A statistical, game-by-game analysis of the Gophers Football schedule

Hollinsanity

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Earlier this week I put together an objective analysis of the Gophers schedule using two statistical models and some Vegas spreads. Objectivity on Gopherhole?! Unheard of, I know.

I emailed The Daily Gopher and 247, but they wanted nothing to do with me so I'm stuck sharing with my Gopherhole family I guess... :D :clap:

The short version: the Gophers are much more likely to win 5 - 6 games than 9. Read below to find out why.

Quick note: Gopherhole formatting is hit or miss. If it is formatted cleanly within please read below, but if not here is a link to a cleanly formatted version with full-size images usable on both mobile and desktop.


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Unlike many new coaches, PJ Fleck is not coming into his new position as Head Coach with an empty cabinet, as the Gophers return most of their starters from a 9-4 team last year. However, determining what to expect from a record standpoint this year is difficult, especially given a new system will be in put in place and a new Quarterback will be learning on the job.

In the analysis below I take a look at the Gophers football schedule on a game-by-game basis based on two respected college football computer models and already-released game spreads.


The inputs:

People often roll their eyes at or ignore statistics-based approaches, but their accuracy can be validated using historical game-by-game results. For this analysis I used two respected, predictive football models: Bill Connely's S&P and ESPN's Football Power Index (FPI).

Bill Connelly has written an excellent preview of the Gophers 2017 season, and his win probabilities are included at the bottom. ESPN's FPI win probabilities can be found here. I have summarized them below for quick reference:

img1.jpg
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Further, Vegas spreads can be helpful in analyzing and setting preseason expectations. If a certain spread is "off" by more than a few points sharp bettors will put forward large bets until the spread shifts, thus becoming accurate. As of now spreads have been set for eight games this year.

Specific game spreads (via 5Dimes):

vs. Buffalo: - 26.5 (26.5 point favorite)
vs. Maryland: -10.5
@ Purdue: -11
vs. Michigan State: -4
vs. Illinois: -13.5
@ Iowa: +3
@ Northwestern: +5.5
vs. Wisconsin: +10

Based on the outcome of 17,000 games over multiple decades, spreads can be directly correlated to win probabilities. For example, six-point favorites win 66% of the time. Using the eight available spreads above I included the following win probabilities in my analysis, assuming that if the spreads were off by too much it would have adjusted already.

img2.jpg


The method:

Given the concepts outlined above, I took game-by-game win probabilities from Bill Connelly's S&P and ESPN's FPI and combined those win probabilities with Vegas spreads to analyze the likelihood of various season-long outcomes.

Specifically, I calculated an "Average Win Probability" for each game by averaging each game's win probability per ESPN's FPI, per Bill Connelly's S&P and per the spread (if available). The results of this are shown in the image below:

img3.jpg

Using the Average Win Probability for each individual game I then calculated the likelihood of each season-long win/loss record. (Note: I can expand upon this if you would like me to, and if you are curious take a look at the spreadsheet linked to the bottom of this email.)


The results:

Likelihood of 6 - 6 or better:72.1%
Likelihood of 7 - 5 or better:46.7%
Likelihood of 8 - 4 or better:22.4%
Likelihood of 9 - 3 or better:7.4%


img5.jpg

I then used the same approach to analyze the Big Ten portion of the schedule separately.

Likelihood of 4 - 5 or better:72.1%
Likelihood of 5 - 4 or better:46.7%
Likelihood of 6 - 3 or better:17.67%
Likelihood of 7 - 2 or better:4.43%


img7.jpg


The takeaway:

To me the schedule can be broken down into three groups: should-be wins, toss ups and likely losses.

Should-be wins:

Buffalo, vs. Middle Tennessee, vs. Maryland, at Purdue, vs. Illinois.

Toss ups:

At Oregon State, vs. Michigan State, at Iowa, vs. Nebraska, at Northwestern.

Likely losses:

At Michigan, vs. Wisconsin.

Whether this season can be labeled as a success will likely come down to the "toss up" games. For me, Big Ten play takes precedence over non-conference games, so the most important games on the schedule are Michigan State (projected to be down this year), Iowa and Nebraska.

