Final 2011 Offensive and Defensive Efficiency Scores

With the 2011 regular season in the books, here are the final efficiency scores:

Offense:

2011	All Time	Tm	OSCORE
1	2	Green Bay Packers	53.95
2	10	New Orleans Saints	48.95
3	17	New England Patriots	42.35
4	144	Carolina Panthers	20.45
5	182	San Diego Chargers	17.65
6	198	Detroit Lions	16.40
7	202	Atlanta Falcons	16.25
8	243	San Francisco 49ers	13.90
9	280	New York Giants	12.60
10	348	Dallas Cowboys	9.85
11	365	Houston Texans	9.10
12	490	Minnesota Vikings	3.60
13	503	Baltimore Ravens	3.20
14	626	Philadelphia Eagles	-1.70
15	675	Oakland Raiders	-3.10
15	675	Miami Dolphins	-3.10
17	681	Pittsburgh Steelers	-3.25
18	723	New York Jets	-4.50
19	733	Cincinnati Bengals	-4.85
20	739	Tennessee Titans	-5.25
21	771	Buffalo Bills	-6.10
22	865	Seattle Seahawks	-10.10
23	919	Arizona Cardinals	-12.95
24	993	Chicago Bears	-16.65
25	1012	Denver Broncos	-17.25
26	1035	Washington Redskins	-18.60
27	1096	Cleveland Browns	-22.80
28	1108	Jacksonville Jaguars	-23.50
29	1135	Tampa Bay Buccaneers	-26.40
30	1149	Indianapolis Colts	-27.80
31	1201	Kansas City Chiefs	-37.95
32	1209	St. Louis Rams	-40.70

Defense:

2011	All Time	Tm	DSCORE
1	20	San Francisco 49ers	36.65
2	84	Baltimore Ravens	25.11
3	135	Seattle Seahawks	20.17
4	195	Houston Texans	16.48
5	211	Chicago Bears	15.81
6	270	New York Jets	12.88
7	300	Detroit Lions	11.78
8	314	Pittsburgh Steelers	11.42
9	324	Green Bay Packers	10.70
10	404	Jacksonville Jaguars	7.44
11	446	New England Patriots	5.93
12	465	Atlanta Falcons	5.42
13	514	Tennessee Titans	4.11
14	565	Cincinnati Bengals	2.28
15	575	Miami Dolphins	1.94
16	578	Cleveland Browns	1.88
17	620	Philadelphia Eagles	0.56
18	621	Kansas City Chiefs	0.54
19	637	Dallas Cowboys	0.13
20	644	Arizona Cardinals	-0.08
21	771	New York Giants	-4.42
22	781	Denver Broncos	-4.86
23	915	Washington Redskins	-11.14
24	921	Buffalo Bills	-11.45
25	943	New Orleans Saints	-12.46
26	955	St. Louis Rams	-13.10
27	982	San Diego Chargers	-14.61
28	1019	Oakland Raiders	-16.24
29	1089	Minnesota Vikings	-21.47
30	1110	Indianapolis Colts	-24.07
31	1137	Carolina Panthers	-26.99
32	1190	Tampa Bay Buccaneers	-34.40

