Non-PPR Ranks-Risk-Rewards Week 1

by John Bush

Non-PPR Ranks-Risk-Rewards Week 1

Non-PPR Ranks-Risk-Rewards Week 1 rankings are not simply numbers on a page or column. I have also included my metric based risk assessment as well as player ranking.

I have also included stand-alone figures that expand the concepts of Risk as I use in fantasy football. I present the Team landscapes of risk numbers and risk analysis of the players within the teams.

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Let’s begin with Risk. I use that term as a measure of possibilities (ceiling to floor). Each ranking in this world is a number usually an average. In 100 games played under these same conditions, a player will average at their rank (50 percentile).

What about the rare games where they scored much higher or lower? Thus a range of possibilities can exist. You use this concept to understand my rankings; I wanted to declare my view of the player’s range of possible outcomes with my rankings.

High Risk means a large set of possibilities or the distance from player ceiling to floor, Mid Risk means a narrower set of outcomes and Low Risk implies a very tight range of outcomes. See below for a visual description.


Fantasy Football Risk Metric and Analysis.

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Team Risk Landscape

As you stroll into my rankings, later on, I predicted that the team’s risk levels can be used to modify your rankings-based lineups or bargain hunting in DFS situations.

I simply present for each team a count of their ranked players who are in the Week and generate the counts of High, Mid or Low-risk players.

FYI to finish my week’s picture

  • I consider game scripts, DAPS, Risk, Range Skew and rankings.
  • I use all the data predictions to move to a holistic opinion!
  • Blindly following numbers is not the best way!

Week 1 Team Risk Landscape

The table shows each team’s Player Counts for Risk Categories. I present an Area View of the Tabular Data and finally a focused view of the Team’s with High to Low Counts of Risky players. 

Each Team in the following table is colorized to note the Teams which have the high, medium and low riskier players.  Good for tiebreakers in DFS and lineups.

Non-PPR Ranks-Risk-Rewards Week 1 Slide1


Team Risk Landscape

The waterfall graph shows each team’s Player Counts for Risk Categories of High and Low. I present a Landscape View of the Tabular Data and finally a focused view of the Team’s with High to Low Counts of Risky players.

Non-PPR Ranks-Risk-Rewards Week 1 Slide2

We see that for the week, WAS, PIT, TB, MIA, ATL, JAC, BUF, and DEN. These teams have the highest level of HIGH risky players ranked. This can at least get data to fantasy players to pause and think about why the high risk?

  • New Players?
  • Unproven Players?
  • Poor Matchup? 

The low-risk teams in week 1 are NYG, KC, NE, LAR, LAC, SEA, DET, and TEN. Again players should consider the reasons for being a low-risk team this week

I think my rankings are closer to reality in lower risk teams than in the higher risk teams. Good for DFS, Lineups and drop and adds this week. I use the rankings as a best case and modify my DFS and Lineups based on the other factors of game scripts, DAPs, and Risk. Good Luck!


Defense and Special Teams

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Kickers

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Quarterbacks

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Non_PPR RBs

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Non_PPR TEs

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Non_PPR WRs

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TEAM View PPR Positions and Players Rankings and Assessments of Risk

These figures of teams present a Rankings and Risk landscape. Use to focus down at a matchup level. Fringe players may be used in great matchups vs avoided in poorer situations. 

I will be adding My Matchups Analysis later in the week. 

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