How I Play “Real” Fantasy Football

Ten months ago, when I wrote My Super Bowl Rooting Record, the coronavirus we now know as Covid-19 was just starting to appear in the United States. The first U.S. death from the virus had occurred a few days earlier, though we didn’t learn this for months. The following post, which is a long overdue prequel to that February post, comes at a time when the virus has irrevocably altered lives around the world, and the positive case, hospitalization, and fatality numbers in the U.S. have reached record highs. Despite the NFL’s efforts, its 2020 season has been continually disrupted, and at this moment it’s not entirely clear that the full season will be completed as planned. While I do not wish to minimize the tragedies that this pandemic has brought upon us, I welcome NFL football as a distraction from them. And so I share this.

I understand why the NFL and its fans like fantasy football. The gamification of player performance helps keep fans engaged and paying attention even when their team isn’t playing, or when their team is playing but is hopelessly inept. Personally, however, I don’t care for fantasy football for this very reason: It causes fans focus on and care about factors that are not directly related to winning and losing games.

Traditional point-spread-style betting is better because it focuses on the outcomes of the games themselves, though still not strictly on the winning and losing. For example, if a team is favored to win by five points and you pick them to cover the spread, you’re disappointed if they win by a field goal, even though from the team’s (and the team’s real fans’) perspective, the victory is all that matters. Last weekend’s Seahawks vs. Eagles game illustrates the point nicely.

In reaction to all of this, I’ve developed my own system for picking games, which I refer to as “Real Fantasy Football.” Simply put, it’s my method of choosing which team to root for in each NFL game. This raises the questions, A) how do I pick the desired winner of each game, and B) how do I measure my success?

It started years ago with a simple rule of thumb that I employed for a long time: A successful NFL weekend for me was one in which the Seahawks, Jets, and Giants all won. The Seahawks because I’ve lived in the Seattle area for most of my adult life and have actively rooted for them for most of that time, the Jets because of my historical and long-suffering allegiance to them, and the Giants because of my legacy loyalty to all things New York.

You might wonder what happens when two of these teams play each other, and the answer is my default hierarchy is Seahawks over Jets over Giants. In rare cases I will flip that order when playoff considerations are at stake. In fact, the only time I ever rooted against the Seahawks in person at a Seahawks home game was in late December 2008, when they hosted the Bret Favre-quarterbacked Jets. The Seahawks were in their final season under coach Mike Holmgren and at 3-11 were already out of playoff contention, while the 9-5 Jets were fighting for a playoff spot. Of course, the Seahawks won. In the snow. The Jets ended up losing the following week as well, missing the playoffs, and firing coach Eric Mangini. In other words, a typical Jets season.

In my current system, I start by dividing each week’s games into three tiers. The top tier includes the games involving those three teams. The middle tier includes games that affect the playoff chances of those three teams. (In recent seasons this has meant the Seahawks’ playoff chances, though in 2020 the weakness of the NFC East means that the games involving the Giants’ division rivals are now in this tier.)

The bottom tier includes all games that don’t fall into either of first two tiers, and typically represents about half the total games. My determination in these games is based on my personal feelings about the teams involved, with several factors involved. Here they are, in no particular order, with some examples:

  • Preference for teams who have gone the longest without a championship or against those who have won many championships. Helps: Cleveland, Buffalo, Detroit, Minnesota, Philadelphia until 2017, Kansas City until 2019. Hurts: New England, Pittsburgh, Green Bay, Dallas, San Francisco.
  • Preference against bitter division rivals of my top tier teams. Hurts: San Francisco, New England, Miami, Dallas, Washington.
  • Preference against teams with offensive nicknames and logos. Hurts: Washington before 2020.
  • Preference for/against owners. Helps: Jacksonville. Hurts: Washington, Dallas, Las Vegas.
  • Preference for/against current GMs/head coaches. Helps: Denver, Kansas City, Atlanta. Hurts: New England, Las Vegas.
  • Preference for/against current players: Helps: Houston (Deshaun Watson). Hurts: Tampa Bay (Tom Brady).

Note that I do not take betting line favorites into consideration at all when making my picks.

In addition to the tiers, I rank all games in a given week from 1 to N. Typically the bottom few games each week fall into the “I don’t really care who wins, I just want the game to be exciting” category, but even in those games I force myself to pick a preferred winner.

As an illustration, let’s go through my picks for last week, Week 12 of the 2020 season:


The first three picks were a straightforward application of my top tier. Games 4 and 5 were to help Seattle reclaim first place in the NFC West, and games 6-8 were to help Seattle against its top-ranked conference rivals. Game 9 was to help the Giants claim first place in the NFC East. Games 10 and 11 were based on giving preference to Buffalo and Cleveland, though in this case both of their opponents happened to also be in the “never won a Super Bowl” club. Game 12 was rooting against Las Vegas. The remaining games were based on the mildest of preferences.

How do I measure my success? The simplest manner is total number of successful picks. Also, because my methodology leads me to disproportionately root for underdogs, I compare my results against the designated favorites for each game (going 7-9 when I’ve picked six favorites is better than going 9-7 when I’ve picked ten favorites). Finally, I calculate a weighted score by giving 3, 2, and 1 points per game to each respective tier. (Having the Jets and Giants go a collective 4-18 through the first twelve weeks of the 2020 season has not aided this last metric.)

It turns out that Week 12 was not a representative sample of my record. At 11-5, it was my best week of the season, not only in absolute terms but by having picked five more winners than favorites. (Contrast it with Week 7, in which Cleveland was my only successful pick.) Here is my week-by-week record to date for 2020:

WeekFavorites PickedRecordWeighted Score

So at the beginning of the season I fell quickly behind the favorites tally. This isn’t entirely surprising, as the who the favorites are gets more accurate when there is more recent regular season game data, especially in 2020, with its absence of preseason games and reduced home field advantage. With a strong Week 12 showing I’ve nearly caught back up.

When I started this system several years ago, I waited until around Thanksgiving to start picking games, figuring that the games didn’t matter until the playoff stakes were evident. But starting last season (2019), I’ve begun with Week l and continued through the playoffs and the Super Bowl. It may appear from this detailed description that I spend a lot of time on this, but in practice it occupies less than fifteen minutes per week. I especially value that I now start each NFL weekend with a clear sense of which games I should care most about.

Every year I revise this system, so 2021 will see some tweaks. I’m considering changing how I calculate the weighted score to give more relative weight to all Seahawks games — realistically, I care a lot more about how the Seahawks do each week than all of the bottom tier games put together — and/or playoff-affecting games that occur later in the season.

One response to “How I Play “Real” Fantasy Football

  1. Pingback: Hitting the Danny Trifecta | Danny Glasser

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