As we did last year, today I’m going to calculate the final 2014 Game Scripts and Pass Identity data. Every week during the season, I write about the Game Scripts from the previous weekend. For new readers, the term Game Script is just shorthand for the average points differential for a team over every second of each game. You can check out the updated Game Scripts page, which shows the results of all 256 games from 2014, and you can read the history behind the metric here.

Let’s begin by looking at the 2014 Game Scripts numbers. The Packers held an average lead of 6.9 points during their regular season games, the highest average in all of football. Because Green Bay was so good, Aaron Rodgers and the Packers weren’t very pass-happy; in fact, the Packers ranked just 21st in pass attempts. That’s why Jordy Nelson and Randall Cobb, as good as their raw numbers were, look even better in some advanced metrics. In some ways, the Packers were the victims of their own success last year, as Green Bay was — by far — the best first half team in the NFL in 2014. That led to the high Game Script number, and a lot of casual dress second halves.

Rk Team GS Record 1 Green Bay Packers 6.9 12-4 2 Denver Broncos 4.7 12-4 3 New England Patriots 4.6 12-4 4 Dallas Cowboys 3.2 12-4 5 Indianapolis Colts 3.1 11-5 6 Seattle Seahawks 3 12-4 7 Philadelphia Eagles 3 10-6 8 Baltimore Ravens 2.6 10-6 9 Houston Texans 2 9-7 10 Cincinnati Bengals 1.7 10-5-1 11 Kansas City Chiefs 1.3 9-7 12 Pittsburgh Steelers 1.2 11-5 13 St. Louis Rams 1.1 6-10 14 Buffalo Bills 1 9-7 15 Miami Dolphins 1 8-8 16 San Francisco 49ers 0.8 8-8 17 Detroit Lions 0.4 11-5 18 New York Giants 0.2 6-10 19 Cleveland Browns -0.3 7-9 20 Atlanta Falcons -0.4 6-10 21 San Diego Chargers -0.5 9-7 22 Minnesota Vikings -0.7 7-9 23 Arizona Cardinals -0.9 11-5 24 New Orleans Saints -1.5 7-9 25 Carolina Panthers -2.1 7-8-1 26 Washington Redskins -3.4 4-12 27 New York Jets -3.9 4-12 28 Tampa Bay Buccaneers -4.6 2-14 29 Jacksonville Jaguars -5.3 3-13 30 Chicago Bears -5.3 5-11 31 Tennessee Titans -5.4 2-14 32 Oakland Raiders -7.3 3-13

A few teams stand out for having Game Scripts that are inconsistent with their records. The leader there is probably Arizona, which isn’t much of a surprise. The Cardinals were 23rd in Game Script, and as Bill Barnwell wrote, the team has a numbers problem. The Lions also fit that bill: Detroit went 11-5, courtesy of a 6-1 record in one-score games. Detroit’s Game Script is more in line with the fact that the Lions were 5-4 in all other games, and given how much of the Lions success was due to the team’s defense, there are reasons to wonder how good Detroit will be in 2015. But more on that next week.

Anyway, that’s just background info. The main use of Game Scripts is to adjust pass/run ratios based on how a game has unfolded. We know that teams with the lead are more likely to run, and teams that are trailing are more likely to pass. As a result, we need to adjust the raw pass ratio of a team for their Game Script. Let’s do that, using the Packers as an example.

Green Bay ranked 21st in pass attempts, including sacks but excluding spikes. The Packers also ranked 14th in rushing attempts (excluding kneels). So Green Bay appears to be run-heavy, but obviously the team was usually playing with the lead. The goal is to neutralize the effect of the scoreboard to get a sense of which teams are truly pass-happy (or run-happy).

Here’s how we do that.

1) The standard deviation of the Game Script averages for the 32 teams in 2014 was 3.27. The average, by definition, was 0.00. So the Packers, with a Game Script of 6.9, were 2.10 standard deviations above average.

2) The average pass ratio (defined as pass plays divided by total plays, excluding kneels and spikes) of the 32 teams in 2014 was 58.85%. The standard deviation of these Pass Ratios was 4.66%. Since the Packers passed on 57.70% of plays, that means the team was 0.25 standard deviations below average in terms of being pass-happy.

3) The next step is to add the results in steps one and two. Here, adding 2.10 and -0.25 tells us that the Packers had a Pass Identity that was 1.86 standard deviations above-average. To convert that number into a more reader-friendly index number, we multiply it by 15 and add it to 100. That results in Green Bay having a Pass Identity score of 127.9, making them the 2nd most pass-happy team in the NFL.

So yeah, the Packers didn’t pass very often in general, but after adjusting for Game Script, only the Colts were more pass-happy. Here’s how to read the Indianapolis line. The Colts had an average Game Script of +3.1, which was 0.96 standard deviations above average. Indianapolis had a Pass Ratio of 63.48%, which was 0.99 standard deviations above average. Add those two numbers together, multiply by 15, and add 100, and you get a Pass Identity of 129.3.

