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Fantasy Football Analytics

Week 11 WRs Uncertainty Tiers [Visualization + Table]

1
  • by Chad Wittman
  • in Projections · Risk
  • — 15 Nov, 2013

First and foremost, this work was inspired by /u/Prayes (Boris Chen – Check out his site: http://borischen.co ) who opened my eyes to this concept.

The NFL has a good chunk of luck (random processes), it seems to sit somewhere between 25%-50%. Boris’ idea of tiering players essentially helps reduce this influence to help make better decisions in your weekly line up.

In my opinion, ranks are relatively meaningless when making decisions for your starting lineup. I need to understand how many points a player is projected for me to determine any sort of value when picking my lineup.

I took Boris’ concept of clustering fantasy players by rank and mashed it with my concept of measuring uncertainty each week to create this:

THE GRAPH: 

Week 11 WRs Uncertainty Tiers

What Is The Graph?

The vertical axis is the player’s Fantasy PTS (FPTS) projection. The dot represents their average, while the bars represent the standard deviation in their projections. The taller the bar, the more uncertainty in the projection.

The horizontal axis is player’s average rank. This is looking at FantasyPros aggregate rankings (wisdom of the crowd). This helps give a sense of how the “experts” would sort the players.

The colors distinguish tiers of players. This is determined by a clustering algorithm which is clustering players by their projected output. Players in the same color, are expected to perform roughly the same as other players in their color – but they are expected to perform differently than tiers different from theirs.

How Do I Use This?

There are two ways to use this graph: identify uncertainty between players or identify tiers of players.

To identify uncertainty between players, examine an individual plot point and note how tall the error bar (vertical bar extending from dot) is. The taller the bar, the more uncertain their projection is. The top of the bar is the most likely “high” score, while the lower bar is their most likely “low” score.

To identify tiers of players, examine groups of players by color. If you’re trying to decide between two players, tend to choose the player with the “hotter” color (red>yellow>green>blue>pink). These players in the same color group are within the same tier, when players are in a same tier – they essentially are a wash between each other due to a randomness. This where I’d recommend to use some intuition and anything else (flip a coin?) to make a call.

I do stuff like this and more at our blog https://fantasyfootballanalytics.net

Table

Name Floor ↓ Avg Ceiling Tier
Calvin Johnson 19.7 25.4 31.1 1
Andre Johnson 18.8 23.0 27.2 1
DeSean Jackson 18.0 20.7 23.4 1
Vincent Jackson 17.6 22.1 26.6 1
Pierre Garcon 17.5 21.0 24.5 1
Antonio Brown 17.4 19.6 21.8 1
Demaryius Thomas 17.4 20.0 22.6 1
Brandon Marshall 17.2 22.4 27.6 1
A.J. Green 17.1 18.4 19.7 2
Wes Welker 16.0 18.6 21.2 2
Torrey Smith 14.7 16.9 19.1 2
Keenan Allen 14.4 16.6 18.8 2
Riley Cooper 14.3 16.4 18.5 2
Victor Cruz 13.7 17.0 20.3 2
Jordy Nelson 13.1 16.3 19.5 2
Harry Douglas 12.8 16.1 19.4 2
Larry Fitzgerald 12.6 16.1 19.6 2
Kendall Wright 12.4 15.4 18.4 2
Golden Tate 12.1 14.9 17.7 2
Josh Gordon 12.0 16.3 20.6 2
DeAndre Hopkins 11.9 13.9 15.9 2
Alshon Jeffery 11.7 15.4 19.1 2
Eric Decker 11.0 15.7 20.4 2
Cecil Shorts 10.9 13.1 15.3 3
Danny Amendola 10.9 13.7 16.5 3
Jarrett Boykin 10.7 13.7 16.7 3
Denarius Moore 10.6 11.7 12.8 3
Marques Colston 10.3 13.4 16.5 3
Steve Smith 10.1 12.1 14.1 3
Anquan Boldin 9.5 11.3 13.1 3
Mike Wallace 9.0 13.1 17.2 3
Hakeem Nicks 8.9 11.4 13.9 3
Brian Hartline 8.5 11.4 14.3 3
Santonio Holmes 8.5 11.6 14.7 3
Rueben Randle 8.1 11.6 15.1 3
Dwayne Bowe 8.0 9.6 11.2 3
Roddy White 8.0 10.7 13.4 3
Michael Floyd 7.8 11.0 14.2 3
Aaron Dobson 7.6 10.4 13.2 3
Kenny Stills 7.5 9.6 11.7 3
Brandon LaFell 7.3 8.6 9.9 4
Mike Brown 7.1 10.6 14.1 3
Jerricho Cotchery 6.9 10.4 13.9 3
Marvin Jones 6.6 9.9 13.2 3
Marlon Brown 6.5 8.0 9.5 4
Tiquan Underwood 6.4 7.4 8.4 4
Eddie Royal 6.3 7.6 8.9 4
Kris Durham 6.3 8.1 9.9 4
Rod Streater 6.3 7.3 8.3 4
Darrius Heyward-Bey 5.9 6.4 6.9 5
Leonard Hankerson 5.8 7.4 9.0 4
Greg Little 5.7 8.6 11.5 4
Doug Baldwin 5.7 10.1 14.5 3
James Jones 5.6 8.7 11.8 4
Mario Manningham 5.6 7.3 9.0 4
Nate Washington 5.4 7.6 9.8 4
Percy Harvin 5.4 10.1 14.8 3
Davone Bess 5.3 6.7 8.1 5
Stephen Hill 5.3 7.1 8.9 4
Greg Jennings 4.9 8.3 11.7 4
Donnie Avery 4.9 9.0 13.1 3
Dexter McCluster 4.6 7.0 9.4 4
Jerome Simpson 4.5 6.3 8.1 5
Vincent Brown 4.3 6.1 7.9 5
Griff Whalen 4.1 5.9 7.7 5
Jason Avant 4.1 5.4 6.7 5
Marquise Goodwin 4.0 6.1 8.2 5
Santana Moss 3.9 4.7 5.5 5
Lance Moore 3.8 6.0 8.2 5
Jacoby Jones 3.6 5.4 7.2 5
Julian Edelman 3.6 5.0 6.4 5
T.J. Graham 3.5 5.6 7.7 5

Disclaimers

I dislike how the names are displayed within the graph. I spent about a day trying to figure out how to best get them to display so that they’re readable. Always open to suggestions, especially if you’re an R nerd like me.

Last, but not least, one more shout-out to Boris.

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Tags: uncertainty

— Chad Wittman

Chad has played fantasy football for 10 years. Finding himself knee deep in statistics at his job, he has been compelled to apply statistical learning to one of his favorite pastimes. Chad is a Redskins fan living in a Seahawks city.

1 Comment

  1. Steve says:
    November 16, 2013 at 4:23 pm

    I like the ‘ranks are meaningless’ approach, but help me understand the tiers. Is a tier 1 always better than a tier 2, or are they different levels of variance so you might prefer a more certain outcome from a tier 2? I know it’s relatively moot since you’d start anyone in those tiers, but it might matter for a tier 3 vs a tier 4.

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