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NFL Season Predictions: What The Bill James Indicators Foresee For The NFC East

At this time of year there's one question floating around somewhere in the minds of all NFL fans: Just how good will my team be this year? We use six different indicators to look at what could be in store for the NFC East.

Rob Carr

Bill James, godfather of advanced baseball stats, used to look at six indicators in his Baseball Abstracts to help predict whether a team would improve or decline in the next season. Today we'll use those indicators to see what they can tell us about the NFC East heading into the 2014 season.

Just a small word of caution up front. James developed the indicators for baseball, not for football. I can't vouch for their validity in baseball, much less in the NFL, but I thought they'd provide an interesting starting point for discussion, as they provide at least some quantitative basis for preseason predictions. Also, because the indicators look at stats from a macro perspective, they can help highlight trends that we might miss as we get lost in the minutiae of roster battles, position rankings and draft pick evaluations.

So without further ado, here are the indicators, and how each NFC East team stacks up:

1. Pythagorean Wins. The Pythagorean formula predicts a team's W/L record based on points scored and points allowed. When a team wins more games than it is projected to win, that team will tend to decline in the following season. Conversely, when a team wins significantly fewer games than projected, that team will tend to improve in the following season. The table below summarizes the win projections and variances for the NFC East teams.

Team 2013 W/L Points
Variance Trend for 2014
Eagles 10-6 442 382 9.4 +0.6
Cowboys 8-8 439 432 8.2 -0.2
Giants 7-9 294 383 5.6 +1.4
Redskins 3-13 334 478 4.8 -1.8

Of the four NFC East teams, the Giants have by far the biggest positive variance between their actual and projected wins. The Pythagorean formula suggests that the Giants outperformed their true level of performance by 1.4 wins. Research by Bill Barnwell shows that there were 97 teams between 1983 and 2010 that outperformed their projection by between 1.0 and 1.5 wins. Those teams declined by an average of 1.5 wins the following season.

Going by Barnwell's numbers, the Eagles would decline by 0.9 wins this year, the Cowboys would remain flat, and the Redskins would improve by 2.5 wins. Overall, this indicator suggests that the Redskins are likely to improve their record in 2014, while the Giants and Eagles are likely to regress.

2. "It’s not how you start, it’s how you finish". Teams who play better in the second half of the season tend to improve the following season. It follows that teams who play worse in the second half tend to decline the following season. Because the NFL season is only 16 games versus the 162 in a baseball season, this indicator is closely related to the first indicator.

So we'll use the Pythagorean Formula once more to calculate the projected wins for the NFC East teams based on the last eight regular season games from 2013 of each team.

Team 2013 W/L* Points
Variance* Trend for 2014
Eagles 7-1 266 171 5.9 +1.1
Cowboys 4-4 209 246 3.2 +0.8
Giants 5-3 153 160 3.8 +1.2
Redskins 0-8 131 225 1.7 -1.7
* Last eight regular season games

By this reckoning, the Eagles, Cowboys and Giants all played worse in the last eight games than their record indicates, so all three should expect to decline in 2014. Good news for the Redskins: As much as they sucked down the stretch, they didn't suck quite as badly as their record indicates.

Of course, this is where we run into the plague of NFL stats: small sample size. Applying the Pythagorean Formula to a 16-game schedule is already dubious at best, and it doesn't get any better when using it against an eight-game schedule, but there's nothing we can change about it except to exercise some caution in not overinterpreting these results.

3. "Plexiglass Principle". In simple terms, teams that show a dramatic improvement (or decline) from one season to the next have a tendency to relapse (or bounce back) in the following season. The Cowboys of course have shown all the bouncing ability of Ayer's Rock over the last three years with their succession of 8-8 records. But the other teams did bounce around a lot.

Team 2012 Wins 2013 Wins "Bounce" Trend for 2014
Eagles 4 10 +6
Cowboys 8 8 0
Giants 9 7 -2
Redskins 10 3 -7

The question here is which of the two seasons to consider the norm and which the aberration. We'll consider 2012 the baseline, but an argument can be made for both the Eagles and Redskins that 2012 was the aberration, and the bounceback already happened in 2013.