Switch those three games to wins in the model and the Gophers likelihood of winning eight or more games jumps from 22% to 64%. And the likelihood of nine wins or more jumps from 7% to 33%.

Win two or three of the games and the Gophers should be competing for a Big Ten West title as they enter the final two games, at Northwestern and vs. Wisconsin.

However, with losses at Iowa and vs. Nebraska the Gophers will quickly find themselves out of contention and instead competing for bowl eligibility.



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Spreadsheet with calculations: https://docs.google.com/spreadsheets/d/1pkeQnsbDFS6tYhjvm86di1BxXtwfiPy3Yxc-a3lhv-E/edit?usp=sharing

And here's the link with clean formatting and full-size images once again for those inclined.
 

Good work. Your predictions are in line with most national publications. The good thing is that the models predict at least a "fair" year. You show the chance of finishing with a losing regular season record as only about 28%. The chance of finishing with 7 wins or more is almost 50%. I'll be reasonably satisfied with 7 wins given its the first year of a new coach and the roster has big question marks in some areas.
 

Nebraska is a toss up, I guess that makes sense but I never think of them as that.

Good read.
 

Validated your results using coin-flip, looks good to me.
0 0.00% 100.00% 0 wins
34 0.03% 100.00% 1 win
346 0.35% 99.96600% 2 wins
2167 2.17% 99.62000% 3 wins
7901 7.90% 97.45300% 4 wins
17642 17.64% 89.55200% 5 wins
25368 25.37% 71.91000% 6 wins
24493 24.49% 46.54200% 7 wins
14892 14.89% 22.04900% 8 wins
5668 5.67% 7.15700% 9 wins
1306 1.31% 1.48900% 10 wins
174 0.17% 0.18300% 11 wins
9 0.01% 0.00900% 12 wins
 

This is excellent and interesting work. This is the kind of preseason fodder I appreciate, as opposed to meaningless chatter from national publications that couldn't name 3 starters if they didn't have a computer in front of them.

I'd be curious for you to re-run this without the ESPN FPI which seems to take an awfully harsh view of the Gophers in comparison to both Connely and Vegas. On that note, do you have any information as to which of the 3 is most historically accurate? Do each of them add some value in a regression equation, or is one simply redundant?
 


Well done and thanks for putting this together.

In my opinion Oregon State is a should-be win. Especially with their QB just transferring. (Just announced)
 


I think we win 8. I'm counting on the 5 should wins, Oregon State will be much more vulnerable early, especially if Durr is back to strengten the secondary, MSU has a lot of holes to fill and we play them early, so 7 wins there. I also think that we'll win one of Northwestern, Nebraska, and Iowa. Everything is fluid preseason a recalculation after the first two games would be interesting.
 

Interesting, thanks for the work on this...wondering what the same analysis would output based on last year's schedule.
 




I think we win 8. I'm counting on the 5 should wins, Oregon State will be much more vulnerable early, especially if Durr is back to strengten the secondary, MSU has a lot of holes to fill and we play them early, so 7 wins there. I also think that we'll win one of Northwestern, Nebraska, and Iowa. Everything is fluid preseason a recalculation after the first two games would be interesting.

I didn't mention it in the article because I focused on the Big Ten games, but the chances of winning 8+ games jump from 22% to 36% with a win at Oregon State in Week 2.

This big jump occurs because the calculation assumes we have a 38% chance of winning, so changing that game to a win is obviously a significant change.
 

Also, I didn't mention in the original post because it got long quickly, but anyone can run their own scenarios/percentages in the Google Spreadsheet I compiled.

1) Go to one of the tabs named "OPEN"
2) Edit the orange cells with what you think the win probability for each game is. If you think we are going to win a certain game enter "100%" or "1"

--> The table below within the sheet you are editing will automatically update.

https://docs.google.com/spreadsheets/d/1pkeQnsbDFS6tYhjvm86di1BxXtwfiPy3Yxc-a3lhv-E


Sent from my iPhone using Tapatalk
 

As we go through the season you should run the analysis again after each game. Would be interesting to see how it changes.
 




Excellent job Hollinsanity. This is a big reason why my expectations are around 6 wins this season.
 




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