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Predict the 2019 Cal Football Season, Spring Edition: Results!

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Did I mention coin flips and rock fights?

NCAA Football: Stanford at California
Whether we can exceed 7 wins largely depends on how well #7 plays this season.
D. Ross Cameron-USA TODAY Sports

The last seven seasons of Cal football have been a whirlwind. Tedford’s 2012 team was 7 years ago, although it feels like 7 decades ago. Six years ago, Sonny Dykes brought us the Bear Raid era of Cal football, featuring some of the most explosive offenses ever to grace Strawberry Canyon along with some of the worst defenses in school history. In two years Justin Wilcox and friends turned that all-offense, no-defense team into its exact opposite. Touchdowns have become a scarce commodity thanks to a suffocating defense and an offense that managed to regress from the Toyota Tercel offense to a hooptie on cinder blocks in West Oakland. Despite the ups and downs, we have been surprisingly consistent in our predictions recently. In 5 of those past 7 seasons we picked the Bears to win 7 games. Sometimes that was wildly optimistic (2013) and other times it was spot on (2015, 2018). After asking you all to participate in our first round of semi-annual Cal football season predictions, we have settled on a familiar number: 7 wins. After meeting expectations with 7 wins last year, apparently we haven’t set our sights any higher for 2019.

Results: Deja Vu

Not only do we expect the Bears to win 7 games, but we expect them to earn 7.20 wins. This is peculiar because that is exactly the same as our 2018 preseason predictions. After some horrific losses, that 2018 team bounced back by finding a unique identity: one in which a grinding defense pulverizes the opponent while the offense tries to avoid shooting itself in the foot. Returning nearly all its major contributors and introducing a couple breakout players, the defense is poised to make an improvement this year. But the offense has not done much to inspire confidence in a major turnaround. As a result, we don’t expect a marked improvement over last year. Before we start spending too much time imaging how good this team would be if it had the 2015 offense, let’s look at the game-by-game results.

Opponent Avg. Win Chance Standard Deviation
UC Davis 96.4% 5.7
at UW 37.8% 16.0
North Texas 87.6% 11.3
at Ole Miss 57.6% 14.2
ASU 63.2% 11.9
at Oregon 33.6% 14.3
OSU 82.3% 12.1
at Utah 42.8% 13.8
WSU 59.3% 14.3
USC 53.0% 15.8
at LSJU 52.5% 22.1
at UCLA 53.7% 13.8
Total 7.20 wins 1.10

The Bears open the season with the likeliest win of the year against the Aggies, and follow that with the second-toughest game of the year on the road against the defending Pac-12 champs. Despite defeating the Huskies in a profoundly satisfying rock fight in 2018, we’re not overly optimistic about the Bears’ chances in Seattle. Fortunately, we ought to get back in the win column when North Texas visits. After that, the schedule is full of uncertainty.

A coin-flip on the road against Ole Miss precedes a coin-flip at home against ASU, the Pac-12’s random number generator. The Sun Devils can beat anyone in the conference or lose to anyone in the conference, and chances are good it will be a one-score game. Then we face our worst and best odds of winning a conference game as we visit Oregon and host Oregon State on consecutive weeks. Then the gauntlet begins.

Starting with the road trip to Salt Lake City, every single remaining game falls into that crucial coin-flip territory, where our chances of winning are between 40 and 60%. Based on our chances of winning the prior games, we’ll probably start this stretch with 5 wins. Bowl eligibility is likely, but the team’s performance in these final 5 games will mean the difference between a mediocre season and a stellar one where we may become a dark horse to win the Pac-12 North. We favor the Bears in 4 of those 5 games, but we would be fortunate to win four. I’ll gladly settle for three wins in this stretch if it means we sweep the California schools in the final three games.

Below I have plotted the distribution of predictions for each game. This helps to visualize how concentrated or dispersed our predictions were, and where they tend to fall on a 0-100 scale.

Prediction distributions for each game. UC Davis is omitted because nearly all predictions fall into the 90-100 mark, which messes with the scaling and makes the other plots harder to read. Plus, these games are all far more interesting than the matchup with the Aggies.

That little bump at the 100% mark for the Big Game is a tradition as old as time itself. Oski smiles upon those of you who make that possible.

