Week 11 WRs Uncertainty Tiers [Visualization + Table]
1First 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:
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 http://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.
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.