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2015 Cal Football Season Predictions: 7 Wins!

We've gathered the results from our final round of season predictions and the future looks bright!

David Banks/Getty Images

For several weeks at CGB we've been gathering and analyzing all sorts of predictions.  As much as I enjoy working with the data from these predictions, I'm glad it's come to an end.  Because for the first time since November of last year, we can watch real, live Cal football in real, meaningful games.  It's been a long nine months and the end is nearly upon us.  Before we the Bears take the field, let's see how the team may perform this season.

Two weeks ago I asked you all to estimate how likely Cal is to defeat each opponent on the schedule.  Many thanks to the 250+ of you who participated.  You provided plenty of data points and today we'll see what wisdom we can extract from them.

In the table below I've listed each opponent, the average prediction that Cal will defeat that opponent, and the standard deviation of those predictions.  In parentheses next to each average I show how much the prediction has changed compared to our spring predictions.  In case you've suppressed all memories of spending time in Evans Hall, the standard deviation reflects the amount of variation in our predictions.  We usually see standard deviations around 15 for most games.  For games with lower standard deviations, we're more certain about Cal's chances.  Likewise, we're less certain about Cal's chances in games with larger standard deviations.

Opponent Avg. Win Probability Standard Deviation
Grambling State 96.95% (+0.25) 4.78
San Diego State 83.80% (-1.40) 11.22
@ Texas 53.61% (+1.41) 15.88
@ Washington 61.13% (+3.03) 15.32
Washington State 75.74% (-0.16) 12.92
@ Utah 47.38% (+0.48) 15.02
@ UCLA 41.58% (-0.92) 16.31
USC 36.79% (-0.21) 18.38
@ Oregon 26.57% (+0.17) 15.51
Oregon State 74.95% (+3.45) 13.83
@ LSJU 56.12% (-1.38) 22.04
ASU 49.88% (-3.82) 15.68
Total 7.04 wins (+0.00) 1.26

Typically when we do the preseason predictions, we see a slight increase in total wins compared to the spring predictions.  This year the win total was identical to our spring predictions.  Why aren't we pumping more sunshine heading into this season?  Have decades of lousy Cal football finally turned us into emotionless automatons?

The schedule is clearly backloaded, as we favor the Bears in the first five games but only two of the final seven games.  In a critical year for Dykes' future at Cal, a four-game losing streak in the middle of the season could be tough for the fanbase to swallow.  We're not big underdogs in any game except Oregon, so a morale-boosting upset could occur in any of our tougher games.  With 7 predicted wins, we have some margin of error in our quest for a bowl game.  A win over Texas would be critical for achieving that bowl game.

In the following tables I listed our chances of winning on the x-axis and the number of respondents on the y-axis.  I have color-coded the plots by opponent.  The primary purpose of this plot is to show the distribution of predictions for each opponent.  First, the home games.


Grambling is clearly our likeliest win of the home games.  The San Diego State game is slightly tougher, and we have a strong advantage over Oregon State and Washington State, both of which should finish near the bottom of the conference this season.  The Arizona State is a toss-up while we are a clear underdog against USC.  It's a good thing we have a record-breaking QB leading one of the nation's most exciting offenses this season, because these opponents do not make for a very exciting home schedule this year.


Other than the Washington game, these all range between toss-up and probable loss.  To earn a bowl berth, we'll need to get at least two road wins.  Washington is our likeliest win. With this many toss-up games, a bit of luck could give us four road wins.  That would put us in a great position to get eight or nine wins this season.


Next I took the predictions from each game and used them to simulate the entire season. The simulation process is pretty simple. I select one prediction at random for Grambling State and use that to predict the winner. If I draw a .95, then the Bears will have a 95% chance of drawing a win.  Based on that percentage, I then draw either a win or a loss for the Bears, move on to the next game, and repeat the process. I did this for each of the 12 games to simulate the season and re-ran the process 1,000,000 times.  And my computer didn't complain once--what a trooper!

I have plotted the results below. On the x-axis we have the number of wins and the y-axis is the probability (per our predictions) of finishing with that number of wins.


In case you prefer tables to plots (you monster), I've listed the numbers from the above plot in the table below.

Wins Probability
0 0.00%
1 0.00%
2 0.13%
3 0.94%
4 3.98%
5 10.98%
6 20.04%
7 25.14%
8 21.26%
9 12.09%
10 4.40%
11 0.93%
12 0.08%

Of course, 7 wins is the likeliest outcome.  8 wins is the next most likely outcome, followed by 6 wins.  Based on our predictions, we have an 85% chance of achieving a bowl game this season.  And we have a 5% chance of earning a double-digit win total!


We have no Editor's Choice Award this time.  I am very disappointed in all of you.

Instead we begin by recognizing those with Rose Bowltinted glasses.

Sonny Delight

Name Wins
1. Herzon_Alfaro (AzusaCA91702) 12.00
2. Fiat Lux 11.93
3. Maxdarkfire 10.65
4. Ghost of Joe Roth 10.50
5. Old Bear 71 10.20
5. Oski Disciple 10.20
7. So Cal Bear 23 10.00
8. VermontBear 9.60
9. Norton1982 9.50
10. Mad Dawg 9.20

Only one of you gave us a 100% chance of winning every single game?!  Blessed be Herzon_Alfaro.  You all could learn a thing or two from him.  Clearly Fiat Lux showed great reservation in only predicting 11.93 wins.  Maxdarkfire rounds out the top three.

At the opposite end of the spectrum we have the doomsayers who envision a grim future for the Bears.

Sonny Yikes!

Name Wins
1. GoBears07 3.49
2. miltybear 3.56
3. Auricursine 4.35
4. puresilence 4.36
5. Momzer 4.57
6. billy 4.60
7. Wyfind 4.65
8. CalBearSF 4.70
9. EECS_Bear 4.75
10. Cal dud 4.90

Two of you predicted fewer than 4 wins?!  The season kicks off in five days--I don't have time for this pessimism!

The Voice of Reason

Our final award recognizes those whose predictions were closest to the community average.  Congratulations on being so reasonable in these times of anticipation and sunshine pumping.

Name Standard Deviation
1. bearroids .046
2. RenoBear88 .047
3. 34f34f .049
4. joltimpact .051
5. 123456 .052
6. brooklyn_bear .054
7. forgot my sb user name .057
8. GhostOfScutaro .057
9. Mbbear .057
10. SuperEQ .058

Fearless Leaders

Finally, we highlight the predictions from your motley crew of CGB writers and mods.

atomsareenough 0.99 0.8 0.6 0.7 0.75 0.4 0.5 0.4 0.3 0.8 0.5 0.4 7.14
Sam Fielder 0.99 0.9 0.65 0.65 0.75 0.45 0.35 0.45 0.15 0.7 0.5 0.35 6.89
Berkelium97 0.999 0.85 0.5 0.55 0.75 0.45 0.4 0.3 0.15 0.75 0.45 0.35 6.499
Leland Wong 0.9 0.75 0.6 0.7 0.65 0.4 0.35 0.2 0.2 0.85 0.5 0.37 6.47
Nick Kranz 1 0.85 0.4 0.6 0.7 0.4 0.3 0.35 0.15 0.8 0.45 0.45 6.45

atoms is the most optimistic while Nick is the least optimistic.  Leland, Nick, and I are all on the same page, as our predictions are within .05 wins.  Go us!

Thanks again for participating!  We appreciate your participation, as it gives us something to write about during this long, long offseason.  Fortunately that offseason comes to an end this Saturday and we can all get back to writing about football again!