Non-PPR Power Rankings Part 1


Non-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

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Textbook on Kindle

Non-PPR Rankings

I celebrate the rushing QBs and bell-cow RBs in Non-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 10 vs 2 in the first round. 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 Non-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


  • 1) 10 RBs in the first 12 picks. 1 Rookie RBs at pick 37
  • 2) 8 WRs/14 RBs/1 TEs by pick 24. – Extreme RBs picked in 2 rounds!
  • 3) First TE by Pick 17 and QB by Pick 22 (Very Early vs 32 in PPR)
  • 4) 48 pick we see 3 TEs/3QBs/24RBs/18WRs. No Rookie WRs in first 4 rounds!
  • 5) WRs pick up steam after a strong RB run (pick 13 to 48). 6 WRs 2s to be left by 4         rounds. 0 RB2s left after four rounds.
  • 6) You should have access to 6 WR2s before pick 34. 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)


Rounds 5 to 8


  • 1) No Rookie WRs Rounds 1 to 8. 3 Rookie RBs rounds 9 to 12 (higher value vs     m          rookie WRs)
  • 2) RB3s start after the 47th pick. 4th RB at Pick 86 -Early 12th round
  • 3) WR3s by the 63rd pick. Pick up 5 WRs 2 in rounds 9
  • 4) 10 TEs gone by the 90th pick
  • 5) 10 QBs by the 88th pick.  The public says the first 10 QBs are worthy. Below are the “weaker” QBs for Non-PPR
  • Plan using these takeaways. For example, if you love a WR rookie you can wait later in the draft at pick 96. Need a QB/TE in the 4th to 8th rounds


Rounds 9 to 12


    • 1) The dominance of later WRs vs RB 15 vs 10. 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. Note 2 WR rookies finally taken.
    • 2) No more Rookie RBs all in here in rounds 9 to 12. These are the 5th and higher RB 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 just 4 rookies RBs drafted.
    • 3) A Rookie TE arrives on the scene but later round 12 or so. On average drafting in redraft for TE2 types only.
  • 4) 0 rookie QBs drafted by pick 144 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
  • 5) Defense starts at pick 111 we have 7 DEF gone by end of the round 12


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


The Landscape of Team Uncertainty Un Scores in Non-PPR

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


Non-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/BAL Kickers are the tops for drafts.


Quarterbacks 2019 Non-PPR PF

8 QBs are in the above average Tier >61 PF. Later QB Drafting seems reasonable but after the 8th QB they drop off quick!


Non-PPR Running Backs

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


Non-PPR Tight Ends

Three clear TE leaders are KC, PHI, and SF >87 PF for PPR. 9 Teams in an obvious grouping >51 vs the next at 36 and below. It’s a good cutoff at 9th TEs. I would suggest staying in those top 2 groups.


Non-PPR Wide Receivers

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


Team Non-PPR 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!  97 PF within the Team.

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

  • ARI 129.4 RW Score
  • ATL 138.8
  • BAL 40.5
  • BUF 36.2


  • CAR 140.1
  • CHI  90.3
  • CIN 168.9
  • CLE 152.4


  • DAL 184.3
  • DEN  91.6
  • DET 99.5
  • GB 90.4


  • HOU 103.1
  • IND  92.7
  • JAX  72.3
  • KC 125.3


  • NE 91
  • NO 124.7
  • NYG 139.5
  • NYJ 154.1


  • OAK 135
  • PHI   102.6
  • PIT   110.4
  • SEA  122.4


  • SF 64
  • TB 113
  • TEN 75.7
  • WAS 49.8


RW Score Tiers for RB and WR Team Groups

This figure sorts the Teams from High to Low of their RW scores. The team tiers are shown in the graph plot using blue circles to point the tier levels. Tier 1 in Non-PPR is DAL, Tier 2 is CIN, Tier 3 is NYJ and CLE, etc. Good tiebreaker for later in the draft for close players.




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