4. Regression to the mean. This statistical phenomenon describes the fact that if a variable is extreme on its first measurement, it will tend to be closer to the average on a second measurement. In sports, this means that teams with a winning record tend to decline; teams with a losing record tend to improve.

The formula we'll use to calculate this is straightforward: Starting with 8 wins, add 0.25 wins for every win above 8 from the previous year, or subtract 0.25 wins for every win below 8 from the previous year. For example, a 12-win team from 2013 would be predicted to have 8 + (12-8)/4 = 9 wins in 2014.

Team 2013 W/L Base wins 0.25 per game
above or below .500
Trend for 2014
Eagles 10-6 8 +0.5 8.5
Cowboys 8-8 8
0 8.0
Giants 7-9 8 -0.25 7.75
Redskins 3-12 8 -1.25 6.75

The Redskins, because they are the statistical outlier in this group, benefit the most from the Regression To The Mean indicator. The data here also confirms what the Cowboys have proven now for three consecutive years: When you're at 8-8, the stats suggest you may have a hard time moving away from that record.

5. Team Age. Young teams improve; old teams don't. This early in the season, we have only the vaguest idea of what the rosters for the NFL teams will look like, and looking at team age doesn't make a lot of sense before the final rosters are set. But here we are in July and want to make a prediction, so I went and looked at the current age of the 22 starters for each team as per the depth charts.

Team Combined Starter Age
Avg. Starter Age Trend for 2014
Eagles 592 26.9
Cowboys 587 26.7
Giants 597 27.1
Redskins 603 27.4

By this method, the Cowboys have the youngest team with a combined age of 26.7 (587 combined years for their 22 projected starters, despite having the oldest QB), while the Redskins have the oldest team (despite having the youngest QB). A lot is likely to change with these roster projections between now and opening day, but for now, I'm awarding the Cowboys an up-arrow and the Redskins a down-arrow.

6. Record in close games:  Bill James' sixth indicator is Triple A performance, but since developmental leagues don't exist for the NFL, I'm picking record in close games as the sixth indicator. It's awfully hard to consistently win a high percentage of games decided by seven points or less, and the vast majority of teams will see their performances in these types of games regress to the mean from year to year. Here's how the East fared in games decided by seven points or less last year:

Team 2013 Close game record
Trend for 2014
Eagles 3-1
Cowboys 5-5
Giants 3-3
Redskins 2-6

Whether the Redskins badly sucked or were just unlucky, and whether the Eagles were really good or simply lucky is for us to think about and Redskins/Eagles fans to hyperventilate about. At the end of the day, it's unlikely that extreme outliers in performance can be maintained year after year.

Summing up the Indicators

You may want to add up the wins and losses each indicator projects for each team; I'll simply tabulate the number of arrows below and let you draw your own conclusions.

Team 2013 W/L Pythagorean
Last 8
Plexiglass Regression
to the mean
Team Age Close Games
Eagles 10-6
Cowboys 8-8
Giants 7-9
Redskins 3-13

What this exercise shows is that there are some larger-scale statistical trends that can have an influence on how a season progresses. These larger-scale trends favor the Redskins to improve, but it's not clear by how much. Similarly, the indicators suggest the Eagles will decline this year, but by how much? Based on these indicators alone, the East looks wide open this year.

But the NFL is not baseball. And picking six largely random stats to make a projection is very arbitrary. There are so many different factors determining who wins and who loses each Sunday that an accurate projection is nearly impossible, and that's without even factoring in the biggest driver of NFL game results: randomness.

For the Cowboys, there is one key takeaway here. Unless something changes significantly, there is little reason to believe the Cowboys will finish the year with anything else than another middling record. However, that "something" can come from a lot of different sources. Team health, better playcalling, an improved pass rush, better pass defense, a few breakout players, scheme familiarity, a dominant O-line, better third down conversion/defense, better safety play, and many more topics that we have and will continue to cover this offseason.

But it's got to be something if you don't want to be stuck in the middle.

You got to be starting something.

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