Crush Your Home League with These Simulations and a Simple Pick Prediction Tool
Image Credit: Leslie Plaza Johnson/Icon Sports. Pictured: Laviska Shenault.

I don’t care if you are in 100 expert leagues, the one you want to absolutely crush is still that first “home” league you joined with your local friends and family.  No one wants to come into the office after a close loss to your raucous coworker.

If you are like me you’ve noticed that these drafts are usually very different from your typical sharp drafts, so I’ve spent some time analyzing the differences and developing a process for taking these leagues down specifically. For the purposes of the article, we will be looking at the full planning process I went through for my upcoming draft.

Platform: NFL.com
Scoring: Half PPR
Teams: 10
Rosters: QB/2RB/2WR/TE/FLX/PK/DEF + 6 BN

Exploiting Platform Rankings

The first major change I developed from a normal draft procedure is in regard to average draft position (ADP). Most of your league mates are going to be rolling into the draft with less preparation than you. Because of this, your draft is unlikely to follow ADP. Instead, it will follow the default rankings present in the draft room for your platform.

Second, I did a regression analysis on the volatility in a player’s ADP throughout the draft and found that it is much more predictable than you would think!

I put these two findings together in a simple tool.[1] You can just insert a player’s ranking from your draft platform and it will tell you the percentage chance that player will be available at each pick.

Chance of Falling:


For example, one of my targets, Laviska Shenault Jr., has a site ranking of 133 on NFL.com. From the tool, to have at least an 80% chance of him being there, I would need to select him by pick 121. Prior to my drafts, I like to identify a list of targets especially after Round 6 and plan out where to slot them into my draft round-by-round with this procedure.

Identifying Targets

Footnotes

Footnotes
1 You can find the tool here: Chance of Falling to Pick X

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Matt Spencer

Machine Learning Approach to Football Analytics with JavaScript

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