In a previous article I documented the scoring performance trend for the USC Trojans football team over the entire Pete Carroll era stretching from 2001 to 2007. The trend is impressive in multiple respects and deserves accolades. Many Trojan fans have fretted, however, as the offense has averaged a more pedestrian level of 30.46 and 32.62 points per game the past two seasons. A more complete game by game look at the scoring trend yields the following trend:
A polynomial fit through the trend has a nice upward spike towards the end of 2007 when all the players were finally healthy. There were a couple of noted stretches over two most recent seasons, however, when the Trojans failed to approach the overall average of 36.24 points per game for the Pete Carroll era.
Of course, multiple reasons exist when teams struggle to score points. In the previous article I outlined the rather large effect that a decline in turnovers forced by the defense has had on the scoring situation. Fewer turnovers equates to poorer field position and a greater number of long field drives. Without a turnover, USC receives the football via a punt instead of starting near mid-field where the Trojans started so many drives in the past thanks to their stellar defense or occasionally strong special teams play.
Through an intermediary I sent the gist of the turnover analysis to Head Coach Pete Carroll and he was kind enough to look at the document and relay back two comments. Number one: he agreed that the analysis was correct and it accurately reflected the large effect that turnovers and positive field position can have on scoring. Most teams , for example, have a 10% chance (or less) of scoring when starting backed up near their own end zone. Move the ball out to mid-field and the scoring probability jumps well over 50% for most any team.
Secondly, however, Coach Carroll commented that also "big plays" on offense are down for the USC Trojans compared to the past few years, excluding the 2001 season of course. This insight I suspect is much easier to digest and more obvious for fans that have watched the Trojan offense the past two seasons.
Carson Palmer and Matt Leinart were more exciting to watch at QB than the reliable and efficient John David Booty. Reggie Bush was a human highlight reel that recent running backs such as Chauncey Washington and others did not match. And the wide receivers in 2007 did nothing to make fans forget Mike Williams, Dwayne Jarrett, or Steve Smith. 2008 may of course be a whole different story.
Big plays are an important lens for viewing any offense. According to an unpublished NFL report "big plays" are one of four metrics that tend to correlate with winning. The four metrics mentioned are:
- First down efficiency (% of 1st down plays that gain +4 yards)
- Red zone efficiency (% of scores when inside the 20 yard line)
- Explosive plays (+12 yard run plays & +16 yard pass plays)
- Turnover margin (turnovers gained - turnovers lost)
Note: Unfortunately I have not been able to track down this report or verify its exact methodology. It is mentioned in passing in the book Developing An Offensive Game Plan.
So big plays apparently are not only exciting for fans to watch but necessary for winning as well, in some statistical sense. Big plays are tough to study, however, since they are not tracked or published online by any service I could locate. Just looking at averages for instance does not give you an indication of the number of big plays contained within that number. Here for example is the recent yards per play performance by USC.
In order to see the big play differential, the data is easier to view when it is converted into a histogram showing the frequency of how many times a certain amount of yardage has been gained.
Here, for example, is the amazing performance of the 2005 USC Trojan offense in total when viewed in this fashion instead of using averages.
As you can see, USC had an amazing 138 plays that season that gained +16 yards either on the ground or through the air. Over 100 other plays gained +10 yards or more as well. The spike centered around the zero value is mostly due to incomplete passes as well as a few zero rushing yardage plays.
For comparison, let's look at a more normal year such as the recently completed 2007 season using the same method. Here you can see clearly that the spike for "big plays" of +16 yards is down from 138 to 102 for a decline of 36 plays or roughly three big plays per game over the course of a season as Coach Carroll points out. In addition, there were a few more zero yard and negative yardage plays as well.
What does the undefeated 2004 national championship year for USC look line in terms of total offense?
Surprisingly the chart is not all that different in shape from the 2007 season. The number of total big plays greater than sixteen yards is essentially even between the two seasons. The number of zero yardage gains, however, is significantly lower in 2004 than in 2007. This ultimately all equates to the half yard per play advantage (6.3 yards versus 5.8 yards) the 2004 team had over the 2007 team.
