At some point during each Saturday for the past several weeks, I’ve asked my wife “Guess what starts four weeks from today?” or “... three weeks from today?” etc. Each time, she pauses, sighs, and then reluctantly says “College football.” Clearly, I’m pretty excited about the upcoming season. At this point, we’re mere days away from kickoff (I haven’t asked “Guess what starts in three days?” because I don’t want to come home to find that the locks have been changed). For the first time in many years, I’m looking forward to sustained improvement on both sides of the ball. I wasn’t terribly excited when Cal hired Sonny Dykes. I enjoyed watching a functioning offense again—especially after the 2010–2012 years of the Tedford offenses, which were like watching someone throw strands of spaghetti at the wall to see which ones stick. That offensive ineptitude was replaced by defensive ineptitude under Sonny Dykes. As a result, there was always that nagging feeling that even if the team piled up 500+ yards per game, we’d still struggle to attain bowl eligibility due to some of the worst defenses Cal has ever produced.
But things have changed in the Justin Wilcox era. The same ragtag bunch of players who struggled to make reads and tackles in 2016 suddenly started playing respectably in 2017. Despite replacing most of the major contributors at the skill positions, the Toyota Tercel offense (I’ll never tire of that metaphor) was good enough to keep us competitive in most games. A differential of 10 points in three pivotal games made the difference between a memorable 2017 (5–7) and a spectacular 2017 (8–4) season. There’s good reason to be cautiously optimistic about 2018.
A couple of weeks ago, I asked you all to gives us Cal’s chances of defeating each opponent. Nearly 250 of you participated (a pleasant increase in turnout over 2017, which was a mild increase over 2016’s turnout—again, excitement abounds). Today we’ll look over the results and see how 2018 may unfold for the Bears.
Results: A Huge Shift in Optimism—with a Caveat
I have taken all the predictions and summarized them into the table below. Next to each opponent, we have the average prediction that the Bears will win and the standard deviation, which captures the amount of uncertainty in our predictions. To notice the most remarkable change, we have to go back the results of last year’s predictions. Last year we picked the Bears to win 5.76 games. The 2017 Bears simultaneously managed to overachieve and underachieve that mark, but what was most notable was that we favored the Bears in only three games. Look at these games below: this year we favor the Bears in a whopping nine games. And if the Arizona predictions were one percentage point higher, that number would be 10. That is a spectacular shift in optimism.
|Opponent||Avg. Win Chance||Standard Deviation|
|North Carolina||78.3% (+2.5)||11.5|
|at BYU||68.1% (-1.0)||16.4|
|Idaho State||95.0% (+0.4)||9.5|
|at Arizona||49.1% (-2.5)||14.1|
|at Oregon State||76.9% (+1.7)||14.1|
|at Washington State||54.7% (+0.5)||16.1|
|at USC||31.1% (+0.3)||17.4|
|Total||7.20 wins (-0.03)||1.19|
Before you start looking at hotels in Pasadena on December 31st, keep in mind that being favored does not automatically mean the Bears will win and being underdogs does not automatically mean the Bears will lose (otherwise 2017 would have been pretty unpleasant). Three games in which we favor the Bears fall into the 40–60% toss-up range. So there’s a fair chance we still may lose to Oregon or Wazzu despite favoring the Bears. That’s why our projected total number of wins is only 7.20, even though we favor the Bears in 9 games. Still, NINE GAMES!
The Bears open the season with a favorable three-game OOC stretch. We give the Bears generous odds of winning each game. Then comes a crucial three-game stretch. We give the Bears a narrow 50.1% chance of beating the Ducks, then barely favor the Wildcats in Tuscon (Have I mentioned how much I HATE games in Tuscon?), then moderately favor the Bears against the Bruins in Berkeley. A 6–0 start isn’t unfathomable. And the following game in Corvallis would mean a 7–0 start ahead of a battle with the Huskies with huge Pac-12 North title implications.
However, the numbers suggest that the UW game will be our likeliest loss of the year, followed two weeks later by our second-likeliest loss in a match at USC. Sandwiched in between those likely losses is a toss-up against a Cougs team that wouldn’t surprise me if it wins 8 games or if it wins 3.
