Diaries

This is a follow up to this post. If you haven't yet, read that first.

So quite a bit of discussion has opened up in the original post about the Efficiency Rating only taking into account the passing efficiency, and in today's College Football world, quarterbacks are much, much more than that.

In this post I'll take a closer look at the current efficiency rating and how it turned out last year in terms of ranking the quarterbacks, as well as taking a stab at my own Quarterback Efficiency Rating, which will hopefully take into account the broader, tangible aspects of a quarterback's game.

Last Season's Results

Top Ten in Passing Efficiency - 2008

Rank	Player, School	YR	PER	QER	Rank*
1	Sam Bradford, Oklahoma	SO	180.84	10.02	1
2	David Johnson, Tulsa	SR	178.69	8.9	2
3	Colt McCoy, Texas	JR	173.75	8.07	6
4	Tim Tebow, Florida	JR	172.37	8.23	5
5	Zac Robinson, Oklahoma St.	JR	166.84	7.43	9
6	Mark Sanchez, Southern California	JR	164.64	8.29	4
7	Chase Clement, Rice	SR	163.92	8.31	3
8	Graham Harrell, Texas Tech	SR	160.04	7.97	7
9	Case Keenum, Houston	SO	159.91	7.96	8
10	Chase Daniel, Missouri	SR	159.44	7.11	10

*Rank is only out of these ten players
(For comparison's sake, Pat White's QER was a 6.3)

Most of the names on the list are pretty obvious ones. The who's who of College Football Quarterbacks last year. Bradford, McCoy, Tebow, Robinson, Sanchez, Harrell, and Daniel all had phenomenal seasons and were in the spotlight of College Football because of it.

Johnson, Clement, and (to an extent) Keenum, however, weren't mentioned too much. They don't play at high-profile programs, and don't play against Grade-A competition, but you can't make an argument that they had great seasons. is David Johnson a better quarterback than McCoy, Tebow, and Sanchez? Almost certainly not. He is a good passing quarterback, however, and his rating shows that.

Key Players Not in Passing Efficiency Top 10

26

Pat White, West Virginia

142.35

39

Michael Desormeaux, La.-Lafayette

135.01

75

Julian Edelman, Kent St.

118.83

Maybe a bit of a stretch to call White, Desormeaux and Edelman "Key Players", but there's a method to my madness. Edelman, Desormeaux, and White had the 11th, 32nd, and 52nd highest rushing yards per game, respectively.

Obviously this didn't suddenly make them some of the best quarterbacks in the nation, as none of the three were invited to the Heisman Ceremony, but it's just an example of the aspects of the game that Passing Efficiency doesn't take into account.

Quarterback Efficiency Rating?

So if Passing Efficiency isn't a great way to evaluate the overall quality of a quarterback, what other ways are there?

Well.. there aren't too many.

So I took a stab at my own Quarterback Efficiency Rating. It has its flaws but it's a more comprehensive, all-encompassing look at what a quarterback does and evaluates them based on a multitude of other statistics, beyond just passing.

Quarterback Efficiency Rating (QER)

      (Completions) + (Passing Yards x 0.5) + (Passing Touchdowns x 50) +
   (Interceptions x -25) + (Rushing Yards x 0.5) + (Rushing Touchdowns x 50)
__________________________________________________________________
                            (Rushing Attempts) + (Passing Attempts)


In this formula, not only is the best possible rating just over 100 (no one would ever realistically reach over 100, or even close to 100) for an easier analysis of the rating, but a pocket passer:

26/32, 280yds, 3 TDs (QB Rating: 9.875)

Has a comparable rating to a dual threat or even a running quarterback:

14/21, 150yds, 1 TD, 10att, 96yds, 2 TDs (QB Rating: 9.26)

There's no arguing that, in this example, the pocket passer had a better game, but at least with the QER they were about on the same level, whereas the Passing Efficiency Rating would have given the pocket passer a 185.7 rating, and the dual threat quarterback a 142.4.

Again, not perfect. But neither is the Passing Efficiency Rating. It might not make it into NCAA Recordkeeping, but it might help us in the bloggosphere rate quarterbacks on more than just their passing ability.
________________

That's all for this installment of Behind the Numbers, please feel free to let me know if you have any constructive advice for the QER. Thanks for reading!

