SITE NEWS: We are moving all of our site and company news into a single blog for Sports-Reference.com. We'll tag all PFR content, so you can quickly and easily find the content you want.

Also, our existing PFR blog rss feed will be redirected to the new site's feed.

Pro-Football-Reference.com » Sports Reference

For more from Chase and Jason, check out their work at Football Perspective and The Big Lead.

If Aikman Were Romo

Posted by Neil Paine on September 25, 2009

This is a goofy idea for a post, but here goes...

A few years ago, in order to write this well-intentioned but flawed monstrosity, I replicated what Football Outsiders called "translated" stats, a process which takes a player's stat line from one league environment and tries to determine what it would have looked like in another one. How did it work? I'll quote my own explanation from back in the day:

"How to translate: Take the raw stats. Calculate the completions/game, pass attempts/game, passing yards/game, TD passes/game, interceptions/game, rushing attempts/game, rushing yards/game, and rushing TD/game for the season in question. For the 2006 NFL, they went like this:

GP	LgCmp/G	LgAtt/G	LgPYds/G LgPTD/G LgInt/G LgRush/G LgRYds/G LgRTD/G
---------------------------------------------------------------------------
16	19.14	32.01	219.29	 1.27	 1.02	 28.22	  117.31   0.83

Now, divide the player total in each category (completions, passing yds, etc.) by the appropriate league numbers, and multiply by the 2006 numbers. Then adjust for the length of schedule, extrapolating the raw totals to a 16-game season. Like magic, your new totals will be normalized, able to go up against any other season without fear of cross-era distortions.

Let's take a look at an example... In 1966, Len Dawson of the Kansas City Chiefs put up this stat line en route to an AFL title and a spot in the very first Super Bowl:

                 +---------------------------------------+-----------------+
                 |              Passing                  |     Rushing     |
+----------+-----+---------------------------------------+-----------------+
| Year  TM |   G |  Comp   Att   PCT    YD   Y/A  TD INT |  Att  Yards  TD |
+----------+-----+---------------------------------------+-----------------+
| 1966 kan |  14 |   159   284  56.0  2527   8.9  26  10 |    24   167   0 |
+----------+-----+---------------------------------------+-----------------+

The environment of the 1966 AFL looked like this:

GP	LgCmp/G	LgAtt/G	LgPYds/G LgPTD/G LgInt/G LgRush/G LgRYds/G LgRTD/G
-----------------------------------------------------------------------------
14	14.62	31.60	215.30	 1.58	 1.72	 28.95	  116.13   0.90

So, after applying our normalization technique to Dawson's raw stats, this is the equivalent performance in the 2006 NFL:

                 +---------------------------------------+-----------------+
                 |              Passing                  |     Rushing     |
+----------+-----+---------------------------------------+-----------------+
| Year  TM |   G |  Comp   Att   PCT    YD   Y/A  TD INT |  Att  Yards  TD |
+----------+-----+---------------------------------------+-----------------+
| 2006 kan |  16 |   238   329  72.3  2942   8.9  24   7 |    27   193   0 |
+----------+-----+---------------------------------------+-----------------+

Repeating this procedure for every player-season in the NFL since 1950, we now have a database of stats that can be compared with each other to determine the best modern players at each position."

Simple? Sure. Flawed? Absolutely. But it's still kind of fun, and the results generally make sense. Now, if you really wanted to spice it up, you could translate using standard deviations above/below the mean (similar to what we do with our advanced passing metrics), but for these purposes I think the simple route is the way to go. Anyway, the result is a stat line that effectively places the player in a new context, where his numbers are perhaps easier to understand than had they been left in their raw form.

Playing around with this method is basically the point here, but I also thought it would interesting to see how the two most recent Dallas Cowboys superstar QBs (Troy Aikman and Tony Romo) stack up across eras, since A) Romo is somewhat surprisingly very high on the all-time passing rate lists, B) Aikman has stats notoriously out of step with his reputation as an all-time great, and C) Aikman (among other Cowboy legends) criticized Romo's play after last year's brutal 44-6 season-ending loss to the Philadelphia Eagles.