The NFL study separated out big plays into +12 yard run plays and +16 yard pass plays. Displaying this slightly different breakdown in chart form would take forever so I summed up the 2002 to 2007 seasons into the following table for ease in viewing. (Note: I skipped the 2001 data since it contained nothing remarkable and it would be the lowest mark in each category).
|Category / Season||2002||2003||2004||2005||2006||2007|
|Big Run Plays (+12 yards)||34||46||53||83||27||57|
|Big Pass Plays (+16 yards)||88||89||72||86||77||66|
|Big Pass Plays + Big Run Plays Combined||122||135||125||169||104||123|
|Just +16 Yard Plays Histogram (either run or pass*)||105||115||100||138||94||102|
*Note the "Just +16 yard play" data will match the histogram charts above due to the way the run and pass data is combined to generate this number. The above histogram charts will not equal +12 runs added to +16 yard plays column since the two fields are combined into one for the histogram (i.e. the +12 to +15 runs are dropped from the total).
As you can see, each season has a different pattern and strength. None of course live up to the standard set by the 2005 Trojan offense; few teams ever will in my opinion. The number one year in terms of big runs for USC was the 2005 season by a wide margin. The 2007 season comes in second just edging the 2004 squad. The top year for big passes is a close race between the 2002, 2003, and 2005 Trojan offense.
It would take 18 individual charts to show each season since 2002 for big runs, big passes, and total offense. If you are that curious here is a link to a page that contains all charts by category and by year (click here). Conversely if averages are more your cup of tea then this file is of more use (click here).
Looking at the table above highlights that the 2006 Trojan offense was quite deficient in terms of big run plays generating only 27 plays of greater than twelve yards. Conversely the number of big pass plays was significantly down in 2007 to the lowest level since 2001. Of course the loss of starting QB John David Booty for three games no doubt affected this total. Still however it was trending for a slightly down year in the passing department even before his injury.
Pete Carroll and the USC Trojan coaching staff did an excellent job improving the running game in 2007. I suspect that the onus now moves mostly back to the passing side of the equation in 2008. A new more mobile starting QB in Mark Sanchez and a more experienced WR corps in 2008 may be poised for a break out year in that respect. Conversely a relatively new offensive line may drive some caution and a higher percentage of three step passes for the early part of the year until the offense settles in and finds a rhythm.
Keep in mind also however that opponent defensive coordinators are not sitting idly by twiddling their thumbs. They spend their off season studying opponent film and figuring out ways to stop attacks. Either in the form of different fire zone blitzes or slightly different secondary schemes, etc. they will have something new in store in 2008 as always. From casual observation and reading recent off season coaching clinic material it appears that more teams in the Pac-10 seem to be favoring a Cover 4 secondary scheme (aka quarters coverage) on defense than in the past.
Cover 4 Sample Alignment
This scheme is normally tough to throw deep against as it defends deeper vertical passing routes very well. Instead it gives up the flats area forcing a more lateral style passing attack. With down hill safety play it can also be quite effective versus the running game.
This scheme and other similar flavors such as the popular hybrid 1/4, 1/4, 1/2 style coverage schemes versus 3 WR Trips sets may be why YPC is down by 15% over the past half a dozen years in the Pac-10. Click here for a summary of Pac-10 offense trends to locate the YPC trend. Or perhaps it could be the influx of more defensively minded coaches into the league or other reasons such as player ability. That effect is tough to sort out and is good for debate. Of course that does not get the USC Trojans off the hook for the decline in big plays. The high standard of the past few seasons has created annually high expectations.
Regardless 2008 should be an interesting season to watch unfold overall in the Pac-10 and for USC in particular. I'll update the USC Trojan big play trends toward the end of the season to see how the results look in this regard. For USC to have a season that matches 2004 in terms of a national championship a sustained and balanced level of "big plays" in both the rushing and passing department will be required. Mark Sanchez, Stafon Johnson, Joe McKnight, Vidal Hazelton and other skill players get their chance to make big plays for the Trojans in 2008. I doubt however that a USC offense matching the 2005 squad will be been seen again for quite some time.
Note: The data for the histograms was calculated from unofficial play by play stats off of various websites. The charts are accurate to the extent that base data is correct which I can not confirm. Sampling a couple games versus the NCAA data base however did not show any significant deviation.