The new meme across college football analysts is the disappointing performances by Terrelle Pryor. Stewart Mandel of Sports Illustrated even went as far to ask if he chose the wrong school.There’s been blame put on Terrelle, Tressel, and I’m sure someone will find a way to blame Rich Rodriguez for Pryor’s woes.

It’s only two weeks into his sophomore campaign, and there has already been talk of Pryor being a bust. This past Saturday, Pryor and his Ohio State team lost in a close game to a USC team that’s ranked number three in the nation. Pryor has made poor decisions on the field, and even recently one off the field, HOWEVA, there are a few questions that need to be answered when addressing Terrelle Pryor. The first question that came to mind was if Terrelle Pryor was a victim of the “OMG star rankings,” and the new media hype of scouting services.

Pryor was ranked as the number one player in the country in 2008, and a five star recruit by Rivals.com. The attention he got throughout the recruiting process seemed like he was getting drafted right out of high school. He was dubbed the savior, the next coming of Vince Young, and even added to the media attention by holding multiple press conferences to announce that he would be announcing a decision, and then eventually announce the decision. The question is; was the hype warranted? Was Terrelle Pryor that much ahead of the rest of the field, and as college ready as the professionals said he was? I took the stats compiled from Pryor’s junior  year of high school, and compared them to Devin Gardner,  2010 QB prospect committed to Michigan.  For argument’s sake, I’ll leave their names out of their stats. Gardner hasn’t yet completed his senior year, and Pryor was dubbed the number one player in the nation after his junior year, anyway.

Rushing Att.	Yds.	Avg.	TD	Pass Att.	PC	Pct.	Yds.	TD	Int.
115	1,401	12.0	22	170	98	58.0	1,886	26	7
Rushing Att.	Yds.	Avg.	TD	Pass Att.	PC	Pct	Yds.	TD	Int.
192	1,676	8.7	29	163	92	56.4	1,732	15	<?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" />-

 

Devin Gardner owns the first set of stats, and the second group belongs to Terrelle Pryor. As you can see, Pryor had approximately 200 more rushing yards, and 7 more rushing TD’s. Gardner, however, has a better passing percentage, more yards, and 11 more touchdown passes than Pryor. The two are also close in height, with Pryor having an inch or two on Gardner, while Terrelle is around 40 pounds heavier than Devin.

Devin Gardner is ranked as a 4 star prospect, and the 53^rd best prospect in the country. So, it would seem by comparing stats and stature that 40 pounds is what separates Gardner from the 5^th star, and the paparazzi following.

I’m not defending Pryor, or lobbying for Gardner. I’m merely comparing the two, and questioning the reason for the hype surrounding Terrelle Pryor.

It’s been said before that the recruiting services base a lot of their opinion on NFL potential. While the NFL has adopted the wildcat and more athletic quarterbacks, the biggest emphasis is still on passing ability. Again, based off of these stats, Pryor is not light years ahead of his peers.

It seems like Pryor has fell victim (I hate to call him a victim of anything) of the new media hype machine. They created the monster, and after building his castle, seem to be deconstructing it one poor decision at a time.

(The next stat that needs to be analyzed is how Pryor compares to past number 1 rated quarterbacks in their freshman and sophomore seasons. I’ll have another post on this later.)

I find it pretty absurd that Tressel now has an angry mob on his hands for losing to USC at home, by 3, on a last-second drive.  You may remember a certain other coach did exactly this in 2005 and was promptly rewarded with a 10-year contract.  But the fallout from this latest loss raises a larger point: what does it mean if you are not able beat USC?

Answer: it means you are a college football team other than USC.

Let's put one particular stat to rest, or at least in perspective--any team or conference's recent record against USC.

USC OOC - 2003-2009
Here is how USC has fared against out-of-conference opponents in recent years.

2003 (5-0)
Auburn - BYU - Hawaii - Notre Dame - Michigan

2004 (5-0)
V. Tech - Colorado St. - BYU - Notre Dame - Oklahoma

2005 (4-1)
Hawaii - Arkansas - Notre Dame - Fresno State
--LOSS Texas

2006 (4-0)
Arkansas - Nebraska - Notre Dame - Michigan

2007 (4-0)
Idaho - Nebraska - Notre Dame - Illinois

2008 (4-0)
Virginia - Ohio State - Notre Dame - Penn State

2009 (2-0)
San Jose State - Ohio State

Overall record: 28-1

Conference records:
Big Ten: 0-6
Ind.: 0-6
WAC: 0-5
Big 12: 1-3
SEC: 0-3
MWC: 0-3
ACC: 0-2

Lessons to be drawn from a 3.6% winning percentage (not many)
The Big Ten (and ND) is the worst.  The reason?  We have played them more.  If some other team or conference was taking every other game--or even one in three--from USC, then maybe I would do some soul searching upon losing to them.  But other than the game of Vince Young's life, they have not lost to any team from another conference since 2002.

