Thread by @WalkWearsCrocs

This flowchart shows my results from simulating NFL playoff overtime, a hot topic since the Super Bowl.

My numbers indicate that there is effectively no advantage between choosing to kick or receive, which aligns with research done by @bburkeESPN and @StatsbyLopez .

Details⬇️

I'm also attaching this version of the chart with a legend, which is slightly less twitter-friendly. The methodology is:

-Receiving team kicks XP on first possession
-Kicking team goes for two down 7
-Defensive scores not shown (happens about 1% of time)

The assumptions shouldn't be too controversial. If you score on first drive, you don't want to go for 2 because then more than half of your opponents' responding TD drives will end up in losses (the 50% of the time you fail your 2-pt, and the ~10% they match and then win later).

If your opponent scores 7 on the opening drive, you want to go for 2 because it's a 50% win proposition compared to 40% extending to sudden death where they have the ball first.

The logic between nodes should also be pretty straightforward. Kicking teams down a touchdown will never attempt a field goal, XP are some times unnecessary, sometimes the difference between outcomes, etc.

The key then is to figure out the transition probabilities between nodes. How do we determine the frequency at which teams will score 0, or 3, or 6-8 points? We can use a combination of empirical results and simulation.

For some nodes, simulation isn't necessary -- we have years of "old school" OT games to determine how often each team wins in a sudden death scenario. Other situations have little data (down 3 after the first possession), or none (down a touchdown after the first possession).

Simulating was done by stitching together drives from resampled plays in recent seasons using @nflfastR data. Constraints were added to make sure teams didn't do anything insane, e.g. kick a field goal down 7, and fourth down decisions were fed into @benbbaldwin 's model.

Plugging in a blend of these simulations and empirical distributions yields the percentages you see above. Chaining together the probabilities and gathering them at the end-of-game nodes gives nearly a 50% win probability for each team.

The results illustrate how close to being 50-50 the choice to kick or receive is under reasonable assumptions, which gives coaches the right to have a preference if they feel confident that their particular situation skews the underlying distributions.

If your defense is gassed then you might consider that first possession more score-heavy than reflected above; if you have one last trick play ready for your 2-pt conversion, maybe you don't mind having to go for 2; and so on

While I'm confident in my approach above, I'm sure there are legitimate critiques of the choices I made so I welcome any and all feedback. You can see the code here: github.com/WalkerHarrison…