
If you want a great example of the difference between a large sample size and a small one, look no further than a recent ESPN.com project using its "Football Power Index" simulations.
Running 20,000 simulations of the 2019 season, the FPI finds that the NFC North is essentially a three-way toss-up between the Vikings, Bears and Packers. All three are projected to win between 8.6 and 8.8 games, with all three projected among the top 10 NFL teams and the Vikings given the slightest of slight edges over the other two.
But ESPN also isolated on one specific simulation – No. 1,721, according to the web site – to project outcomes for all 267 games in the season for the entire NFL. In that one simulation, the Vikings lost 27-13 to the Falcons in Week 1 and went just 7-9 for the season while the Bears went 8-7-1. The Packers dominated the NFC North, going 13-3.
Vikings fans are hoping for any of the other 19,999 potential realities, I would imagine (though it should be noted the Packers at least were bounced from the playoffs).
These differences in scale, though – one vs. 20,000 – are fascinating when placed side by side.
And picking just one out of 20,000 reveals a haunting but marvelous truth about sports: The season that eventually actually does happen doesn't necessarily most accurately reflect the composite strengths and weaknesses of teams.
It's a snap shot of randomness, fortunate bounces, magnificent performances and being in the right place at the right time (or wrong place at the wrong time).
But you can't play the 2019 season 20,000 times in real life (though the NFL owners might love to try to add it to the new collective bargaining agreement to goose TV revenue). Only one season can become reality.