As much as Michigan fans may enjoy hearing some loud, overly-decisive talking head blather about how USC owns Ohio State or Notre Dame, remember that the same is true for us.  And further, for everyone.  So I think we should hold off on declaring OSU less-than-stellar, Pryor a bust, etc.  The pundits, as always, are over-punditing.  Losing to USC does not mean OSU is not very good, or that the Big 10 is weak.  It means they played USC during Pete Carrol's reign of NCAA terror.

This is partially a response to Black Heart Gold Pants, but I have enough SB Nation blogs already and don't feel like signing up for another rival's, nor waiting the requisite number of days to post, so if someone with a BHGP account wants to give him a heads up...

Also, warning: it's long. For those who like their baseball games in ESPN highlights, and their Melville in Cliff Notes, I put bullet points under each heading.

I wanted to generate a discussion on different polling strategies, and come to a consensus on what we expect from NCAA polls.

First, assumptions:

1. Polls are not and will never be exact, even at the end of the season. There is no "right answer." Comparing over 100 teams with hideously unbalanced schedules with absolute accuracy is nigh impossible.
2. We want polls anyway.
3. A higher-ranked team is considered better than one ranked below it.
4. Even if we produced that theoretical "perfect poll" there would be plenty of people who disagree on it.
5. To a degree, there is an unstated general consensus that some teams are better than others, i.e. the masses can agree on certain things, like Florida is in the Top 3, and Michigan isn't.
6. We will know more as the season progresses.
7. The perfect poll would be the exact same in the preseason and at the end of the season, and still be entirely justifiable.
8. Consensus is the ultimate goal -- corollary: fewer polls is better.

Resume Voting

• Best At: Being a ranking on this year's performance that actually has its basis in this year's performance
  
• Worst At: Providing a non-laughable poll before November
• Primary Gripe: Small sample = useless

I have respect for resume voters because they have the same standard throughout the season. The downside is their polls take awhile to come together. Resumes grow more demonstrative only after there's experience on there. If I showed you the resumes of two 16-year-olds and you had to pick which one will end up making the most money by the time they are 50, we would be clueless.

At least it's a metric that makes some sense. But the wild variance defeats the purpose of having these polls in the first place: it's not to generate discussion, it's to provide a frame of reference for assessing the difficulty of beating one team or another. If Cincy loses next week, nobody's going to believe it if you say "oh wow, they beat the No. 1 team in the country."

It also, when it's used in concert with other voting metrics, has the unintended effect of compounding things like an overrated conference. A great example is the Big East a few years ago, when South Florida, Rutgers, Louisville and West Virginia took advantage of some early season flukes and an incredibly soft middle of the schedule to leap-frog each other to the top of the polls. This was the primary culprit in the short-lived appearance of USF at No. 2 in the BCS poll -- any ranking that has South Florida second in the nation in anything beside STDs is a travesty.

The upside of resume voting is that every week it gets more and more feasible. The BCS poll has been, in many of its incarnations, essentially a resume poll, which had the good sense to begin releasing data late in the season. Ultimately, resume voting is a justifiable system so long as it remains pure, but isn't very useful early in the year at providing a poll's primary objective: to provide a plausible ranking of NCAA's best teams.

Suggestion for improvement: Stay out of it until near the end. I want resume to determine who plays for the National Championship, but I'd rather not half-finished resumes affecting the mid-season polls. Other words: I'm with you if you wanna put '03 LSU and '03 Oklahoma in the Championship, but let's call '03 USC No. 1 right up until the end of the Rose Bowl, just so we're clear that Michigan is facing the hardest team in the country. Make sense?

Roster Voting

• Best At: Pre-Season Poll that passes credulity test, Mid-season difficulty rankings
  
• Worst At: End-of-Season Poll that passes credulity test
• Primary Gripe: Not enough data, plays down this year's performance, which, like, isn't that what the poll is about?

