition

Click Link Below

Textbook on Kindle


PPR Rankings

My approach to my data is fewer words and more visuals. Do you want me to hand-feed you what you can see? No! Use to inspire deeper thinking. Chop the wood then get the fire! Do not be like those who would want the fire then maybe you will chop some wood! They keep you dependent!

Please go read part 1 to get a “view” of the landscape of current ADP and Team uncertainty and positional power!


Player Level PPR PFs

These figures present my PPR PF rankings. I divided the metrics into 3 columns of Uncertainty Levels (High, Average, Low) as well as overall positional league level PF.


Uncertainty Levels for Each Player (All from my textbook FYI)

The following are a few differences between risk and uncertainty:

  • In risk, you can predict the possibility of a future outcome while in uncertainty you cannot predict the possibility of a future outcome.
  • Risk can be managed while uncertainty is uncontrollable.
  • Risks can be measured and quantified while uncertainty cannot.
  • You can assign a probability to risks events, while with uncertainty you can’t.

Conclusion: Risk and uncertainty are different terms, but most people think they are the same and ignore them. Managing risk is easier because you can identify risks and develop a response plan in advance based on your experience. However, managing uncertainty is very difficult as previous information is not available, too many parameters are involved, and you cannot predict the outcome.*

*https://pmstudycircle.com/2012/02/risk-vs-uncertainty/. This source explains risk vs uncertainty

I think the issue for Fantasy Football is better described as uncertainty. I have previously outlined some steps to mitigate uncertainty. On average the level of uncertainty goes up in a draft, so your process must change as you go into the draft. Knowing the positional patterns helps as well as team usages of positions and the pecking order within the team.

*To Insure yourself from uncertainty by considering the max/min of each pick (floor to ceiling).

Usually, you hear draft for the high ceiling but what is the floor. Also, you can be told draft for a high floor but what is the maximum?

* Insure yourself from uncertainty by considering decision trees associated with your information.

Mock Drafts or Best Balls can work these decision trees out for you.

* Insure yourself from uncertainty by considering the Hurwicz Criterion **

** Hurwicz Criterion: The maximax and the maximin criteria of a draft pick, assumes that the fantasy player is either optimistic or pessimistic.

A more realistic approach would, however, to consider the degree or index of  optimism or pessimism of the decision-maker in the process of decision-making which players to draft

For each player considered determine your degree of player success as well as the Ceiling and Floor for that player.

If a, a constant lying between 0 and 1, denotes the degree of your draft pick optimism, then the degree of pessimism will be 1 – a.

Then a weighted average of the maximum and minimum payoffs of action, with and 1 – as respective weights, is computed. The action with the highest average is regarded as optimal.

I suggest using an estimate of PPR production. If you think a player will get 160 FP as your optimum, then decide the worst case say 90 FP. Do that for all major choices.

We note that nearer to unity indicates that the decision-maker is optimistic while a value nearer to zero indicates that he is pessimistic. If = 0.5, the decision maker is said to be neutralist.

Assume that the index of optimism = 0.7. or a 70% chance you predict of hitting 160 FP for player 1 then you are saying he has a 30% chance of 90 FP.

Example Matrix of Decision

The first Player is   160  90  = 160*.7    plus   90*0.3    = 139

Player 2   150 100 = 150 *.75 plus 100*0.25  = 137.5

Player 3   175  80  = 175*0.6  plus   80 *0.4   =  137

Since the average for Player 1 is maximum, it is optimal.

** https://www.wisdomjobs.com/e-university/quantitative-techniques-for-management-tutorial-297/decision-making-under-uncertainty-10067.html


Defense 

The Tiers are clear.

  1. CHI
  2. LAR, JAX, LAC
  3. CLE
  4. BAL
  5. MIN, HOU
  6. DAL
  7. DEN, PHI,
  8. NO, GB, BUF, IND, NE, PIT

Slide25


Kicker

Tiers

  1. Zurlein
  2. Butker, Tucker
  3. Lutz
  4. Gostkowski, Fairbairn
  5. Tavecchio, Myers
  6. Vinatieri, Elliot
  7. Badgley, Maher

Slide26


Quarterbacks

Nice selections for your analysis. It clear which QBs have more uncertainty or less within the top 10 QBs.