After the dust settles and the last rock has been thrown, we’re likely to end up at 7 wins. Again. Is that good enough? Last year the defense carried the worst Cal offense many of us have ever seen to 7 wins. This year the defense ought to be even better, so another 7-win season may not be good enough...

Simulations!

To provide more insight into the data, I ran some simulations based on our predictions. The simulation process is simple: I start by drawing a UC Davis prediction at random and use that prediction to determine if we win or lose. If the prediction is 90%, for example, I’ll have a 90% chance of drawing a 1 and a 10% chance of drawing a 0. I then move on to the Washington game, select a prediction at random, and use that to dictate the odds of drawing a 1 or a 0. I repeat this for each of the 12 games and then add up the results to get our final record. After one billion simulated season, we get the following distribution of wins.

Projected number of wins based on our predictions.

7 wins is the likeliest outcome, followed by 8 wins and then 6 wins. Looking at the probabilities in the table below indicates that we only give the Bears a 15% chance of failing to achieve bowl eligibility. After these last 7 years of Cal football, that’s a nice baseline.

Wins Probability
0 0.00%
1 0.00%
2 0.10%
3 0.72%
4 3.30%
5 9.69%
6 18.70%
7 24.70%
8 22.33%
9 13.67%
10 5.40%
11 1.21%
12 0.13%

While the preceding section tells us how likely we are to finish the season, it’s useful to examine our potential trajectories over the course of the season. While I was running the simulations, I stored the win-loss record after each game. So after 1 game I kept track of the number of simulated seasons with 1 win or 0 wins. After 2 games I kept track of the number of seasons with 2 wins, 1 win, or 0 wins. And so on. I plot the results in the figure below. The numbers in the boxes refer to the probability that the Bears have the number of wins depicted on the x-axis. To help readability, I’ve colored the boxes such that darker boxes are more likely.

Game-by-game projected win totals.

According to our predictions, after the UC Davis game we have a 96% chance of being 1-0. Then after the road trip to seattle we have a 2% chance of being 0-2, a 61% chance of being 1-1, and a 36% chance of being 2-0. And so on through the rest of the table. This is a helpful way to see which record is most likely as we complete each game.

Awards

As decreed by our Overlords at SBN, we cannot finish this series without handing out some awards. In order, we recognize those whose predictions were most optimistic, most pessimistic, and closest to the community average.

Sunshine Pumpers

Only one ballot gave us a 100% chance of winning every single game? These must be grim times in Bear Territory.

Name Wins
1. RememberTheCalamo 12.00
2. BoggerVB 11.98
3. Oski Disciple 11.47
4. Old Bear 71 9.92
5. texashaterforlife 9.58
6. rising4air 9.45
7. Olybear 9.10
7. CalBear91 9.10
9. Your Mama 8.95
9. CruzinBears 8.95

Old Blues

If you round to the nearest integer, only 5 of us expect us to miss a bowl game. That’s pretty good!

Name Wins
1. Poohbears 4.30
2. No SBNation user name 4.95
3. rollah 5.25
4. Don't have one 5.40
5. jubears 5.44
6. Bob 5.50
7. Skeedabear 5.54
8. joe 5.55
9. Terracewalk 5.60
10. oskioftarth 5.65

The Voice of Reason

Finally, these are those whose predictions were closest to our average predictions for each game.

Name Standard Deviation
1. shin2391 2.30
2. CalBearPete 2.89
3. Joe burn 3.37
4. Bearly Legal 3.92
5. Alex Ghenis 4.40
6. A$AP Bear 4.82
7. mrjpark 5.70
8. WilderThanGene 6.04
9. BTown85 6.22
10. Novarem 6.23

We’ll run one more round of these season predictions midway through Fall Camp. Until then, I hope you look forward to a whole heap of rock fights.

Poll

How would you feel about a 7-5 season in 2019?

This poll is closed

  • 0%
    FIRE EVERYONE
    (1 vote)
  • 5%
    Very dissatisfied
    (13 votes)
  • 14%
    Dissatisfied
    (35 votes)
  • 28%
    Mildly dissatisfied
    (70 votes)
  • 8%
    Indifferent
    (20 votes)
  • 26%
    Mildly satisfied
    (66 votes)
  • 14%
    Satisfied
    (35 votes)
  • 2%
    Very satisfied
    (6 votes)
  • 1%
    CONTRACT EXTENSIONS FOR EVERYONE
    (4 votes)
250 votes total Vote Now