Early in the season, this is most polls, including the AP and Coaches. Since no games have been played, it's a vote based primarily on how good the team was last year, with plusses for returning players, minuses for returning players.

This does a much better job of placating the masses in the pre-season. As the season progresses, however, as opposed to resume voting, this metric tends to disappear almost entirely, which I think is a major disservice to these polls.

Essentially, they fall victim early on to resume voting, rather than stick to their guns. This means big drops for teams as they lose. The downside, of course, is that if there's a consensus No. 1 team that loses its only two games early in the year, you'll see a major shift in that team's ranking -- big drop, steady incline, etc. This hurts the usefulness of the poll, since it changes its base metric mid-way through, essentially calling out its own initial justification.

A roster-based poll shouldn't be oblivious to the unfolding season, but it also shouldn't abandon its basis. Updates would be based on roster shifts, such as Oregon losing Dixon, Pat White losing a finger, or Michigan discovering one of its 4-star freshman recruits is already a more-than-serviceable and perhaps awesome college QB. This does not seem to generate much shift, but revelations abound in college football -- if someone pays close attention, we could end up with a fairly decent poll insofar as showing how much of a challenge each team should present.

Like resume polling, a roster poll is justifiable -- last year's performance, injuries, player statistics: these are all available metrics.

However, as the year progresses, such a poll would require A TON of input to remain accurate. Barring a UFR for every team, a roster poll seems unfeasible.

I can't think of a poll that keeps this metric throughout the season. I'd like to see one in the blog poll. It would wrack up a lot of Mr. Stubborns, and a few other outliers as other voters respond to season upsets, etc. And more importantly, while it's very useful at showing which team is the hardest to beat talent-wise early in the year, the more the season progresses, the more you'll have major incongruities, like a highly talented 4-loss team in the Top 5 while a lucky, scrappy, undefeated mid-Major team lingers at the bottom of the Top 25.

After about 8 weeks, a roster-voted poll would get lapped by the resume voters in placating the general populace, and take a lot of flack along the way. And at the end of the year, it would be totally useless.

Suggestion for improvement: This needs statistics, or it's as bupkis as pre-season polls. One day (I'm already looking into it) there will be UFR-like statistics kept for every player on every team. This will facilitate player and position rankings. And coaching ratings, too. And team rankings (offensive/defensive efficiency, etc.) The more info compiled and thrown in, the more this type of polling becomes feasible. Never going to be useful for who belongs in a championship, but I, for one, would find such a stat very interesting when having one team go up against another.

Predictive Voting

• Best At: Pre-Season Polling
• Worst At: BCS Selection, Precision
• Primary Gripe: Factors are compounded

This is a straight-up attempt to get the final poll right in Week 1. A lot of AP voters fall into this trap, as evidenced by the justification they give for their preseason ballots.

e.g.

"I ranked Ohio State 1st because the lolBigTen is so weak the Buckeyes can knock off a freshman-quarterbacked USC, then tapdance to the BCS championship again."

In this example, does this hypothetical assclown voter call Ohio State the best team in the country? No. But isn't the best team in the country supposed to be ranked No. 1? Umm....yes?

Predictive voting does have a strategy for keeping itself in line, which makes it somewhat useful, if still inaccurate, for mid-season and late-season polling. Essentially, teams are not down-rated at all when they lose something they were expected to lose in the fashion in which they were expected to lose it. They play against their expectations.

Predictive voting is often used in concert with another metric, most often as a correction to Roster Voting ballots that generally have mid-Majors and giants in weak BCS conferences underrated. It generally has a lot of opportunity to look stupid as the season progresses, since the swings after unexpected wins and losses, in practice, are never truly in line with expectations. It also doesn't account for surprises, like Notre Dame losing to Michigan (not expected) but demonstrating that its offense is for real (i.e. they're not worthy of a major fall).

Predictive voting is, however, not a bad way, conceptually, to achieve the goal of a preseason ballot that bears some resemblance to the end of the season. Of course, it's hideous at providing an accurate ranking of teams' actual ability. But it does a fair job of passing the eyeball test, and remains a well-used tool for college polling.