Offensive Efficiency Rankings Through Week 16

Offensive Efficiency Rankings Through Week 16

2011	All Time	Tm	OSCORE
1	2	Green Bay Packers	54.25
2	14	New Orleans Saints	45.45
3	21	New England Patriots	40.55
4	123	Carolina Panthers	22.25
5	202	Detroit Lions	16.05
6	233	San Diego Chargers	14.35
7	263	Atlanta Falcons	13.30
8	282	Dallas Cowboys	12.35
9	320	San Francisco 49ers	10.95
10	336	Houston Texans	10.20
11	352	New York Giants	9.75
12	386	Minnesota Vikings	7.95
13	548	Baltimore Ravens	1.40
14	603	Pittsburgh Steelers	-0.55
15	646	Miami Dolphins	-2.15
16	678	New York Jets	-3.15
17	701	Cincinnati Bengals	-3.95
18	724	Oakland Raiders	-4.60
19	733	Philadelphia Eagles	-4.90
20	736	Buffalo Bills	-5.10
21	758	Tennessee Titans	-5.85
22	863	Seattle Seahawks	-10.05
23	919	Denver Broncos	-12.95
23	919	Arizona Cardinals	-12.95
25	943	Chicago Bears	-13.95
26	1012	Washington Redskins	-17.20
27	1075	Cleveland Browns	-20.85
28	1125	Jacksonville Jaguars	-25.50
29	1129	Tampa Bay Buccaneers	-25.70
30	1137	Indianapolis Colts	-26.60
31	1199	Kansas City Chiefs	-36.40
32	1217	St. Louis Rams	-47.05

2011 Efficiency Rankings Through Week 15

With 15 weeks of the NFL season in the books, here are the OSCORE and DSCORE rankings:

2011	All Time	Tm	OSCORE
1	3	Green Bay Packers	52.35
2	14	New Orleans Saints	43.20
3	21	New England Patriots	40.05
4	185	San Diego Chargers	17.05
5	215	Detroit Lions	15.05
6	231	Atlanta Falcons	14.50
7	241	Dallas Cowboys	14.05
8	252	Carolina Panthers	13.65
9	301	Houston Texans	11.70
10	339	San Francisco 49ers	10.15
11	371	New York Giants	8.90
12	524	Baltimore Ravens	2.10
13	533	Minnesota Vikings	1.90
14	565	New York Jets	0.90
15	672	Buffalo Bills	-2.90
16	673	Cincinnati Bengals	-2.95
17	687	Oakland Raiders	-3.55
18	688	Philadelphia Eagles	-3.55
19	700	Pittsburgh Steelers	-3.85
20	702	Miami Dolphins	-3.90
21	771	Tennessee Titans	-6.10
22	840	Seattle Seahawks	-9.05
23	858	Chicago Bears	-9.90
24	865	Denver Broncos	-10.05
25	931	Arizona Cardinals	-13.25
26	1056	Washington Redskins	-19.75
27	1076	Cleveland Browns	-21.05
28	1110	Tampa Bay Buccaneers	-23.65
29	1129	Jacksonville Jaguars	-25.70
30	1138	Indianapolis Colts	-27.00
31	1192	Kansas City Chiefs	-35.25
32	1213	St. Louis Rams	-43.55

2011	All Time	Tm	DSCORE
1	8	San Francisco 49ers	44.34
2	106	Baltimore Ravens	22.88
3	145	Seattle Seahawks	19.38
4	151	Chicago Bears	18.92
5	157	Houston Texans	18.32
6	252	New York Jets	14.02
7	275	Detroit Lions	12.80
8	318	Green Bay Packers	11.18
9	403	Atlanta Falcons	7.46
10	427	Dallas Cowboys	6.64
11	431	Pittsburgh Steelers	6.44
12	446	New England Patriots	5.98
13	453	Tennessee Titans	5.74
14	530	Miami Dolphins	3.56
15	552	Jacksonville Jaguars	2.94
16	589	Cincinnati Bengals	1.56
17	662	Cleveland Browns	-0.76
18	673	Arizona Cardinals	-1.18
19	735	Philadelphia Eagles	-3.18
20	752	Washington Redskins	-3.54
21	814	Denver Broncos	-6.48
22	843	San Diego Chargers	-7.76
23	852	Kansas City Chiefs	-8.18
24	864	St. Louis Rams	-8.52
25	886	New York Giants	-9.74
26	948	Buffalo Bills	-12.66
27	1005	New Orleans Saints	-15.72
28	1024	Oakland Raiders	-16.54
29	1115	Tampa Bay Buccaneers	-25.00
30	1127	Carolina Panthers	-25.98
31	1143	Indianapolis Colts	-27.38
32	1152	Minnesota Vikings	-28.44

