Tis the season.
Cal football is back in full. Gone are the uncertainties of Spring Ball, and in are the hopes that come with Fall camp. Our analytical and hype sides (borrowing a Nam-ism) debating between a 2-9 rebuilt year and a 8-5 over achievement. But what do the early, highly volatile S&P+/FEI numbers say about Cal and its next Match--up UNC?
One thing to note, since Cal changed its coaching staff and schemes, and UNC lost all of its meaningful production on offense. Thus these projections have a very high degree of uncertainty and have the predictive power of reading the flight paths of crows. The preseason model made by Bill Connely gives the Tar Heels a 5.5 point advantage. But hey, Cal has beat harder odds before (I certainly had in Econ 1... and 101A...).
California Golden Bears, 0-0 (0-0, Pac-12 North) | Projected S&P+ Ranking : 53
There will be a severe regression from the previous few years, the main factors being the change in QB, the turnover on the OL, and the implementation of the new scheme. It isn’t that the routes are different or anything, even concepts are mostly the same. However, it is the rhythm of the offense, the progressions, and the core bundle of plays that changes, with these changes it takes time for each player to be able to play within the scheme at full speed.
The change from 4-3 to 3-4 (with a LEO/Designated Rush LB) system also introduces another realm of uncertainty. Add the fact that under Kaufman the predominant coverage was a Cover 4 with little creativity and we’re basically moving from simple Supply/Demand graphs in a perfect competition to a marketplace with non-standard goods and asymmetric information from a complexity standpoint.
A lot of noise was made regarding the increased use of LBs in blitzes which should help the terrible HAVOC rate of the LB corps from 2016 (1.9%, 125th in the nation). Add the fact that both Darius Allensworth and Luke Rubenzer (active team leader in career INTs) are not starting on the depth chart we can imagine that the way DBs will play will also change.
North Carolina Tar Heels, 0-0 (0-0, ACC Coastal) | Projected S&P+ Ranking : 37
Here's a first look at the depth chart as we begin Cal game week. Kickoff is just five days away! #GoHeels #BeatCal pic.twitter.com/oCyYMrnsUy— Carolina Football (@TarHeelFootball) August 28, 2017
UNC lost nearly everyone. Cal’s 2016 season where Cal lost 6 WRs and Jared Goff to the NFL pales in comparison to the turnover on the UNC roster. Not only are they breaking in a new QB and a whole new WR corps, unlike Cal, they are returning only 2 linemen with double digit starts from last year.
Add the fact that their presumptive QB, Brandon Harris, has a career completion percentage of 53.9% on 347 attempts and a 2:1 TD:INT ratio indicates that the Tar Heels might struggle mightily on offense.
|Passing||Rushing||Total Offense||First Downs||Penalties||Turnovers|
Here lies the relative strength of the Tar Heels. Sans the sole INT they captured in 2016, this is an experienced unit lead by Senior SS Donnie Miles. This unit in 2016 was 44th in S&P+ on defense. Considering that the forecast have it raining during game day this should put a further damper on our hopes of seeing Ross Bowers really air it out on his starting debut.
We can see from 2016 that UNC’s opponents tended to find more success on the ground than through the air, as evidenced by the total yards, TD’s, and First Downs per game.
I promise once data starts flowing in I will have a more substantive reports and analysis. For now, due the high level of uncertainty leading to a high degree statistical volatility there isn’t a lot of reliable data to be used. This is one of the reasons football is played on the field, and not on a spreadsheet.
As it was mentioned before, S&P+ has us at 5.5 point underdogs, however, I think that the error on this prediction is high enough to warrant this a good chance for a Cal win.