Suggestion for improvement: Accuracy is the problem, because all changes are totally subjective. So use computers. Run 10,000 simulations of every game left in the season. This becomes the base prediction for each team, and should provide a solid framework for an initial season. Derivation from expectation down-ranks them or up-ranks them as the season progresses. Easier way: use the spread -- gamblers know what they're doing.

Hype Voting

• Best At: Wooooo!!! Tate Forcier is a god!!! I'm gonna go online now and see if the national consensus agrees! Woooo!!! They agree! We Rock!!!!
• Worst At: NCAA Polling
• Primary Gripe: Loose grip on reality

OMG UNIVERSITY OF COLLEGE DEFEATED COLLEGE UNIVERSITY BY THREE TOUCHDOWNS -- BUMP BUMP BUMP, DROP DROP DROP.

Accordingly.

This metric is among the least justifiable of the non-biased metrics, but is also rampant. Except it's also the easiest way to create a poll that readers generally agree with mid-season. It's basically rearranging teams each week based on carrots like "so-and-so deserves a 10-slot bump" or "Team X defeated Team Y so team X should go above Team Y."

It passes the eyeball test, which is the whole point of hype voting. But it also generates a goodly chunk of the eyeball rolling from other pollsters who want something more concrete behind their polls.

Suggestion for improvement: This basically comes down to faking it to get the results you wanted when solid metrics fail. I'm of a mind to either improve metrics or believe them before turning to pre-conceived notions out of convenience.

Bias Voting

• Best At: No. 3 Notre Dame @ No. 1 USC. TONIGHT on NBC!!!
  
• Worst At: Honesty
• Primary Gripe: Subversion of polling for selfish gain

This is included because it happens. It's justifiable because it basically follows the suppositions of the masses. Bias serves a purpose beyond actual strength of teams, be it a coach who wants his opponents overrated to get into a BCS bowl game, or a rival underrated to keep him out, etc. It also includes sports/journalists/networks well-served by rating a major national program just over sliced bread. And bloggers who want some recognition for their beloved team, and the conference it plays in, etc.

Brian uses the Coulter/Kos Award to keep the bloggers honest about their own teams, but I don't know how much he's watching what they do to their rivals and opponents. Just because you wear your bias on your sleeve, that doesn't mean you're immune from it (e.g. Coulter, Kos).

Suggestion for improvement: Not that Brian hasn't said it 1,000 times, but this bears repetition upon repetition: MAKE ALL VOTES PUBLIC AND HOLD VOTERS ACCOUNTABLE.

What's Best?

Obviously, aside from a few resume polls, most polls are a combination of many of these metrics, all of which have major holes in them that strain credulity, over/under-reward scheduling and biases and notoriety, etc. At any given point during the season, and depending on the function a poll is meant to serve at that point in the season, there are better metrics than others.

So let's go back to our suppositions, and pick out what it is we want from a poll at any given time:

• Preseason: Closest as possible to the final poll, plus something that passes the eye test, i.e. readers can generally agree with it. For this, I suggest a combination of Roster and Predictive polling. Both are in dire need of better statistics, but the stats are out there already, and currently being employed to good effect by oddsmakers, who have a stake in getting it right (although they move their bets based on hype). We know who's on what team, and who will most likely be playing X amount of time at each position. We have a record of play for every year prior for every player on every team. We know the recruiting value of incoming freshmen, and we know the base value of freshmen to keep the recruiting value in perspective. As the season progresses, we have more records of play, which should make us more accurate. Transcribing this to a statistical value is not impossible, just very time-consuming.
• Early Season: Still, I would stick to exclusively Roster and Predictive polls, for reasons shown above. I think one consensus poll would be best for this period.
• Week 8 to Bowls: Start publishing a second poll, sort of like the BCS numbers, but not really, because it would be entirely Resume based (note: would also be used to determine playoff spots). This poll would show teams ranked by their resume If they were to win every game left on their schedule. It seems counter-intuitive, since, yeah, a lot of them play each other. But actually, that keeps it cleaner -- those that play each other get credit for doing so based on where each is at before the inevitable down-ranking of each other.*
• End of Season: Publish a final Resume-based poll.

* This system is kind of radical. No, I didn't say re-publish this poll. The idea is that by Week 8, we have a pecking order. For you to get into a 2-team (i.e. BCS) or 4-team, 8-team, or 16-team playoff, the teams ahead of you would have to lose, maybe twice if you're far enough down. This would radically change the college football season: you'd spend the first half trying to earn a ranking, and the second half would basically be a playoff (it would be a playoff in that fans would know the probable outcomes off-hand before each game).

