PPR Power Rankings Part 1

======================================

PPR Power Rankings Part 1

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

I celebrate the rushing QBs and Pass Catching RBs in PPR. My general thoughts are draft QB later and TEs Early or Late (Barbell Approach). In 2019 the RBs are coming off the board early and WR later in the first rounds. The pattern RB_RW_RB_RW seems to be playing out in drafts. Follow or flip the script with WR/RB/WR/RB or take an Early TE in the RB slots.

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!

———————————————————————————————————————————–

The Landscape of the Current PPR Leagues by Positions 1st to 144th Pick


Rounds 1 to 4

Let’s find the patterns. The figure below is for the first 4 rounds displaying from the Top; WR, TE, RB, QBs. Note the picks are by 6 pick segments. Star Superscripts are rookies

Takeaways.

  • 1) 8 RBs in the first 12 picks. 2 Rookie RBs at pick 30 and 42
  • 2) 10 WRs/13 RBs/1TEs by pick 24. – Surprising in a PPR that RB >WR in the first 2              rounds
  • 3) First TE by Pick 17 and QB by Pick 32.
  • 4) 48 pick we see 3 TEs/2QBs/22RBs/18WRs. No Rookie WRs in first 4 rounds!
  • 5) WRs pick up steam after a strong RB run (pick 14 to 30). 6 WRs 2s to be left by 4         rounds. 2 RB2s left after four rounds.
  • 6) You should have access to 6 WR2s before pick 48. The pattern might be RB/RB or       WR/RB/RB or WR. So Assume RB _ RB _ in the first 4 picks
  • 7) I suggest waiting on QBs
  • 8) Use the Barbell approach for TEs (Go early or late)

Slide2


Rounds 5 to 8

Takeaways.

  • 1) Rookie WRs begin late vs 4 Rookie RBs ( 8th round)
  • 2) RB3s start after the 57th pick.
  • 3) WR3s by the 58th pick. (tied with RBs in the 5th round).
  • 4) 9 TEs gone by the 87th pick
  • 5) 10 QBs by the 94th pick.  The public says the first 10 QBs are worthy. Below are the “weaker” QBs for PPR
  • Plan using these takeaways. For example, if you love a WR rookie you can wait later in the draft at pick 84 or so.

Slide3


Rounds 9 to 12

Takeaways

  • 1) The dominance of later WRs vs RB 18 vs 14. These are WR4s and 5s. They all have “flaws” so use team usages/round of draft originally taken/context of other WRs.  A team WR2 that is a WR4 overall should be better than lower team WRs. Note only a few teams can support 3 WRs for Fantasy.
  • 2) 2 more Rookie RBs all in here in rounds 9 t0 12. These are Rookies that have more questions than the top RBs. Team usages, and the hierarchy of their Team RB group. Are they pass-catchers? By round 12 we have seen 6 rookies RBs drafted.
  • 3) A Rookie TE arrives on the scene but later round 10 or so. On average drafting in redraft for TE2 types only.
  • 4) 1 rookie QBs drafted in pick 101 so they mostly should appear in round 13 or higher. They are being taken as a 2nd QB type for this year. Still, look at NFL draft round taken. Round 1>2 etc

Slide4


Levels of Team Uncertainty

This chart can be a shorthand for quick decisions in a timed draft. I have annotated the Teams into High, Average and Low Uncertainty (red, yellow or green). In this table, I list the number of players in each team in the High, Average and Low Levels of Uncertainty.

Also, I included the High and Average Player vs Low Player Count Ratio as a metric for a numerical view of the Team Uncertainty. Finally, I used another metric for measuring Team Uncertainty, the UN Score an algorithmic based metric.

I used the UN Score as a guide to assign annotation of the Team Uncertainty. I would use as a tiebreaker in closely ranked players probably later in the draft

Slide6


The Landscape of Team Uncertainty Un Scores in PPR

The team UN Score tiers are much clearer in this plot-High to Low Uncertainty Levels. NE vs CIN represents the Highs to Lows in Un Scores. Use these metrics for tie-breakers and teams to dig for late sleepers.

Slide7


PPR Based Team Positional Predicted Performance Score (PF) for 2019

Use of Draft Selection and Tier Level View of each Team’s Position 2019 PF. Again, we have a nice tiebreaker metric for drafts. Note PF is my 2019 Predictions for each Team Positions.

