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Great expectation dating site

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That gap -- 3.3 wins -- is the fourth-largest since 1989. The Jaguars, meanwhile, went 3-13 with the Pythagorean expectation of a 5.9-win team.

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As an example, consider the 99 teams who finished 8-8 between 19.To be clear, teams aren't "due" to decline and have a subpar record the following year; that's the gambler's fallacy.Teams with particularly good or bad marks during a year of one-score games are equally likely to be great or terrible in those games the following year.Adjusted net yards per attempt (or ANY/A) uses more modern research by Chase Stuart to estimate the value of touchdowns and interceptions while also incorporating sacks, which evidence suggests has plenty to do with quarterbacks despite being commonly blamed on the offensive line.You can find out more about ANY/A here.2017 impact: Despite receiving praise for his hot start, Carson Wentz had a dismal rookie season by ANY/A, ranking between Blake Bortles and Case Keenum at 27th among qualifying passers.In trying to break down football games and understand which elements of performance correlate best with winning, I've come to rely on a toolbox of statistics and concepts that give me a better sense of what's actually happening on the field.

Let's go through them and understand why they work (and where they come up short), starting with broader team metrics.

(I'm using seven points as opposed to eight to make it easier to compare teams across eras when the two-point conversion was not part of the NFL game.)Evidence suggests that teams like the 2001 Bears, a squad that went 8-0 in games decided by seven points or fewer, are extremely unlikely to keep that up year after year.

The following year, those same Bears went 4-6 in one-score games, with their overall record falling from 13-3 to 4-12.

YPA correlates well with winning, but the complicated passer rating statistic is better.

Passer rating is built on an antiquated framework and doesn't fit the modern game, so if we're going to use raw data to create a complex quarterback stat, we might as well use one built more recently that boasts a stronger quantitative underpinning.

We can figure out how many games a team "should" have won in a given season based off their point differential by calculating their Pythagorean expectation, a metric invented by Bill James for baseball and applied to football by Daryl Morey. More often than not, teams whose win total outstrips their Pythagorean expectation will decline the following year, as was the case with the 2016 Panthers and Broncos.