Our final two games are two favorable home games, including a Big Game in which we give the Bears 58.1% chance of bringing the Axe home. Are we a touch over-optimistic after nearly pulling the upset last year in Palo Alto? Perhaps. Do I still think we’ll end the streak this year. Yes I do! The year ends with a very favorable matchup against a Colorado team that, like Wazzu, may win 8 or it may win 3.
In addition to the table above, I’ve plotted the results below to show the distribution of our predictions. The plots have been smoothed to account for idiosyncrasies in the data (e.g. propensities for people to submit predictions divisible by 5).
As our FCS opponent, Idaho State is clearly the most probable win. Then we have Carolina and Colorado, two favorable games where wins are not guaranteed. Then we have an odd trifecta of UCLA, Oregon, and LSJU in that critical toss-up range. I’m really surprised by how many people predict that Oregon will be tougher than the Lobsterbacks. No surprise, however, is that UW is by itself on the far left as our toughest game of the home slate.
Next we have our five road games with a pretty clear hierarchy of difficulty.
Thank Oski we’re not playing against Beau Baldwin’s squad when Cal plays Oregon State this year. Otherwise our predictions wouldn’t be nearly as optimistic. BYU looks like a likely (but not certain) win while we’re at the positive end of toss-ups with the game against Wazzu. The Arizona match-up is about as close to a coin flip as one can get. And then we have our annual and dreaded trip to Los Angeles. We ought to have a better chance than normal to defeat USC, but it’s hard to shake the looming doom carried by 14 consecutive losses.
Simulating the Season
Next we move on to simulations of the season. The simulation procedure is pretty simple: I start by drawing a prediction for the Carolina game at random, and use that prediction to determine whether we win or lose. If I draw a .70, then we have a 70% chance of winning and a 30% chance of losing. After drawing a win or loss, I move on to the next game, draw another prediction at random, and use that prediction to determine whether we win or lose. I repeat the process until we’ve gone through the whole season. Normally, I do this for all 12 games, save the total number of wins, and then repeat the process until we have one million simulated seasons. This time I employed a slightly more sophisticated approach in which I save the number of wins after each game. That way we can see how likely we are to have 0 or 1 wins after Carolina, 0, 1, or 2 wins after BYU, and so on. I’ve plotted those probabilities below and shaded the boxes according to how likely that outcome is.
The probabilities disperse over the course of the season because the number of possible scenarios (0 wins, 1 win, 2 wins, etc.) increases after each game. But we can see some concentration in win probabilities over time. After the Wazzu game, for example, our likeliest outcome is to have 6 wins (and bowl eligibility!). By the end of the season, we can see how likely we are to finish with everything from 3 wins to 11 wins according to our predictions. Consistent with our projected win total from the table at the beginning of this piece, 7 wins is the likeliest outcome. The Bears look to improve over last year’s record, as we’re as likely to win 9 games as we are to finish with 5 or fewer wins.
As is our custom, we hand out awards to the most remarkable predictions. We highlight those that were closest the community averages, the most optimistic predictions, and the most pessimistic predictions. First up, those most reasonable of predictions.
The Voice of Reason
This is a particularly interesting set of winners this time because 1) anyone in the top five would have had the lowest standard deviation in our 2017 preseason predictions and 2) jrrad1980 and jolimpact finished 2nd and 1st, respectively, in our spring edition of our preseason predictions. Well done!
Next we have the sunniest, most optimistic predictions culminating in a two-way tie for first between OCBear1983 and Remember the Calamo.
|6. Ghost of Joe Roth||10.57|
|8. Oski Disciple||9.93|
|9. Jose N.||9.84|
Finally, we turn to those who couldn’t find a ray of sunshine in an Alaskan summer, the Old Blues. They loved Cal football once and it broke their hearts—and all they expect now is doom and gloom. But apparently not that much doom and gloom, as only five of us predicted a fate worse than the 2017 Bears. That should fill us all with optimism.
|8. Davis Rich||5.40|
If 7 wins isn’t enough optimism for you, wait until tomorrow when we post the results of last week’s 2018 Pac-12 Predictions. Four schools will be very happy if 2018 follows those predictions—and Cal is one of those beneficiaries.
How would you feel about 7 regular-season wins?
This poll is closed
CONTRACT EXTENSIONS FOR EVERYONE
I wish we would have hired Herm Edwards instead