It would be awesome for fans, as major programs try to schedule each other early to build a high resume before Week 8. Then, as injuries deplete rosters and cold sets in, each team is in do-or-die mode every week, or else risk losing their place in line.

Okay, I've said my piece. As with everything else I write, I ask you to please find as many holes in it as you can (except typos, which I plan to go back and fix when time allots).

Brian's poker talk has got a hold on me.  I have one more analogy I need to get out.

Back in the 80's and 90's poker had 3 types of players basically.  The conservative math guys that new statistically what the right play was.  The Doyle Brunson devotees that always applied pressure with aggressive betting and you had donkeys that gave these types of players money.  College football was much the same you had your conservative programs like Michigan, Penn St, Notre Dame and much of the SEC consistently winning . You had the super aggressive teams taking over like Florida St , Miami and Nebraska with aggressive blitzing defenses and high powered offenses.  These cultures clashed in spectacular fashion with merits to both successful styles.  The donkeys like Indiana and Mississippi tried different things and continually got their teeth kicked in because they were not smart nor good.
 
Then the internet age came in with ESPN televising poker and we we're introduced to a new style of poker.  This kid was scoffed at by the top pros with his small ball style of poker with small raises and playing 34 offsuit, he was labeled a donkey by the establishment.  When he had success it was considered luck that could not be sustained.  Eventually Daniel Negrenau won people over and a new style of poker emerged where you play a lot of hands and since it went against the grain of the popular styles it was wildly successful.  This reminds me of a football coach that I like a lot named Rich Rodriguez.  The spread was thought of as a gimmick and now it is wildly accepted.  The thing I like the best is that while Rodriguez and Negreanu are thought of as innovators and wacky they really believe in old school beliefs and values but the fancy dressing throws people off.  Rodriguez offense is founded in being physical and running the ball and you rarely see Negreanu making wild bluffs or calling bad bets that don't have value.

The interesting thing is that now we are past both these stages and now that both styles have been accepted as a credible strategy they are no longer just successful because they are contrarian,  they are now part of the establishment.  To me this age we are in is not about styles, but more about who is the smartest and the toughest and who is willing to adapt.  Now the best offenses are no longer just spreads, or option or passing but blends of styles.  Oklahoma, Florida and hopefully soon Michigan have a multitude of looks that can quickly attack a defenses weakness instead of pounding your style relentlessly hoping to outwill your opponent.  Much like the best poker players are the ones that have adapted to the internet maniacs and have a style that they can adjust to the table or setting they are in.    I have full confidence Rod is one of these poker players that will win for Michigan.  He's not a lunatic like Weis or mathematician like Carr.  I think he is a master play caller much like Holtz in the the 80's or Spurrier in the 90's that can and has already adapted to his teams strengths and other teams weaknesses while not straying from his core beliefs.  Rod's a good poker player and now that he has added Forcier and Robinson he's getting some pocket Aces to play with making it a little bit easier to win with. 

There are a lot of statistics floating around the world of College Football. Some intriguing, some important, some useless, some hilarious. Behind the Numbers is a semi-regular look at just a few of the statistics that you may or may not be aware of, with a little bit of a dissection of each. Enjoy.

UPDATE: Part Two is here. Includes an alrernative to Passing Efficiency.

Today's Stat: Passing Efficiency

(Full NCAA Rankings)
Players of note: Ryan Mallett, Arkansas (1st, 210.25); Jimmy Clausen, ND (3rd, 196.31); Kirk Cousins, MSU (6th, 186.71); Tate Forcier, Michigan (21st, 161.69); Terrelle Pryor, OSU (79th, 116.92)

Why it's important:

It's pretty much the golden standard for measuring the (wait for it) efficiency of a quarterback. It's not flawless by any means, but overall is a pretty good indication of how good a quarterback is. Once there's a good sample size (at least 100 attempts), it's pretty safe to say that a player in the top 20 of the efficiency ratings is a good quarterback, and a player outside the top 50 isn't quite as high-caliber.

