Over the past four years, Shawn Siegele has finished first, second, first, and first in the MFL10 of Death, proving it’s always better to be lucky, even if you are decent. In this series, The Best Ball Workshop, he discusses tactics and explains how you can use the RotoViz Best Ball Tools to create a virtual money machine from your best ball drafts.
Waiting for the launch of the best ball tools from Mike Beers has been like waiting for your parents to get up on Christmas morning. And unwrapping them today gave me that same jolt you got when Santa perfectly delivered for your five-year-old self. Mike is a best ball savant, and his tools are everything you’d expect from this fantastic fantasy mind.
I’ve been cheating and playing with the toys behind the scenes, and so we’re going to jump right in with Lesson 1. But first, a little context.
The apps include tools for FFPC, Fanball, DRAFT, and Fantrax and are tailored to the format. You can track ADP and personal exposures, examine the types of builds players are using in 2019, and research what has worked in the past with the Roster Construction Explorer. Every time I dive into this tool, I look up later and find hours, not minutes, have passed. The RCE will form the basis for the Best Ball Workshop.
Contingency-Based Drafting
In last year’s strategy session, How to Create League-Winning Scenarios in the MFL10 of Death, I detailed the main principles for winning drafts:
- Use structural drafting to increase your flexibility instead of limit it. Use it to supercharge your player-picking expertise instead of finding yourself chasing volume on players you’d otherwise prefer not to draft.
- Instead of chasing early-season volume, emphasize scenarios where you can gain the largest shift in volume.
- Create scenarios where as little as possible has to go right in order to win.
- Win individual portions of the draft.
Over the course of his series, we’re going to discuss how to accomplish these objectives by using the different types of evidence at our disposal.
Player Win Rates
In Lesson 1, we start with the basics, looking back at 2018 to see who won and lost leagues.
Player Win Rates – Top 10 2018
| Rank | Player | Pos | ADP | Pts | Win Rate |
|---|---|---|---|---|---|
| 1 | Christian McCaffrey | RB | 16.7 | 351.2 | 0.27 |
| 2 | James Conner | RB | 200.3 | 267.6 | 0.22 |
| 3 | Patrick Mahomes | QB | 129.2 | 416.95 | 0.21 |
| 4 | James White | RB | 111.7 | 246.3 | 0.19 |
| 5 | JuJu Smith-Schuster | WR | 45.6 | 261.7 | 0.18 |
| 6 | Saquon Barkley | RB | 7.9 | 342.9 | 0.18 |
| 7 | Zach Ertz | TE | 36.4 | 240.8 | 0.17 |
| 8 | Davante Adams | WR | 19.2 | 305.5 | 0.17 |
| 9 | Tarik Cohen | RB | 71.3 | 219.55 | 0.17 |
| 10 | George Kittle | TE | 113.9 | 214.4 | 0.16 |
Five of the top 10 players in win rate came from the running back position, and our first instinct would be to employ a RB-heavy approach as a result. But a closer look reveals James Conner from our list of Handcuffs Who Could Be RBs1 and James White and Tarik Cohen from our 2018 Zero RB Candidates.
If we focus on players drafted in the first four rounds, the picture changes.
Player Win Rates – First 4 Rounds ADP 2018
| Player | Pos | ADP | Pts | W16 |
|---|---|---|---|---|
| Christian McCaffrey | RB | 16.7 | 351.2 | 0.274 |
| Saquon Barkley | RB | 7.9 | 342.9 | 0.181 |
| JuJu Smith-Schuster | WR | 45.6 | 261.7 | 0.181 |
| Zach Ertz | TE | 36.4 | 240.8 | 0.171 |
| Davante Adams | WR | 19.2 | 305.5 | 0.168 |
| Travis Kelce | TE | 27.7 | 273 | 0.163 |
| Alvin Kamara | RB | 6.1 | 327.7 | 0.158 |
| Adam Thielen | WR | 29.8 | 287.3 | 0.145 |
| Tyreek Hill | WR | 28.1 | 286.3 | 0.143 |
| Todd Gurley | RB | 1.2 | 372.1 | 0.131 |
| Stefon Diggs | WR | 32.8 | 238.6 | 0.113 |
| Amari Cooper | WR | 37.5 | 203.3 | 0.109 |
| T.Y. Hilton | WR | 30.1 | 210.1 | 0.102 |
| Michael Thomas | WR | 14.9 | 279.7 | 0.100 |
| Brandin Cooks | WR | 43.1 | 210.8 | 0.095 |
| DeAndre Hopkins | WR | 8 | 287.4 | 0.094 |
| Jarvis Landry | WR | 47 | 184.1 | 0.093 |
| Joe Mixon | RB | 23.6 | 221.9 | 0.091 |
| Derrick Henry | RB | 37.2 | 173.7 | 0.085 |
