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Week 6 DraftKings Thursday Night Football Showdown: Washington Commanders at Chicago Bears

Landover, Maryland, USA; Washington Commanders wide receiver Terry McLaurin (17) warms up before the game between the Washington Commanders and the Philadelphia Eagles at FedExField. Mandatory Credit: Brad Mills-USA TODAY Sports

• Best CPT values: Commanders WR Terry McLaurin has the most positive leverage for the CPT spot.

• Best FLEX values: Bears WR Darnell Mooney and the Washington Commanders defense look like the best value in the FLEX position among the highest-salaried players.

Click here to become an expert on the Showdown format and winning strategies.

Estimated Reading Time: 5 mins

This season, we'll analyze all of the NFL’s “island” games (TNF, SNF and MNF) and playoff matchups, utilizing PFF’s weekly projections, current betting lines and millions of simulated historical combinations to identify the best and worst values for an upcoming matchup.

There are five main components to this Showdown slate analysis that you’ll find below:

A breakdown of methodology and the most similar historical matchup to this game: 2022 Week 3: Chicago BearsHouston Texans, with Justin Fields as himself and Davis Mills playing the role of Carson Wentz.

Optimal lineup allocations (CPT and total roster) for both teams based on the results of similar historical matchups.

Comparison of player ownership projections for FLEX and CPT, produced by a model trained on 2018-2022 Showdown contest results to optimal allocations.

Recent CPT ownership trends illustrated for both starting lineups.

A table showing the most common players on optimal lineups for each player. This allows you to see which other players are commonly found on the same optimal lineups as a player you’re interested in rostering.


To analyze this specific Showdown slate, I looked through thousands of NFL matchups from 2014 to 2022 and found the closest analogies to this contest according to the following parameters: Betting spread, over/under and average fantasy points scoring for the top-ranked positional players of both rosters (QB1, RB1, WR1, TE1).

I won’t detail every matchup that falls into the top 100 for this game, but for illustration purposes, let’s look at the most similar matchup:

Historical Current
Player Pos Team Player Pos Team
Justin Fields QB CHI Justin Fields QB CHI
David Montgomery RB CHI David Montgomery RB CHI
Darnell Mooney WR CHI Darnell Mooney WR CHI
Cole Kmet TE CHI Cole Kmet TE CHI
Davis Mills QB HOU Carson Wentz QB WAS
Rex Burkhead RB HOU Antonio Gibson RB WAS
Brandin Cooks WR HOU Terry McLaurin WR WAS
O.J. Howard TE HOU John Bates TE WAS

The spread and over/under are similar in these matchups (Bears -3, 39.5 O/U versus this matchup at Bears -1, 38 O/U). All the players aren’t perfect matches, but that’s why we use 100 similar matchups and not just the single most similar.

The optimal roster for that historical matchup, assuming positional salaries equaled what they are for this showdown slate, would have been:

Player Team Position Roster Position Fantasy Pts
Khalil Herbert CHI RB CPT 33.9
Dameon Pierce HOU RB FLEX 18.2
Cairo Santos CHI K FLEX 14.0
Jordan Akins HOU TE FLEX 12.1
Texans HOU DST FLEX 12.0
Davis Mills HOU QB FLEX 11.8

For this game and 99 other similar matchups, I calculated every possible combination that fits with Showdown rules (one CPT, at least one offensive player from each team) and would fall under the $50K salary threshold, assuming the salaries for the historical similar matchups are the same as those for this contest.


The most unique part of the format, and therefore the biggest opportunity for a competitive advantage, is choosing your CPT. Should you always choose a QB who typically has the highest absolute fantasy scoring? Are defenses and kickers viable options? RB versus WR?

I went through the millions of possible lineup combinations for the 100 most similar matchups and found who the CPT selections were on the top-five scoring lineups for each matchup. Here are the 500 CPT choices from those matchups by position rank according to salary.


This graph illustrates the full range of allocations for the different positions to measure how many of the 500 optimal rosters had exactly zero, one or two of the given positions.


The boxplot above shows the ranges for CPT ownership for each starting player in contests since 2019.

Projected ownership versus optimal

This is where the analysis comes together and becomes actionable. What’s most important when viewing these numbers is to contrast them to the optimal numbers taken from the analysis above for different positions. Then, we see where the leverage may exist.

The two tables below compare the optimal allocations above, with adjustments for the personnel of this particular matchup, to our ownership projections for CPT and FLEX.



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