Rk Team Game Script StDev GS Pass Ratio StDev PR Pass Identity 1 IND 3.1 0.96 63.48% 0.99 129.3 2 GNB 6.9 2.10 57.7% -0.25 127.9 3 NWE 4.6 1.39 60.36% 0.32 125.7 4 DEN 4.7 1.42 59.73% 0.19 124.2 5 MIA 1.0 0.29 62.44% 0.77 116.0 6 DET 0.4 0.11 63.15% 0.92 115.5 7 ATL -0.4 -0.12 64.13% 1.13 115.2 8 PHI 3.0 0.90 58.79% -0.01 113.3 9 PIT 1.2 0.36 60.98% 0.46 112.2 10 BUF 1.0 0.32 61.07% 0.48 111.9 11 NOR -1.5 -0.47 63.24% 0.94 107.2 12 STL 1.1 0.35 59.20% 0.07 106.3 13 SDG -0.5 -0.16 61.24% 0.51 105.3 14 BAL 2.6 0.79 56.53% -0.50 104.3 15 ARI -0.9 -0.26 60.94% 0.45 102.8 16 NYG 0.2 0.05 59.05% 0.04 101.4 17 KAN 1.3 0.41 56.81% -0.44 99.6 18 CHI -5.3 -1.62 65.52% 1.43 97.2 19 MIN -0.7 -0.21 58.34% -0.11 95.3 20 JAX -5.3 -1.62 63.72% 1.05 91.4 21 OAK -7.3 -2.22 66.23% 1.58 90.5 22 WAS -3.4 -1.03 60.50% 0.35 89.9 23 TAM -4.6 -1.40 62.15% 0.71 89.6 24 DAL 3.2 0.99 50.70% -1.75 88.6 25 SFO 0.8 0.24 54.06% -1.03 88.1 26 CIN 1.7 0.51 52.34% -1.40 86.6 27 TEN -5.4 -1.66 61.95% 0.67 85.1 28 SEA 3.0 0.90 49.40% -2.03 83.1 29 CAR -2.1 -0.63 55.67% -0.68 80.3 30 CLE -0.3 -0.09 53.04% -1.25 80.0 31 HOU 2.0 0.60 48.75% -2.17 76.5 32 NYJ -3.9 -1.2 51.97% -1.48 59.9

Given the fact that Andrew Luck was the quarterback and Trent Richardson was the running back, it makes a lot of sense for the Colts to have been the most pass-happy team in the NFL last year. Indianapolis ranked 5th in raw Pass Ratio, the only team with a positive Game Script average in the top five. That’s a sign of how committed the organization is to putting the ball in Luck’s hands, which again, makes a lot of sense.

The Packers line is kind of interesting. To regular NFL fans, it might not be very surprising to see Green Bay as the 2nd most pass-happy team in the NFL. Your average NFL fan might say something like “duh! Rodgers was the MVP, and he has Nelson and Cobb, of course the Packers pass a ton.” And that’s a feature, not a bug, of this Game Script system. NFL fans focused on statistics might have known that Green Bay actually had a below-average pass/run ratio, but that’s the beauty of using Game Scripts to determine Pass Identity.

You probably aren’t too surprised to see the Patriots and Broncos 3rd and 4th in Pass Identity. And after the two teams led by historic quarterbacks, albeit with a big gap, comes the Dolphins. As I alluded to on Friday, it was weird that Miami was so effective at running in 2014 but so uninterested in doing so.

The Raiders, behind rookie Derek Carr, finished 1st in Pass Ratio last year. The Raiders passed on nearly two-thirds of all plays, but they still have a below-average Pass Identity. Because while the team was 1.58 standard deviations above average in Pass Ratio, Oakland was 2.22 standard deviations below average in Game Script. There were five games where the Raiders had a Game Script of -2.0 or better, including all three wins. In two of those games, Oakland was really run-heavy, in wins against the 49ers and Bills. In the other three, Oakland still finished more slanted towards league average than you’d expect. The Raiders may have ranked last in rushing attempts and in the top 5 in pass attempts, but that was a function of Game Script, not design.

For the second year in a row, the Jets were your most run-happy team. The Jets finished with nearly identical numbers in 2014 as they did in 2013, but actually had a slightly worse Game Script and a slightly lower Pass Ratio. That’s going to lead to an even lower Pass Identity score, and the Jets drop from 64.9 to 59.9. Which is insane, especially after adding Eric Decker. This year, I have little reason to think Buffalo won’t now occupy that 32nd spot, as Rex Ryan is surely going to bring his brand of football to Western New York. The Jets quarterback situation remains a disaster, but with Brandon Marshall and Chan Gailey in town, I don’t think New York will rank 32nd for a third straight year (if only, perhaps, because of Buffalo).

The ideas behind Game Scripts and Pass Identity are not to surprise you, but rather to quantify what we all feel. To that end, I doubt many of you are surprised to see Houston, Cleveland, Carolina, and Seattle all in the bottom five in Pass Identity (or, if you prefer, top 5 in Rush Identity). What might be a little surprising is seeing that Houston only finished a hair behind the Seahawks in Game Script last year. This is a good time to remind you that Game Scripts numbers are not adjusted for Strength of Schedule, which would surely have widened the Seattle/Houston gap. But through 3 quarters of play, the Seahawks only had a points differential that was 2 points per game greater than Houston’s, so I guess these numbers make sense.

What stands out to you?