2011 Offensive Efficiency Scores

Yesterday, I posted my final Offensice Efficiency (O-SCORE) rankings for 1970-2010 (you can find them here: 1970-2010 Rankings). Here are the 2011 scores, along with their all-time rank:

2011	All Time	Tm	OSCORE
1	3	Green Bay Packers	52.46
2	18	New Orleans Saints	39.56
3	38	New England Patriots	33.02
4	121	Houston Texans	21.73
5	251	Detroit Lions	13.20
6	292	Atlanta Falcons	11.63
7	302	Dallas Cowboys	11.13
8	354	San Francisco 49ers	9.07
9	385	New York Giants	7.69
10	448	Carolina Panthers	5.05
11	451	Minnesota Vikings	4.95
12	457	Pittsburgh Steelers	4.82
13	460	Buffalo Bills	4.78
14	473	Chicago Bears	4.19
15	513	Oakland Raiders	2.80
16	552	Cincinnati Bengals	1.53
17	567	Baltimore Ravens	0.81
18	582	San Diego Chargers	0.52
19	621	Philadelphia Eagles	-1.00
20	665	Miami Dolphins	-2.63
21	731	Tennessee Titans	-4.71
22	814	New York Jets	-7.70
23	894	Denver Broncos	-10.67
24	913	Cleveland Browns	-11.83
25	996	Arizona Cardinals	-15.90
26	1042	Tampa Bay Buccaneers	-17.60
27	1053	Seattle Seahawks	-18.21
28	1105	Washington Redskins	-22.08
29	1145	Jacksonville Jaguars	-26.49
30	1182	Indianapolis Colts	-31.45
31	1193	Kansas City Chiefs	-33.77
32	1209	St. Louis Rams	-37.79

Through 11 weeks, the Packers have the 3rd most efficient offense since the 1970 NFL/AFL merger. They still trail the 2007 Patriots significantly in most variables, so I doubt they will get to #1. It’s possible that they overtake the 1984 Dolphins (52.64) though, given Green Bay’s fairly soft schedule the last 5 weeks.

On the other end of the spectrum, the 2011 Rams have the 13th worst offense since 1970. It’s possible (especially if A.J. Feeley gets more starts) that they drop into the bottom 10 but even a total collapse probably wouldn’t get them in the bottom 3.  St. Louis’ 2009 offense was 5th worst since 1970. The Tampa Bay Buccaneers (1976, 1977) are the only other team to have two appearances in the bottom 20 within 5 years of each other. The 1977 and 1985 Buffalo Bills and 1972 and 1998 Eagles are the other repeat offenders.

The big surprise for me here is the Minnesota Vikings being a little better than the Steelers. This is mostly due to turnover % (the Steelers  have had 5% more offensive drives end in a turnover than Minnesota) and Yards Per Point (the Steelers are 23rd best, the Vikings are 16th).

Revisiting Russell Wilson and The Defensive Impact On O-SCORE

Getting caught up on a couple emails:

Jay writes:

Outstanding job on your offensive efficiency rankings, but you didn’t mention the quality of defense faced by each team. Surely a team which faces soft defenses is going to appear to be more efficient than one who plays the Ravens, Steelers etc?

It’s a good observation.  The quality of defense a team faces definitely has an effect on offensive production. The next series of posts I do will be on a corresponding defensive efficiency ranking (called, unsurprisingly, “D-SCORE”). I thought it would be more useful to get the defensive piece of the puzzle out of the way before adjusting O-SCORE to reflect opponent defensive quality. I suspect though, that in most cases there will be only a modest-to-small impact over the course of a season. It’s very rare for a team to play more than 3-4 really good or really bad defenses. Because football sample sizes are so small, and each sample has a ton of variables for which stats can’t account, I’ve found that it’s often better to take a slightly broader view of things than you would with other sports. Sometimes mincing things too finely can skew your data more than if you had gone with a broader-than-ideal way of looking at things.