Defense and Kicker 2019 PFs

Note CHI DEF is much the best while the LAR/KC Kickers are the tops for drafts.

Slide9

Slide10


Quarterbacks 2019 Dynasty PF

9 QBs are in the above average Tier >61 PF. Later QB Drafting seems reasonable but after the 9th QB they drop off quick!

Slide11


Running Backs

6 Teams (NYG/CAR/DAL/ARI/NYJ/CIN) had RB crews in the >93 PFs for Dynasty. Note the Tier at 80s Oak and then drop into the 70s for NO/LAR/CLE

Slide12


Tight Ends

Three clear TE leaders are KC, PHI, and SF >89 PF for PPR. 7 Teams in an obvious grouping >54 vs the next at 36 and below. It’s a good cutoff at 10th TEs. I would suggest staying in those top 2 groups.

Slide13


Wide Receivers

DAL is the top in here followed by MIN, ATL, TB, and CLE. All of those have upcoming WRs in their WR crews. MIA/BUF/BAL is the worst for PF and uncertainty for sure.

Slide14


Team Positional PFs

I suggest using these metrics for finding extremes within each team. You should focus you onto the highs and lows within each Team. I would use these metrics for deeper views.

By coming into my rankings for the top down, I try to eliminate the “halo” effect of a good/bad player’s name that can cause over or underestimation of a Team/Position/or Player

The halo effect is a type of immediate judgement discrepancy, or cognitive bias, where a person making an initial assessment of another person, place, or thing will assume ambiguous information based upon concrete information.[1][2][3] A simplified example of the halo effect is when an individual noticing that the person in the photograph is attractive, well-groomed, and properly attired, assumes, using a mental heuristic, that the person in the photograph is a good person based upon the rules of that individual’s social concept.[4][5][6] This constant error in judgment is reflective of the individual’s preferences, prejudicesideology, aspirations, and social perception.[3][6][7][8][9] The halo effect is an evaluation by an individual and can affect the perception of a decision, action, idea, business, person, group, entity, or other whenever concrete data is generalized or influences ambiguous information.[10][11][8]

Link  Halo Effect Wikipedia

Note I have included a scaled Performance Factor (PF) metric to place the position’s PF into the league context. (negative scaled PFs are below league average while positive scaled PFs are above the league average).

Thus, you get an outside vs inside look into each team!

For example, ARI is all about that RB action boss! +32 league average and 90 PF within the Team.

I use the RW score to “see” the RB/WR totals

  • ARI-129 RW Score
  • ATL 145
  • BAL 62.9
  • BUF 42.1

Slide16

  • CAR 140.9
  • CHI  86.9
  • CIN 167.9
  • CLE 157.5

Slide17

  • DAL 186.3
  • DEN  93.3
  • DET 98.2
  • GB 134.4

Slide18

  • HOU 140.8
  • IND  102.8
  • JAX  75.4
  • KC 105.7

Slide19

  • NE 95.9
  • NO 126.1
  • NYG 144.9
  • NYJ 126.9

Slide21

  • OAK 143.6
  • PHI   98.3
  • PIT   111.0
  • SEA  119.9

Slide22

  • SF 61.7
  • TB 116.2
  • TEN 77.1
  • WAS 30.1

Slide23


RW Score Tiers for RB and WR Team Groups

  • DAL 186.3
  • ———————
  • CIN 167.9
  • ——————–
  • CLE 157.5
  • ——————-
  • ATL 145
  • NYG 144.9
  • OAK 143.6
  • CAR 140.9
  • HOU 140.8
  • ———————
  • GB 134.4
  • ——————–
  • ARI-129
  • NYJ 126.9
  • NO 126.1
  • ——————–
  • SEA  119.9
  • TB 116.2
  • ——————-
  • PIT   111.0
  • ——————
  • KC 105.7
  • IND  102.8
  • PHI   98.3
  • DET 98.2
  • ——————
  • NE 95.9
  • DEN  93.3
  • ——————–
  • CHI  86.9
  • ——————
  • TEN 77.1
  • JAX  75.4
  • —————–
  • BAL 62.9
  • SF 61.7
  • —————-
  • BUF 42.1
  • WAS 30.1

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: