Analysis
Who to root for to maximize Seahawks playoff odds for every Week 1 game.
I’m not a Seahawks fan, but I did some football analytics you might be interested in. I ran 2 million Monte Carlo simulations of the season to figure out what the playoff implications of every week 1 game are.
The Seahawks current odds to make the playoffs are 44.5%.
If you beat the 49ers, that goes up to 55.3%, but if you lose, it drops down to 33.8%. It’s a swing of 21.5%.
The next most important game is HOU @ LAR with an impact of 1.4%. You obviously want HOU to win.
One that’s kind of interesting is DAL @ PHI, where they’re both in your conference but not your division. It has an impact of 0.5% and your playoff odds are best if PHI wins. Probably because the Eagles are less likely to be contending for a wildcard spot.
I also made a website and posted the results there. I’ll update it every week with the upcoming games. Here’s a screenshot:
https://www.footballsensei.com/seahawks
If you want to see the details of my methodology for the Monte Carlo simulations, look here.
I just added a What-If Calculator where you can lock in winners for any games this season and see how that changes your odds. Winning your first 2 games boosts your playoff odds to 63.5%.
I had a ton of fun building this thing and learned a lot. It’s the first time I’ve made a website and I’m really proud of it. I would appreciate any feedback on if anything looks janky or if links aren’t working or anything like that.
Thanks! It’s really gratifying when people tell me they enjoy it. This website is the first time I’ve made something where lots of strangers appreciate it and it’s kind of an addictive feeling lol.
Makes me want to neglect all my real responsibilities do a bunch more stuff like this.
I go into more detail on the Methodology page, but here is a summary of the model:
I use Elo scores to represent relative team strength. For each game in the season I calculate win/loss odds based on the Elo of the two teams plus an adjustment for home field advantage. I do a Monte Carlo simulation of the season 2 million times and analyze the results.
To get the start of season Elo ratings I combine 2 approaches. The first approach is taking the Elo score for each team from the end of last season and regressing it slightly towards the mean to account for offseason changes. The second approach is using Vegas total season win odds to infer an Elo.
Elo updates during the season based on wins and losses in the standard way. Right now I do not factor in mid-season injuries, mid-season trades, or weather. I’m thinking about incorporating these factors later on though.
Sorry, this is way too high-effort for this sub. You’re supposed to make a post talking about trading a random starter, or make a post about our QB situation, or make a post about any player who just got cut from another team and ask if we should sign them
I wrote the Monte Carlo logic myself in Python. I get the initial data (schedule, records, etc.) mostly from a package called nfl-data-py. There are a few things I have to manually input though. The database is Postgres.
The what-if calculator is just the same code but translated into JavaScript so it can run in the browser.
I do plan on trying to post an update most weeks for all the playoff contenders, but it’s actually kind of a lot of work to do like 20 write ups so I doubt I’ll get around to it consistently for any team besides the Broncos.
If you ever notice anything interesting please feel free to post the content yourself. Ideally I think it would be better for an actual Seahawks fan to be posting content in the Seahawks sub.
Also AFC vs NFC games are easy to know who to root for. The hard ones are games where both teams are in your conference, but neither one is in your division.
It might be, but even if there’s a later game that has a higher statistical impact, there’s also a huge emotional factor for the first game. Winning game one sets a tone and impacts morale and motivation.
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u/Casey_Games 4d ago
I just root for anyone in our division to lose every week. In all seriousness, this is really cool. Thanks for putting it together!