Why it's flawed:

Passing Efficiency measures just that -- efficiency. How efficient something or someone is usually boils down to how much of 'x' they can do in 'y' amount of tries. It's no different in the world of college football. The equation for Passing Efficiency in College Football is as follows:

(Completions x 100) + (Yards x 8.4) + (Touchdowns x 330) - (Interceptions x 200)
                                                        Attempts

So while all of that stuff on top is really important, it really boils down to how many passes the quarterback has attempted. For example:

Quarterback A plays basically the whole game and racks up some pretty good numbers, but in the red zone gets bruised up and comes out for a play.

Quarterback B comes in for that one play and throws an eight yard touchdown pass, and is right back on the bench, and remains there for the rest of the game.

Quarterback A's stats: 28/35, 310yds, 3 TDs, 1 INT
Quarterback B's stats: 1/1, 8yds, 1 TD

Go ahead and take a stab at each quarterback's rating. Or just scroll down a bit and look at the actual answers, you cheater.

Quarterback A's Efficiency Rating: 246.2
Quarterback B's Efficiency Rating: 497.2

Quarterback B, the backup who came in for one play, isn't necessarily a better quarterback than Quarterback A.. there's actually a good chance that he's a good deal worse. His efficiency rating, however, is more than twice that of Quarterback A, who had a damn good day throwing the ball. However because that one pass attempt that he did have was a successful one, his Efficiency Rating is about 287 points higher than the current highest rating in Division 1.

Applying this to current statistics:

Ryan Mallett: 17/22, 309yds, 1 TD (210.25)
In the one game he's appeared in so far, Mallett has only attempted 22 passes (remember, the smaller the sample size the more skewed the rating), and completed 17 of them. A 77% completion percentage is second only to Sean Canfield (OSU, NTOSU), who has the 14th highest efficiency rating. He only has the one touchdown and has yet to throw a pick (not as important as you'd think, as you'll see later). Not stellar numbers by any means, but he did pretty well against Missouri State.

Jimmy Clausen: 40/60, 651yds, 7 TDs (196.31)
Not too much to say here, the efficiency rating is pretty well deserved so far. Quite the interesting comparison to Mallett's numbers, however. Clausen's numbers are obviously superior in every way but completion percentage. Clausen is clearly the superior quarterback here, yet because of the small sample size in Mallett's case, he has the higher rating.

Tate Forcier: 36/53, 419yds, 5 TDs, 1 INT (161.69)
Tate's numbers compared to his rating are also pretty interesting. He actually has a higher completion percentage (67.9) than Clausen (66.7), has a respectable touchdown percentage (9.43% of his passes are touchdowns, compared to Clausen's 11.7%), and only has the one interception. However even if we take that interception away (it wasn't even his fault!), Forcier's rating doesn't improve too dramatically. If the pass fell harmlessly to the ground, his rating would be a 165.5, good for 17th. If the pass was completed for a 15 yard gain his rating would be a 169.7, putting him in 16th.

The Takeaway

Quarterback Efficiency Rating is an effective way to rank the overall efficiency of quarterbacks, especially later in the season once there is a decent sample size of attempts to go by. Until then, however, it's a stat that's easily skewed by a few attempts going for big yards and touchdowns. We all know Quarterback A in the example above had a better game than Quarterback B, but the formula for efficiency rating doesn't. Quarterback B did complete 100% of his passes, and 100% of his attempts went for touchdowns.. the thing is there was just the one attempt. Therein lies the flaw.

Just for fun, try to guess which stat line would garner the higher efficiency rating. Answers are at the bottom of the post.

                         Situation 1                                           Situation 2
     A. 25/30, 250yds, 2 TDs, 2 INTs     l     A. 30/40, 300yds, 1 TD
     B. 15/17, 140yds, 1 TD                 l     B. 10/12, 100yds, 2 TDs                  
                                                        Situation 3
                                        A. 20/24, 200yds, 2 TDs, 4 INTs
                                              B. 20/40, 250yds, 5 TDs

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Behind the Numbers will be back soon with another look at a stat from the world of College Football. Any stats you want to be examined a little closer? Or even just a stat you've been interested in for a long time? Let me know in the comments and I'll do my best to get to it in the next few installments of BtN. Thanks for reading!
-CollegeFootball13

Situation 1- A: 162.0 B: 176.8; Situation 2- A: 146.2 B: 208.3;
Situation 3- A: 147.5 B:143.75