That said, it’s definitely something that I’ll be looking into and presenting for discussion.

GoHawks writes:

During a Wisconsin game, the announcers were making the case that Russell Wilson’s height shouldn’t be an issue because he plays behind an “NFL sized” OL already….thoughts?

That argument seems to be gaining a little traction and I suspect we’ll be hearing about it more as we get closer to April. My problem with it is that the size of the OL is fine, but what about the size/length/speed of the defensive players he’s facing? That’s really the challenge. Too much of the “height discussion” has centered around his ability to see over the line – which is only a part of the problem small QB’s face. There are other factors to consider:

– I think we can assume that NFL DL and LB are better than their college counterparts. Furthermore, they’re usually the best physical specimens in the country. The biggest guys who can run the fastest, or the most agile 350 lbs guys, or the guys with the longest and strongest arms. These guys can tip passes and disrupt QB’s far better than college players. The taller a QB, the easier it is for him to get the ball over the line and avoid tips (unless he has a funky delivery/release point).

– Along the same lines, Wilson is protected by a very good Wisconsin OL which is better relative to their opponents DL than most pro OL’s. In other words, unless Wilson is playing behind a top 5 NFL OL, he is going to be challenged significantly. Combined with the “bigger, faster” point, he is unlikely to have the kind of time in the pocket he enjoys now. And when he had less time, at N.C. State, he looked like a guy who was just another short college QB with very limited pro potential.

– It’s not just height, it’s overall size. Wilson makes a fair number of plays with his legs, and chances are he’d have to make more in the pros because defenses are better and his OL will (most likely) be worse relative to his opponent’s DL. While he’s RB sized (5’11, 210), as a QB he can’t afford to take the beating a RB would and still remain effective. How many times have we seen a “mobile” QB who becomes less effective after taking a bunch of hits? I’m not saying Wilson couldn’t take the pounding, but it’s certainly something to consider for any QB who relies on extending plays with his legs. Furthermore, I’m not sure Wilson is athletic enough to have a ton of success extending plays in the NFL (again, NFL players are faster and bigger and Wilson isn’t Michael Vick in terms of athletic ability).

– For all the talk about Drew Brees, people forget that Brees has a somewhat unusually high release point. I’m guessing he developed that somewhere along the line to compensate for his height. Wilson is not only shorter, but releases the ball lower which could present problems for him.

I don’t like to categorically dismiss players based on one physical attribute, so I’m not going to say Wilson will definitely flop in the NFL. But the track record for short QB’s is abysmal for a reason. So while Wilson has shown he can succeed behind a “big” OL, I’m not sure that means he can succeed behind the average NFL line. Much of his success comes from him being able to compensate for his small stature because the Wisconsin OL is bigger and better than their opponents. When his line breaks down, he can outrun many of his pursuers to make a play out of the pocket. I don’t foresee him having that type of advantage in the pros, which to me is a much bigger concern than the height of his OL.

O-Score: Final Rankings

In case you missed it, here are the first five parts to this series:

O-Score: Measuring Offensive Efficiency (A Preface)

Offensive Efficiency: Yards Per Drive

Offensive Efficiency: Turnovers

Offensive Efficiency: TD% And Points Per Drive

Offensive Efficiency: Yards Per Point

Some final thoughts on our variables before we look at the final scores:

– Turnovers: It seems like common sense that a team that turns the ball over a lot is unlikely to score a lot of points – but that’s not necessarily the case. In fact, a team’s turnover rate is only very weakly linked to their points scoring. The 1977 Cleveland Browns, 2001 St. Louis Rams and 1993 Houston Oilers all had offenses which scored 10%+ more than league average but are all bottom 2o (since 1970) teams in turnover ratio. However, of the 50 teams which turned the ball over the least, only 5 had worse-than-average scoring offenses (measured by points per drive). The conclusion here seems to be that great scoring offenses who turn the ball over a lot aren’t hurt too much since they are so efficient at turning their other drives into points. Offenses which turn the ball over a lot tend to be mediocre or worse at scoring points, but some of that is probably due to a lack of talent. After all, how many great QB’s turn the ball over a ton? How many high-quality RB’s fumble a lot? A few, for sure. But in general, elite scoring offenses are laden with elite talent – the type of which doesn’t turn the ball over and can overcome the mistakes they do make. The negatives effects of offensive turnovers are more likely to appear in their team’s defensive stats.

– Yards Per Drive: Again, the takeaway point here is that great scoring offenses generate a lot of yards per drive. Teams who have high points-per-game or points-per-drive tend to have high TD%. Because TD drives are (usually) longer than drives which end in field goals or punts, a high YPD is very common amongst high TD% teams. Since 1970, there have been 571 offenses which have been below-average in terms of YPD. Of those, only a mere 83 (14.5%) put up a PPD better than league average.

-TD% – A variable which is closely tied to Points Per Drive. Touchdown drives maximize the number of points your team scores (i.e. it’s unlikely you will be outscored in a game if you score a TD on every drive, assuming a PAT conversion, your opponent would either need an extra drive or to make a 2 point conversion). Furthermore, drives which end in TD’s obviously cannot end in turnovers or punts – both of which can lead to an opponent scoring a non-offensive TD.

– Yards Per Point – At the risk of sounding redundant, great scoring offenses almost always have high YPP rankings. However, there is a large “middle class” of YPP offenses which under-perform their expected PPD ranking. This could be due to a number of variables (shaky field goal kicker, red zone troubles, turnovers, etc). It’s rare for a below average YPP offense to have an above average PPD (about 15%). This stat can be skewed a little by a team having an elite defense or special teams – creating an unusually high number of short fields for the offense.

-Points Per Drive – This is the most important measure of an offense. It tells us what the offense does with what they are given. It’s a much better way to measure an offense than Points Per Game – as teams with terrible defenses will have fewer offensive opportunities. The problem with using PPD as the sole measure of offensive efficiency is that it doesn’t the whole story. Imagine these two scenarios:

Team A: 8 offensive drives, 8 FG’s = 3 PPD

Team B: 8 offensive drives, 4 TD, 2 punts, 2 turnovers = 3.5 PPD

While team B scored 4 more points (assuming XP and not 2 point conversions), the 2 turnovers and 2 punts are more likely to lead to their opponent scoring than Team A’s 8 kickoffs (even more the case with the new kickoff rules). Therefore, while team B scored more points, they are more likely to give up more points – assuming league average defense and special teams for both Team A and Team B. Another way to think of this is that Team B’s offensive points are worth less than Team A’s

So, in coming with my final scoring system, I took these five variables and weighted them in this order:

Points Per Drive

Yards Per Point

TO%

TD%

Yards Per Drive

All variables were taken as a percentage of league average. For example the 2007 New England Patriots had a YPD of 43.58, which was 40% better than league average. So for my rankings, I assigned them a YPD value of 45. The 2007 San Francisco 49ers had a YPD of 20.98, 33% worse than league average, so they get a value of -33.

The coefficients by which I weighted each variable were determined largely by a series of linear regression models. If you’re unfamiliar with regression analysis, it’s a way of mathematically determining the effect a variety of different variables have on another variable. The goal was to determine which offense gave their team the best overall chance to win, assuming a league average defense. Because the math is as boring as it is complicated for most, I’ll skip it for now (and revisit it perhaps in a future post for the math geeks out there).

