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Week 4 DraftKings Monday Night Football Showdown: San Francisco 49ers vs. Los Angeles Rams

September 18, 2022; Santa Clara, California, USA; San Francisco 49ers running back Jeff Wilson Jr. (22) runs with the football against Seattle Seahawks cornerback Mike Jackson (30) during the fourth quarter at Levi's Stadium. Mandatory Credit: Kyle Terada-USA TODAY Sports

• Best CPT values: Jeff Wilson Jr. and Allen Robinson II are both projected to have materially lower roster percentages than the likelihood of being the optimal CPT.

• Best FLEX values: Jimmy Garoppolo and Cam Akers are the strongest value FLEX choices.

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Estimated Reading Time: 6 mins

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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: 2019 Week 8: Tennessee TitansTampa Bay Buccaneers, with Ryan Tannehill as Jimmy Garoppolo and Jameis Winston playing the role of Matthew Stafford.
  • 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
Ryan Tannehill QB TEN Jimmy Garoppolo QB SF
Derrick Henry RB TEN Jeff Wilson Jr. RB SF
Corey Davis WR TEN Deebo Samuel WR SF
Jonnu Smith TE TEN George Kittle TE SF
Jameis Winston QB TB Matthew Stafford QB LAR
Peyton Barber RB TB Cam Akers RB LAR
Chris Godwin WR TB Cooper Kupp WR LAR
Cameron Brate TE TB Tyler Higbee TE LAR

The spread and over/under are similar in these matchups (Titans -2, 45.5 O/U versus this matchup at 49ers -1.5, 42.5 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
Mike Evans TB WR CPT 45.8
Jameis Winston TB QB FLEX 24.3
Jonnu Smith TEN TE FLEX 19.8
Ryan Tannehill TEN QB FLEX 19.4
Cody Parkey TEN K FLEX 12.0
Titans TEN DST FLEX 11.0

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 with 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 PFF's ownership projections for CPT and FLEX.



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