| Melvin Gordon | RB | 11 | 251.5 | 0.082 |
| Ezekiel Elliott | RB | 3.8 | 311.3 | 0.081 |
| Mike Evans | WR | 23 | 240.8 | 0.081 |
| Antonio Brown | WR | 5.2 | 279.2 | 0.077 |
| Julio Jones | WR | 13.2 | 284.3 | 0.075 |
| Kenyan Drake | RB | 35.3 | 182.3 | 0.074 |
| Keenan Allen | WR | 16.1 | 238.9 | 0.070 |
| Golden Tate | WR | 46 | 172.3 | 0.069 |
| Kareem Hunt | RB | 9.3 | 230.2 | 0.066 |
| Allen Robinson | WR | 42.3 | 139.9 | 0.066 |
| Josh Gordon | WR | 46.3 | 138.7 | 0.062 |
| Demaryius Thomas | WR | 44.3 | 150 | 0.057 |
| Larry Fitzgerald | WR | 34.2 | 155.5 | 0.056 |
| Mark Ingram | RB | 38 | 124.9 | 0.056 |
| Alex Collins | RB | 44.4 | 108.6 | 0.052 |
| Odell Beckham | WR | 10.7 | 231.4 | 0.049 |
| Jay Ajayi | RB | 45 | 43.4 | 0.047 |
| Doug Baldwin | WR | 29.8 | 111.5 | 0.045 |
| Derrius Guice | RB | 37 | 0 | 0.039 |
| A.J. Green | WR | 19.6 | 149.4 | 0.037 |
| Jordan Howard | RB | 25.5 | 140.6 | 0.036 |
| Rob Gronkowski | TE | 23.8 | 126.8 | 0.034 |
| Dalvin Cook | RB | 14.3 | 128.2 | 0.031 |
| Leonard Fournette | RB | 11.3 | 104.3 | 0.029 |
| David Johnson | RB | 3.3 | 221.1 | 0.028 |
| LeSean McCoy | RB | 25 | 109.9 | 0.026 |
| Jerick McKinnon | RB | 27.4 | 0 | 0.025 |
| Devonta Freeman | RB | 21.1 | 14.1 | 0.019 |
| Le'Veon Bell | RB | 2.3 | 0 | 0.008 |
The top two players by win rate are still star RBs, Christian McCaffrey and Saquon Barkley, but suddenly we see just how risky the position is. Only four RBs find their way into the first 16 players by win rate. By contrast, the first four rounds are full of RB landmines. Twelve of the bottom 16 players are RBs, including the worst seven.
The Roster Construction Explorer
Here’s where the Roster Construction Explorer comes in handy. We can test whether these individual win rates tell us something important about overall team win rates, and we can see if 2018 was a one-year aberration.
The RCE allows us to do a ton of different calculations, but we’ll start with something simple today and build out from it.
We can test whether RB-heavy or WR-heavy starts have been more successful by using the Round-By-Round settings. (We’ll set the Table Settings to TE to make it easy to see the differences.) By choosing a construction where we select three RBs in the first four rounds, we can investigate the win rates.
Over the last four years, 37,855 teams have selected three RBs in the first four rounds. The results are shockingly poor with an average score of 2180 and an average win rate of 6.7 percent.
By contrast, a start with three wide receivers was both more popular and much more effective.
Owners who started with three WRs in the first four rounds averaged over 2200 points and won 9.0 percent of the time.
This is particularly relevant as we head into 2019 with RBs gaining popularity. Last season, the RB-heavy start was almost as popular as WR-heavy and the gap in results was even more pronounced. RB heavy starts won less than five percent of the time, while WR-heavy starts jumped over 10 percent. The point gap rose to over 100.
More to Come
There’s more to it than this, of course. We’ll look at more individual seasons in the future, as well as examining a variety of ways you can boost your win rate well beyond 10 percent.
Finally, player selection does matter. Recommending you do whatever it takes to get Christian McCaffrey last season was one of my favorite calls for RotoViz subscribers. If you roster league-winning players, your results will reflect that. But while I owned a lot of McCaffrey last season, I passed on him in the MFL10 of Death and continued with the Zero RB approach that has paid dividends for me even in the RB-friendly seasons.1 Using structural advantages gives you the best opportunity to take advantage of both luck and your player-picking prowess.
This is just the beginning. We’ll dive into that and much more as we move through the lessons in the Best Ball Workshop.
- To be clear, RB-heavy had an edge in win rate for 2016 but was swamped by the large edge for WR-heavy in 2015 and 2018 when we look at the sample as a whole. (back)