The other, smaller, part of the coefficients is much less scientific. There’s a point to which stats unfortunately can’t explain everything. There’s simply no way to know how many times a drive which ends in a turnover would have otherwise ended in a score. Furthermore, there is very limited data (in terms of years) available on things like points of turnovers and red zone scoring %. There’s also stuff which isn’t reflected in stats, such as “can this offense effectively run out the clock when they’re winning, even if they’re not a high-scoring team” (YPD is probably the closest we can come to figuring that out statistically). To this end, I put a little additional weight on TO% and YPD and a little less weight on TD% (which is partially overlapped by PPD anyway).

Here are the top and bottom 20 offenses of all time. For rankings of every team since 1970 click here. Keep in mind that an OSCORE of 0 would be exactly average

Top 20:

Rank	Year	Tm	OSCORE
1	2007	New England Patriots	65.48
2	1984	Miami Dolphins	52.64
3	2010	New England Patriots	50.26
4	2004	Indianapolis Colts	49.62
5	1994	San Francisco 49ers	49.22
6	1993	San Francisco 49ers	49.19
7	1998	Minnesota Vikings	49.04
8	1992	San Francisco 49ers	48.86
9	1982	San Diego Chargers	47.26
10	1976	Baltimore Colts	45.80
11	2000	St. Louis Rams	45.25
12	2006	San Diego Chargers	43.11
13	2005	Indianapolis Colts	41.36
14	2006	Indianapolis Colts	41.29
15	1998	Denver Broncos	41.19
16	1983	Washington Redskins	39.80
17	1977	Miami Dolphins	39.40
18	1991	Washington Redskins	38.55
19	2002	Kansas City Chiefs	38.33
20	1973	Los Angeles Rams	37.69

Bottom 20:

Rank	Year	Tm	OSCORE
1170	1973	San Diego Chargers	-35.44
1171	2000	Cleveland Browns	-35.54
1172	1997	New Orleans Saints	-35.55
1173	1990	New England Patriots	-36.01
1174	2000	Cincinnati Bengals	-36.37
1175	1985	Buffalo Bills	-36.39
1176	2002	Dallas Cowboys	-36.75
1177	1998	Philadelphia Eagles	-37.60
1178	2004	Chicago Bears	-38.34
1179	1977	Buffalo Bills	-38.37
1180	1976	New York Jets	-38.76
1181	1991	Indianapolis Colts	-40.04
1182	2010	Carolina Panthers	-40.35
1183	1972	Philadelphia Eagles	-40.50
1184	1976	Tampa Bay Buccaneers	-40.56
1185	2009	St. Louis Rams	-41.96
1186	1992	Seattle Seahawks	-45.35
1187	2006	Oakland Raiders	-55.49
1188	1974	Atlanta Falcons	-59.13
1189	1977	Tampa Bay Buccaneers	-61.32

Offensive Efficiency: Yards Per Drive

As I mentioned previously, in determining offensive efficiency I chose five variables with which to work. The first of which is Yards Per Drive (YPD). Now I know what you’re thinking: football games aren’t scored in yards so why should we look at it when examining the quality of an offense? While it’s true that yards, in a vacuum, don’t mean much, they should be considered for a few reasons:

– Offenses which generate more yards per drive tend to score more points. But this doesn’t tell us all that much about offensive efficiency because a team which drives 80 yards every time they have a ball but never get touchdowns (instead settles for field goals) isn’t a model of efficiency.

– Long drives which don’t necessarily end in points can still be productive. The chances of scoring on a particular drive are somewhat dependent upon a team’s starting field position. Starting a drive at the 50 is more likely to result in points than starting a drive at your own 1 yard line. Teams which generate a lot of yardage per drive are more likely to win the field-position battle in a given game. Indirectly, this should lead to more points in the long run.

Here we see that there’s definitely a correlation between offenses which score a lot of points and offenses which generate a lot of yards per drive. Again, this doesn’t really tell us much about an offense as any team which scores a lot of points is going to have to get a lot of yards unless they have extremely good special teams or a defense which creates a lot of turnovers (in either case, the average starting field position would be improved to the point where less yards would be needed to score points).

