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Describing the Seattle Seahawks' Awful 2008 with Ever More Complex Statistics

There was a time when statistical analysis was the oil in my engine and few features on Field Gulls lacked it. Sports fans love stats. The modern order of baseball-style advanced stats has permeated almost every sport. I imagine it isn't long before MMA adopts an adjusted-elbows-over-average metric. The problem is, with the good comes the bad. With the illuminating comes the confusing, manipulative and ultimately stupefying. It might have read credible to cook numbers until I got what I wanted, but it wasn't intelligent analysis.

Nevertheless, a host of good stats exist. Ones with logical bases and an understandable methodology. In this murky period where we pat down the dirt of last season and begin blueprints for the next, here's a look at Seattle through the lens of statistics.

Record: 4-12

Statistical analysis needs a semantic enema. We too often talk about "luck and skill". Did Seattle luck into its four wins or get screwed out of more? I offer 4-12 is a perfect reflection of the 2008 Seattle Seahawks skill and a lousy starting point to determine the 2009 Seattle Seahawks skill. All those missed fumbles, botched third downs and injuries, injuries, injuries reflected some kind of skill, some kind of decision making and some kind of accomplishment or failure, but many are never likely to happen again. So buck up Seahawks, you sucked, and given it all over to do again, you could have sucked differently. Next season you will likely suck in whole other ways or maybe even not suck at all.

Useful Bar Stat: Record against River Boat Gamblers: 1-0

Expected Win Loss: 5.4-10.6

This is instructive because it adds a qualitative measure to Seattle's wins and losses. Therefore, scraping out a victory is not as valuable as blowing an opponent out. It also removes leverage, which is a bit of bad thing. Point differential doesn't matter much in the standings and NFL coaches run notoriously permissive defensive packages during blowouts. It also doesn't adjust for strength of opponent. Despite all that, Pythagorean wins correlate much more strongly to a team's record the following season. Meaning that though Seattle lived in the slums, it was but a hop skip and jump over a dead bum to the bad part of Mediocrity Village.

Useful Bar Stat: Expected Win Loss projected strictly from Seneca Wallace starts: 7.2-8.8

Total DVOA: -23.0% (29th)

DVOA is a proprietary "system that breaks down every single play and compares a team's performance to the league average based on situation in order to determine value over average." In other words, a four yard run on first and 10 is compared to all runs made by all teams on first and ten, evaluated for success and then adjusted for opponent. It's a clever system well met for the challenges of football. Football is extremely relativistic, and there's a moving target for what is successful. Seattle had two targets: its foot and its fans. One reason Seattle's DVOA reflects its overall record more than its Pythagorean record is three of its four wins came against teams ranked in the bottom quarter of the league. And remember that awesome win against the playoff bound Jets? Well the Jets missed the playoffs and finished 19th in total DVOA. That means the majority of teams should expect to beat the Jets and all but the worse should beat them when playing at home.

Useful Bar Stat: Bodacious Index of Winning One for Holmgren: Brodadical Rex

We'll finish this next week, with a look at drive stats, team efficiency and an estimate of how many points Seattle lost because of injury.

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I'm curious

how you’re going to account for injured players playing when they shouldn’t and/or are surrounded by players that are doing the same thing.

I.E. a beat up Matt Hasslebeck who was surrounded by injured/back up recievers and throwing even though he was injured. In other words, I’m wondering how you’re going to figure out how he would have played had we stuck closer to the league average on injuries (the points we lost because of injury). A strict enlargement of the games he played will include lousy games where he was injured. A strict enlargement of the games where he wasn’t injured is such a small sample size. I honestly have no idea how to approach that problem, short of some combination of stats between last year’s numbers, his injured game numbers from this year, and his non-injured game numbers
from this year.

Either way, I can’t wait.

by Fear on Feb 6, 2009 2:38 PM PST reply actions  

That's going to be a fascinating piece.

I’ve been wondering for a while what our record could have looked like had we not lost certain players for extended periods.

by BrianL on Feb 6, 2009 2:41 PM PST up reply actions  

I will require some estimates based on replacement level

It won’t be precise, but it should give a meaningful interpretation of how many points Seattle lost due to injury.

by John Morgan on Feb 6, 2009 2:42 PM PST up reply actions  

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