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Can you feel it?
Last week I told my best friend (shout out to Jennifer!) that I am starving for football. Starving for Saturday games, whether they would be at 3pm or 10pm here in the East Coast. I miss reading Bill Connely’s stats on Tuesday mornings to rave or rage about our team and our opponents. I miss singing the fight songs, shouting “TOUCHDOWN BEARS”, and writing for CGB in joy and in anguish.
With the season looming around the corner I decided to evaluate the offensive projections for Cal’s 2016 opponents. Allonz-y!
Big Picture Projections
2016 Schedule |
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| Date | Opponent | Proj. S&P+ Rk | Proj. Margin | Win Probability |
| 26-Aug | vs. Hawaii | 118 | 18.2 | 85% |
| 10-Sep | at San Diego State | 55 | -2.7 | 44% |
| 17-Sep | Texas | 34 | -0.9 | 48% |
| 24-Sep | at Arizona State | 57 | -2.4 | 44% |
| 1-Oct | Utah | 39 | 0.5 | 51% |
| 8-Oct | at Oregon State | 86 | 4.2 | 60% |
| 21-Oct | Oregon | 18 | -6.7 | 35% |
| 27-Oct | at USC | 8 | -16.0 | 18% |
| 5-Nov | Washington | 10 | -8.7 | 31% |
| 12-Nov | at Washington State | 48 | -3.7 | 42% |
| 19-Nov | Stanford | 16 | -7.0 | 34% |
| 26-Jan | UCLA | 12 | -8.2 | 32% |
| Projected wins: 5.2 | ||||
This projection of 5.2 wins a little more pessimistic than what I personally expect from Cal. I think a big chunk of the downward projects is the high level of uncertainty on offense. We lost our Goffensive leader, and over 80% of our WR production across all statistics. Furthermore, Cal changed OCs from Tony Franklin to Jake Spavital (Spavifense(R)). How do those numbers look vis-a-vis Cal’s 2016 opponents?
Vis-a-Vis 2016 Opponents
| Returning Production | |||||
| Team | Proj. S&P+ Rk | Overall | Offense | Defense | |
| Date | Cal | 49 | 39% | 13% | 62% |
| 26-Aug | vs. Hawaii | 118 | 67% | 66% | 69% |
| 10-Sep | at San Diego State | 55 | 66% | 52% | 79% |
| 17-Sep | Texas | 34 | 80% | 79% | 81% |
| 24-Sep | at Arizona State | 57 | 35% | 27% | 43% |
| 1-Oct | Utah | 39 | 55% | 35% | 76% |
| 8-Oct | at Oregon State | 86 | 75% | 72% | 78% |
| 21-Oct | Oregon | 18 | 64% | 49% | 79% |
| 27-Oct | at USC | 8 | 66% | 54% | 77% |
| 5-Nov | Washington | 10 | 76% | 72% | 79% |
| 12-Nov | at Washington State | 48 | 79% | 87% | 71% |
| 19-Nov | Stanford | 16 | 36% | 20% | 52% |
| 26-Jan | UCLA | 12 | 72% | 61% | 88% |
This table depicts the level of uncertainty we’re coming into the season. None of our opponents will experience that level of drop-off in offensive performance.
We can see here that out of Cal’s opponents only ASU and Stanford have a fewer amount of production returning. On offense Cal is only returning a tiny 13% of the production, this can only be compared to Stanford’s 20% of returning production (16% of which is probably Christian McCaffrey). The average returning production for our opponents in 2016 is 56% with Washington State returning 87% of its offensive production next year. In all of the cases we can expect Cal’s defense to face experienced offenses, unlike Cal’s basically brand-new passing attack that is returning 13% of its offensive production which according to Bill Connelly’s model means a decline of 6.2 points per game.
Part Where Fancy Math was Used
| Team | O returning | Proj. O PPG change | D returning | Proj. D PPG change | Overall Returning | Overall proj. PPG change | Rank |
| Texas | 79% | 2.7 | 81% | -3.1 | 80% | 5.8 | 14 |
| WSU | 87% | 3.7 | 71% | -1.4 | 79% | 5.1 | 23 |
| Washington | 72% | 1.7 | 79% | -2.8 | 76% | 4.5 | 27 |
| UCLA | 61% | 0.2 | 88% | -4.3 | 75% | 4.5 | 28 |
| Oregon State | 72% | 1.6 | 78% | -2.5 | 75% | 4.1 | 33 |
| Hawaii | 66% | 0.8 | 69% | -0.9 | 67% | 1.7 | 60 |
| SDSU | 52% | -1.1 | 79% | -2.8 | 66% | 1.7 | 63 |
| USC | 54% | -0.8 | 77% | -2.5 | 66% | 1.6 | 64 |
| Oregon | 49% | -1.5 | 79% | -2.8 | 64% | 1.3 | 69 |
| Utah | 35% | -3.5 | 76% | -2.2 | 55% | -1.3 | 99 |
| Stanford | 33% | -3.7 | 61% | 0.5 | 47% | -4.2 | 115 |
| California | 15% | -6.2 | 62% | 0.2 | 39% | -6.4 | 124 |
| Arizona State | 27% | -4.5 | 43% | 3.7 | 35% | -8.2 | 126 |
This chart shows us the impact of lost and retained production as per Bill Connely’s analysis. As per tradition of Cal not being able to have nice things, out of all of our opponents, only ASU will suffer a larger decline in PPG, and no other team will suffer a larger decline in Offensive PPG. In the model Cal will lose a touchdown per game simply due to the drain on offense.
To visualize the impact of this projected decline in PPG: out of 13 games Cal played in 2015, 4 games (@ Texas, @ Washington, WSU, and ASU) were won by 6 points or less, this would change the W-L record from 8-5 to 3-9 (since we end 3-9 we never play against the Air Force in the bowl game, and thus never gain the 8th win).
However, it was pointed out by Bill Connely that the precipitous decline in production, Cal presents an interesting case: are we rebuilding or are we reloading? With the addition of Davis Webb and the rave reviews of Meliquise Stovall and Demetrius Robinson coming out of camp I doubt the decline from 2015 will be anywhere near 6 PPG.
Our opponents on the other hand did not lose as much as we have over the course of the year. Each of our opponents is projected to do better on offense relative to Cal’s offense with PPG differential between Cal and its opponents ranges from 1.7 points (ASU) and 9.9 points (WSU).
Final Thoughts
If we go back to the first chart, we should look at the projected margins of loss/victory. Assuming that Cal’s offense will only decline by 3 PPG, and not 6.2. Holding all else constant, the win/loss ratio for Cal increases from a 5.2 to 6+ wins with Cal being favored in 6 games rather than 3 in the original projections. While also giving us a much closer match-up with WSU.
Uncertainty is the flavor of the season for Cal. The loss of Goff et al. will hurt and be visible, however, the influx of raw athletic talent from the WRs will shake things up on the field. Furthermore, this uncertainty will mean that for the first few games of the season the S&P+ projections and values will be fluctuating wildly as the model calibrates to the 2016 season. In the case of Cal fans: Cardiac Bears are here to stay.