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Non_PPR Ranks Risk Skew Week 4
- Updated: September 29, 2017

by John Bush
Non_PPR Ranks Risk Skew Week 4
Non_PPR Ranks Risk Skew Week 4 rankings are not simply numbers on a page or column. I have to include my metric based risk assessment and a new metric based range skew analysis that I have developed this summer.
I have also included two stand-alone figures that expand the concepts of Risk as I use in fantasy football and the idea of a Ranking Range Skew number. I present the Team landscapes of risk numbers and risk analysis of the positions within the teams.
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Let’s begin with Risk. I use that term as a measure of possibilities. 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 to understand my rankings; I wanted to declare my view of the player range of possible outcomes.
High Risk means a large set of possibilities, Mid Risk means a narrower set of outcomes and Low Risk implies a very tight range of outcomes. See Figure 1 for a visual description.
Figure 1. Fantasy Football Risk Metric and Analysis.
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Figure 2. Outcome Range Skew
I have divided the positions into groups and present my PPR based rankings with risk and Range Skew from high to low rankings (Green to Red).
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Week 4 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. In Figure 3, I simply present for each team a count of their ranked players who are in the week 4, High, Mid or Low-risk players.
For example, this week KC has well over half its ranked players at high risk (67%) and WAS is at 63%! My rankings must be considered a best case. DEN and ATL have zero players at high risk this week. Interestingly, MIA, TEN, and BAL have only 1 player at predicted high risk! These teams should as a whole have more consistent player production as their ranking indicates. Use this data to evolve your views.
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!
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Figure 3 to 4. Week 4 Team Risk Landscape
Figure 3 shows each team’s Player Counts for Risk Catergories. 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.
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Non_PPR Ranks, Risk, Skew Week 4
I use the ranking as a best case and modify my DFS and Lineups based on the other factors of game scripts, DAPs, Risk, and Range Skew. Good Luck!