Tiers

  1. Mahomes
  2. Luck
  3. Rodgers
  4. Watson
  5. Mayfield, Ryan, Brees
  6. Wilson, Wentz
  7. Goff
  8. Murray, Newton, Winston
  9. Roethlisberger, Brady

Slide27


Running Backs

Given the current ADP patterns, the early RBs are being drafted and they also have low uncertainty levels.

The only issue with my method of uncertainty assignments is the extreme players top or bottom “look” so good and safe or bad and unsafe. This is a bias we all have to fight. Thus begin here with these rankings of uncertainty and dig down.

**The uncertainty of a single measurement is limited by the precision and accuracy of the measuring instrument, along with any other factors that might affect the ability of the experimenter to make the measurement.

**https://www.webassign.net/question_assets/unccolphysmechl1/measurements/manual.html

My algorithmic approach to uncertainty is the measuring instrument. Thus as the definition above suggests my algorithmic approach is limited by precision and accuracy.  I will need numerous samples of data to get feedback to alter the algorithmic approach (multiple seasons of data). It will always be a work in progress FYI.


Tiers

  1. Barkley, CMC
  2. Elliot, Kamara
  3. Gordon, DJ
  4. L Bell
  5. Connor
  6. Mixon
  7. Gurley
  8. Cook
  9. D. Will, N. Chubb
  10. D. Freeman
  11. Fournette, Jacobs, Mack
  12. Jones, Henry, K Johnson
  13. Lindsey, Michel, D Montgomery, Ingram
  14. Carson
  15. Drake, White, Cohen, Guice

Slide28

16. Sanders, Miller, Coleman

17. Hunt, L Murray, Penny, Howard, Jones

18.  R Freeman, McCoy, Ekeler, Hyde, Samuels, Singletary, I Smith

19. Foreman, Hines

20. Barber, Peterson, Lewis, Justice Hill

Slide29


Tight Ends

The top TEs for dynasty have nice low uncertainty levels but only 3 are above 80 PF levels. The Top 10 TEs are fairly “safe” thus, I have been drafting in that range. I have taken Hooper as a low TE 1 and Goedert/Reed/Rudolph as gambles but mainly as TE2 types.

Tiers

  1. Kelce
  2. Ertz
  3. Kittle
  4. Howard, Ebron
  5. Henry, Engram
  6. Cook, McDonald
  7. Njoku
  8. Hooper
  9. Hockenson
  10. Walker
  11. Olsen
  12. Burton
  13. Herndon, Fant, Rudolph, Reed

Slide30


Wide Receivers

Again, we see the extremes in the uncertainty data. Begin here to trust but verify my assignments.

Tiers

  1. Hopkins, Adams
  2. Thomas, Jones
  3. OBJ, JuJu
  4. Brown, Evans
  5. Thielen, Hilton
  6. Allen, Cooper
  7. Green
  8. Diggs
  9. Edelman
  10. Cooks, Golladay, Woods,
  11. Ridley, Kupp, Watkins
  12. Godwin, Landry, Lockett
  13. Williams, DJ Moore,
  14. Boyd, Hill, Jeffrey
  15. Anderson
  16. Robinson, Harry, Fuller

Slide31

17, Hardman, Pettis, Metcalf,

18. Allison, Tate, Shepard, Kirk

19. Fitzgerald, Davis, Sanders

20. Jones, Sutton, Washington, Westbrooke

Slide32


Team Level Player PFs

The preceding metrics focused on the league level positional PFs while these PFs are within the Team. In PPR pass-catching adds luster to RBs.

I use the outside in approach in my thinking.

  • Who is around my player?
  • Is there a committee?
  • Is the QB’s future uncertain for the complete season?
  • Where is the talent on the team?
  • Handcuffs viable?
  • 50% is near average for the PFs

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