Here are the best and worst YPD offenses of the last 40 years:

You’ll notice a lot of the same teams as in yesterday’s post.

And here are the highest PPG offenses and their corresponding rank by YPD:

What we see is that while high yards-per-drive offenses tend to score a lot of points, there are a few teams which scored a lot of points but weren’t particularly high in yards-per-drive. The most noticeable example is the 1983 Washington Redskins who had the 4th highest scoring offense of all-time but aren’t in the top 25% of best YPD offenses (and they were only 5th best in 1983).

Here are the best YPD offenses and how they stack up in terms of PPG:

Five of the top 10 PPG teams are in the top 20 of YPD but there are seven teams here outside of the top 100, including the 2nd and 3rd best YPD offenses. The reason (which you might have guessed) the 2008 Broncos vastly underperformed relative to their YPD is the same reason the 1983 Redskins over-performed: turnovers – which will be the subject of tomorrow’s discussion.

O-Score: Measuring Offensive Efficiency (A Preface)

How do we determine how efficient a team’s offense is? It’s a tricky question to answer and perhaps more complex that it seems at first. This is the first part of what will be a week-long look at offensive efficiency. Lets start off with what appears to be an obvious statement:

Football games are won by scoring more points than your opponent. The vast majority of points are scored by a team’s offense (93.5% since 1970). Therefore, a good offense is one which scores the most points.

Right? Well, not really. Imagine this scenario:

Team A has 12 offensive drives in a game. They score touchdowns on 4 of them (and go without points on the other 6). At the end of the game, Team A has scored 28 points.

Team B only gets the ball 8 times and scores touchdowns on 3 of them. They end up with 21 points.

Which is the better offense? Team B scored more frequently than Team A but their overall points-per-game output is hampered by their lack of offensive drives.  Further complicating this evaluation is that the reasons for Team B having less drives could be related to any number of factors – some of which are offense driven and some of which are out of the offense’s control.  I’d probably prefer to have Team B’s offense which is most likely (but not necessarily) more efficient than Team A’s. It presents us with an interesting challenge in determining offensive efficiency.

In my mind there is a  (perhaps subtle) difference between “value” and “efficiency”. In terms of the way it is commonly evaluated: value is situation and play dependent, whereas efficiency is best defined in a broader view.  Therefore,  efficient offenses are almost always valuable but valuable offenses are not necessarily the most efficient. This is especially true once we get beyond the extreme ends of the statistical distribution. To illustrate this here is another hypothetical situation:

Team A has 9 offensive drives in a game and scores a TD on all 9. They win the game 63-0

Team B has 9 offensive drives in a game and scores a TD on all 9. They win the game 63-62

Both teams have equally efficient offenses (in an overly simplified touchdowns-per-drive way) but team B’s offense would have more value. In Team B’s case, their offense is able to keep pace with their opponent and the most common “value” metrics would give them a bonus for consistently getting go-ahead scores after their opponent scores. In other words, their 9th touchdown would have much greater value than Team A’s 9th TD.

For the purposes of this discussion, I’m going to stick to offensive efficiency. If you’re interested in a value-driven discussion, the folks over at Football Outsiders do an excellent job with their DVOA metric.

So, how do we measure offensive efficiency? I haven’t found a specific stat which answers that question to my liking, so I decided to create my own which I call simply “O-Score” (or Offensive efficiency Score). It’s essentially a team’s performance relative to league average in a few different efficiency stats with a strength of schedule adjustment.

Here are the statistical categories I’ve chosen to include:

Points Per Drive

TD%

Turnover%

Yards Per Point

Yards Per Drive

Over the course of this week, I’ll be discussing each one of these variables separately and then unveiling the final scores over the weekend. Until then, check out the best and worst point-per-game offenses since the AFL/NFL merger:

Where will these offenses rank in terms of efficiency? Check back later this week to find out.