Aikman played in an era with less leaguewide passing success than Romo has enjoyed, he threw the ball less (especially in the red zone) because Dallas had Emmitt Smith to carry the rushing load, and he has a number of bad (non-prime) seasons that drag down his career rates, while Romo's career essentially consists of nothing but prime seasons (ages 26-29). So what if we took Aikman's stats from ages 26-29, translated them from the 1992-1995 environment to 2006-2009, and prorated everything to Romo's attempts per game? How would Aikman's numbers look compared to those of Romo? Would he be in a better position to criticize a guy who's 3rd on the all-time career passer rating list?

Year Team G Comp Att Cmp% pYds Y/A pTD INT Rate Rush rYds rTD
2004 DAL 6 0 0 0.0% 0 0.0 0 0 0.0 0 0 0
2005 DAL 16 0 0 0.0% 0 0.0 0 0 0.0 0 0 0
2006 DAL 16 223 337 66.2% 2504 7.4 17 8 95.0 34 100 1
2007 DAL 14 334 455 73.3% 3717 8.2 20 7 105.4 27 111 0
2008 DAL 13 305 450 67.8% 3433 7.6 17 13 91.1 28 65 1
2009 DAL 2 38 56 68.3% 442 7.9 2 1 98.3 2 3 0
Career 67 900 1298 69.4% 10096 7.8 55 28 97.5 91 279 2

As it turns out, yes. According to the translated stats, if Aikman had been afforded Romo's opportunity to play from 2006-09, throw the ball as much as Romo, and limit his career to just prime seasons, through Week 2 of the 2009 season he would: rank first all-time in career passer rating, first all-time in completion %, be tied for 8th all-time (4 spots behind Romo) in yards per attempt, rank 5th all-time in lowest interception %, and be 3rd all-time in career adjusted yards per attempt. Remember, Romo's real-life career looks like this:

Year Team G Comp Att Cmp% pYds Y/A pTD INT Rate Rush rYds rTD
2004 DAL 6 0 0 0.0% 0 0.0 0 0 0.0 0 0 0
2005 DAL 16 0 0 0.0% 0 0.0 0 0 0.0 2 -2 0
2006 DAL 16 220 337 65.3% 2903 8.6 19 13 95.1 34 102 0
2007 DAL 16 335 520 64.4% 4211 8.1 36 19 97.4 31 129 2
2008 DAL 13 276 450 61.3% 3448 7.7 26 14 91.4 28 41 0
2009 DAL 2 29 56 51.8% 480 8.6 4 3 82.4 2 5 1
Career 69 860 1363 63.1% 11042 8.1 85 49 94.2 97 275 3

So, basically, erasing the contextual advantages Romo has over Aikman was enough to boost Aikman from a rather pedestrian career 81.6 rating to a 97.5  mark-- and this isn't even taking into account the postseason, where Aikman's career numbers blow Romo's away.

Am I saying that Romo isn't a good QB? No, of course not. But I am saying that he has had a number of advantages in his career that allow him post such impressive stats. When people look at his numbers and compare them to players from the past without regard to changing league passing conditions, they are ignoring the built-in advantages that passers like Romo have. Aikman is just one example of a player whose stats receive a big boost from "the Romo treatment" -- a player like Len Dawson would post even more ridiculous numbers when translated to the modern game.

So while this is a somewhat silly, naive method, it shows that Aikman is more than justified in demanding more from his successor as the Cowboys' superstar QB. After all, giving him Romo's situation is enough to tack 15.9 points of passer rating onto Aikman's career mark, which was roughly the difference between Philip Rivers and Matt Cassel last season.

This entry was posted on Friday, September 25th, 2009 at 1:02 am and is filed under Statgeekery. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed.