How often Jim Harbaugh’s 4th down decisions agree with analytics

This is a guest post from Tony Kaminski, a recent University of Michigan graduate and engineer. You can follow him on Twitter or check out his site Big House Analytics.

How does Jim Harbaugh’s fourth down decisions stack up to analytics?

The numbers say that coaches should go for it on fourth down way more than they do. Berkeley professor David Romer started this research back in 2006, and Brian Burke, now with ESPN, has performed the most complete study based on NFL data.

My interest in this topic as a Michigan fan began with a conversation with Craig Ross, a member of WTKA MGoBlog Roundtable and author of two books on Michigan sports. In his book The Search for the Unified Field Theory (Football Version), he writes

So here’s the deal. Einstein’s follies aside, I believe there is a unified field theory in football, a fundamental set of ideas or equations that can help to explain “what happened” in a football game, why the game was won or lost. More than this, I think this theory allows a coach to make choices and structure his team and program in a way that squeezes out a few more wins than might otherwise be the case.

And therein lies our aim: finding this unified theory. Craig and others have good reason to believe that not punting very much, or at least substantially less than coaches tend to do currently, is a part of applying this theory to winning more games.

The natural starting point of this conversation is the work of David Romer, the Berkeley economist. An excerpt from a New York Times profile of Romer explains the motivation looking at 4th downs:

Romer, a lifelong sports fan who is a professor at the University of California, Berkeley, came up with the idea to rigorously examine fourth-down plays after listening to a radio broadcast of an Oakland Raiders game in his car about a decade ago. Although the Raiders had the ball in striking distance of the end zone, one of the commentators remarked that they would be smarter to kick a near-certain field goal rather risk going for a touchdown.

“I am pretty analytic,” Romer recalled telling himself. “That is a pretty shallow way of thinking about it.”

So, after stewing over the idea for a couple of years, he set out to tackle the great fourth-down debate.

Romer’s work has been largely met with skepticism in coaching circles because the difficulty in overcoming conventional wisdom. Coaches at big-time universities or professional franchises with nine-figure payrolls often stick to the proverbial book — and why not?

If you fail underneath the brightest lights, it’s easier to defend yourself when your decisions echo the conventional wisdom. Wins come at a premium, and no career has less job security or more turnover than football coach. So you do everything you can to hold onto that gig, because they don’t come around often.

But doing great things, in the private sector or on the football field, involves bucking convention. Romer has shown this means punting less. Way less.

You can read this article for a quick tutorial on Romer’s work and its application. While the New York Times model doesn’t explicitly reference the professor, their “4th Down Bot” comes to a very similar conclusion, just with more data to back it up. It boils down to this:

Especially near the middle of the field, coaches need to be more aggressive. In this article, we’ll look at Jim Harbaugh’s fourth down decisions since his arrival at Michigan. A few points on this analysis.

  • While Romer and the New York Times used NFL data, Romer believes the findings also apply to the college game. (Craig recounts an email conversation that him and the professor had in his book where Romer explains why.)
  • Bill Connelly’s S&P has designated garbage time as being up by 25 points or more in the second quarter, 22 or more in the third, or 17 or more in the fourth. For the 2015 analysis, I filtered this out arbitrarily, in a more liberal manner than Bill does, based on my recollections of the individual games. In 2016, I followed Connelly’s rules.
  • This is not an indictment of Harbaugh’s decision making on fourth down, merely an analysis of how closely his decisions echo Romer’s advice. There are specific team, opponent, or situation-variant times where it would be best to not follow the chart above.
  • This data does not reflect the final outcome of the decision made but only the decision to go for a fourth-down conversion or punt itself.

Let’s first look at Harbaugh’s 2015 fourth down decisions in these tables. The color green designates a decision that follows what analytics recommends. Yellow means it did not but was defensible given the score, situation, or general trend of the game (more on that later). Red designates a time when Harbaugh probably should have gone for it on fourth down opposed to punting.

Let’s discuss a few of the decisions marked yellow, or ones I found defensible given the game situation. (Maybe I was a bit too friendly to our coach, I’m a fan and proud alum, after all — leave a comment if you disagree with any of my designations, and we’ll continue the conversation).

For instance, Michigan punts on fourth and seven from the Michigan State 38 with 1:12 to go in the first half of a 10-7 game. That’s not technically the correct decision but consider the following:

  • Michigan State is out of timeouts
  • Michigan had allowed exactly seven points over the prior 17 quarters
  • Michigan had one of the best punters in college football in 2015

Michigan State runs three quick plays without scoring before halftime.

Against Northwestern, it’s fourth and nine from their 34 with 4:19 to go in the second quarter. Michigan has a 21-0 lead. The chart says to try a field goal but that’s too deep for then-freshman kicker Kenny Allen, who had missed a 44-yard attempt earlier in the season. Michigan punts, and then Jourdan Lewis houses an interception on the ensuing possession that erases any doubt about the outcome.

This isn’t to say I agree with all of the times Harbaugh deviated from the research. I was upset by the decision to punt from Ohio State’s 36 on fourth and five less than five minutes into that game. Given the talent discrepancy between the Wolverines and Buckeyes, who littered the first round of the NFL draft (literally, probably), points would be at a premium, and we passed up an opportunity to get some early.

Ultimately, Harbaugh had a 77.8% “success rate” — out of Michigan’s 54 fourth down decisions, Harbaugh went with analytics or I found the punt defensible on 42 of them. If you want to go by the book (meaning the punts I deemed as defensible but not Romer-approved counting against our success rate instead of for it), our score is 59.3% (32 of 54).

The following table shows my results for the 2016 season through the Ohio State game.

On the following fourth downs, Harbaugh went for the first down.

This analysis shows a 91.3% success rate (42 of 46). The results were so staggering that I had to have a friend double check my work. If you went purely by the numbers, our success rate is 76.0% (35 of 46) . By either metric, this is a substantial improvement from last season.

A couple notes:

  • Michigan blew out seven of their 12 regular-season opponents, so this chart was significantly easier to compile than last year’s.
  • I did not chart the “defeat with dignity” portion of the Michigan State game, the final offensive play against Indiana (it was a full-blown blizzard in Ann Arbor at that point and IU had effectively conceded), or the fourth-down attempt in overtime against Ohio State since we obviously didn’t have a choice.
  • There were only four punts I gave the “red” designation, and even then, I felt that I may have been being unreasonably harsh on Harbaugh, since these were coming up correct at a much higher clip than last season.
  • Michigan was 12 for 18 on fourth-down conversion attempts in 2016 compared to six for 16 in 2015. More of these came in garbage time this year than last, hence the disparity in charted attempts.

Harbaugh’s decision making already agreed with analytics a good bit in 2015, but 2016 represents an even bigger step forward. I have a few hypotheses on why.

First, Michigan has a larger analytics team than under previous regimes. It’s not hard to believe that they had a part in this trend.

Second, Harbaugh had a different situation on defense these two years. In 2015, the defensive production fell off with the injury of Ryan Glasgow, most notably when Indiana gashed Michigan for 307 rushing yards in Bloomington and the dreadful Ohio State game.

This was not the case in 2016. Don Brown’s defense was stout all season long, which gave Harbaugh the confidence the defense could get a stop on a short field.

Podcast: College football championship week, Atlanta Falcons and Washington Redskins

thefootballanalyticsshow_cover_landscapeCollege football is getting real, folks. In this week’s podcast, I discuss the scenarios for all the top teams.

Ohio State isn’t a lock. There just aren’t any locks in sports, although it is highly likely the Buckeyes make the playoff.

Michigan isn’t dead. But they do need help, and maybe more than you think.

Then I transition to the NFL to discuss the Atlanta Falcons, the surprising top team in my member NFL rankings. We shall see how long they last there.

Last but not least, I look at the Washington Redskins and their potent offense. They have an interesting game at Arizona this week.

To listen to the podcast, click on the play button.

To listen on iTunes, click here.

Podcast: Michigan at Ohio State

thefootballanalyticsshow_cover_landscapeThis week, I focus on Michigan at Ohio State, a critical game in the college football playoff picture. After looking at all the numbers, the game boils down to which team can run the ball, because both teams will find it extremely difficult to throw.

I end with a prediction for Michigan at Ohio State, and then jump into college football upset alert. You might laugh at one of the picks, but hey, I’m here to entertain.

I end with a college football total that just might make one of our picks in the prediction service.

To listen to the podcast on iTunes, click here.

To listen here, click on the play button.

Warning: Don’t think Michigan should be too big a favorite over Michigan State

harbaugh_streetsMichigan travels to Michigan State this weekend in a game with two program headed in opposite directions.

Michigan has blossomed in Jim Harbargh’s second year as coach. The defense has excelled as the Wolverines have dominated every game except Colorado and Wisconsin.

In contrast, Michigan State started the year 12th in the AP Poll but have lost their last 5 games. It’s not a surprise the offense has declined with the departure of key talent from last year. But the drop off on defense led by Malik McDowell has been a shock.

So what will happen on Saturday in East Lansing? As of Tuesday afternoon, the markets favor Michigan by 23 point.

This point spread is too large. Let me explain.

The curse of small sample size

Some type of analytics give a spread even larger than 23.

For example, consider my rankings algorithm that takes margin of victory and adjusts for strength of schedule. Using only games from this season, this method makes Michigan 32 points better than Michigan State. With home field for the Spartans, this gives a predicted point spread of 29 points.

However, this prediction considers only 7 or 8 games for each team, and it’s dangerous to draw conclusions based on small sample size. In addition, randomness can affect the margin of victory through plays like turnovers, as Michigan State has a -4 turnover margin this season.

To get a better assessment of the right point spread for this game, let’s consult other sources of data.

Adjusted Yards Per Play

At The Power Rank, I also rank teams based on yards per play, a powerful efficiency metric that captures the ability of the offense to move the ball and the defense to prevent this movement. The same ranking algorithm takes data from each game and adjusts for strength of schedule.

By adjusted yards per play, Michigan State ranks 38th in the nation. While not stellar, the Spartans look much better by yards per play than adjusted margin of victory (90th).

To explain the discrepancy between yards per play and margin of victory, we consult Bill Connelly’s data on finishing drives. By points per trip inside the 40, Michigan State ranks 94th and 89th on offense and defense respectively.

The Spartans haven’t been clutch this season. However, this could change any week, as an offense ranked 34th in adjusted yards per play will almost certainly finish drives better than they have so far this season. And the defense overall should be better than their rank of 62nd by adjusted yards per play.

Michigan is 5th in team rankings based on adjusted yards per play, and this suggests they should be favored by about 10 points.

Market rankings

The betting markets provide another way to evaluate teams. This year, I started applying my ranking algorithm to closing point spreads in the markets to rank teams. Just like with the team rankings, each team gets a rating that gives an expected margin of victory against an average FBS team on a neutral site.

In these market rankings, I weight recent games much more than games earlier this season. For example, the spreads in week 1 get only 3% of the weight of this past week’s games.

This bias should favor Michigan, as they have improved from preseason expectations. In addition, they got an extra bump last week as a 40 point favorite against an Illinois team starting their 3rd quarterback.

The weight towards more recent games should also hurt Michigan State, as the markets have adjusted to their decline. The Spartans would have been more than a 3 point favorite at Maryland last week if the game had been earlier this season.

However, the market rankings predict a 9.5 point win for Michigan at Michigan State.

Ensemble Prediction

Members of The Power Rank have access to ensemble predictions that combine the factors discussed here with other calculations. These predictions have gone 53.7% (217-187 with 8 pushes) against the closing spread this year.

My member prediction has Michigan by 10.7 points over Michigan State. That seems low to me based on the play I’ve seen from both teams this year, and I could see Michigan covering more than 20 points.

However, if you think Michigan will one hundred percent dominate this game, don’t underestimate the randomness of college football.

Michigan State might play above their true talent in this game, as Mark Dantonio hasn’t suddenly become a terrible football coach the last 8 weeks. Throw in an ill timed turnover from Michigan, and it could be a close game on Saturday.

The Ultimate Guide to College Football Conference Win Probabilities

Will your college football team win a conference title in 2016? Which teams will win the Power 5 conferences, giving them the inside track towards a College Football Playoff berth?

Unlike the typical college football publication, I won’t pick a single team to win each conference. Every team has some chance to win, even Kansas, and modern sports analytics can assign each team a conference win probability.

These numbers come from my preseason college football model, which considers team performance over the past four years, turnovers and returning starters to rank all 128 FBS teams. This model predicted the winner in 73.3% of games last season, a win rate that only includes games with two FBS teams.

This preseason model gives a win probability for each game this season, and these numbers drive my win total predictions at The Power Rank.

These win probabilities also provide the parameters for simulating each conference 10,000 times with random numbers. Each simulation determines the division winners through tiebreakers, and then flips another coin to determine the outcome of the championship game. These simulations give the win probabilities below, which I compare with the market odds from Bovada.

Let’s look at the numbers and story lines for each Power 5 conference.

SEC

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Is Tennessee the new beast in the SEC East?

Despite 4 losses last season, Tennessee played close games with Alabama and Oklahoma and never lost by more than a touchdown. The Vols finished last season 8th in my team rankings, which take margin of victory in games and adjusts for strength of schedule.

This season, Tennessee should fully see the fruits of strong classes Butch Jones recruited in 2014 and 2015. My preseason model ranks the Vols 7th and gives them a 44.8% chance to win the East despite a difficult cross division game with Alabama.

Tennessee’s strong chances to win the East reflect poorly on the other programs in the division.

  • Georgia hired a coach (Kirby Smart) who has never been a head coach.
  • Florida looked on the rise last season under Jim McElwain before getting demoralized by Florida State, Alabama and Michigan to end the season.
  • Steve Spurrier left South Carolina mid-season, and the Gamecocks replaced him with Will Muschamp, who never got the job done in four years at Florida.
  • Missouri won the SEC East in 2013 and 2014 but appear in rebuilding mode after the retirement of Gary Pinkel.

My model doesn’t like the prospects of these usual contenders for the SEC East crown, which enhances the odds for Tennessee. The story changes if Tennessee played in the SEC West.

My numbers rank Ole Miss right behind Tennessee at 8th in the nation. However, with Alabama (#1) and LSU (#3) ahead of them, Ole Miss has a 8.7% chance to win the division.

The lack of power balance also favors Tennessee in the overall conference odds. My preseason model would make LSU a 2.5 point favorite over Tennessee in the SEC title game. However, because they play in a weaker division, Tennessee has a better probability of winning the SEC than LSU.

SEC East

Tennessee (#7) has a 44.8% chance to win.
Georgia (#16) has a 28.4% chance to win.
Florida (#28) has a 12.2% chance to win.
South Carolina (#34) has a 8.0% chance to win.
Vanderbilt (#44) has a 4.0% chance to win.
Missouri (#52) has a 2.2% chance to win.
Kentucky (#83) has a 0.3% chance to win.

SEC West

Alabama (#1) has a 45.1% chance to win.
LSU (#3) has a 27.7% chance to win.
Mississippi (#8) has a 8.7% chance to win.
Arkansas (#12) has a 8.3% chance to win.
Texas A&M (#10) has a 5.6% chance to win.
Mississippi State (#23) has a 3.5% chance to win.
Auburn (#32) has a 1.1% chance to win.

Big Ten

bigten

A year ago, Ohio State was the toast of college football. Urban Meyer’s team had won the first playoff, and he was killing it as usual on the recruiting trail.

Then in the most inexplicable game of 2015, Ohio State lost to Michigan State, a team without star QB Connor Cook. The loss cost the Buckeyes a spot in the playoff, and they lost 10 players to the first 3 rounds of the NFL draft.

In contrast, Michigan had many unanswered questions a year ago. They went 5-7 the previous season, and their hopes for 2015 rested on their faith in new coach Jim Harbaugh.

Michigan had a few rough spots in 2015, including a demoralizing 42-13 home loss to Ohio State. However, they finished 10-3 after a convincing win over Florida in a bowl game, and Harbaugh landed a top 5 recruiting class in February.

How do Ohio State and Michigan compare in 2016?

My numbers imply a dead heat between Ohio State and Michigan in 2016. Michigan (#9) is ranked ahead of Ohio State (#11) but would be a 2.5 point underdog when they travel to Columbus in November.

However, Michigan does have a better chance to win the Big Ten East (37.8% vs 34.9% for Ohio State) due to an kinder cross division schedule. Both teams play Wisconsin, but Michigan gets Iowa (#36) and Illinois (#88) while Ohio State tangles with Nebraska (#25) and Northwestern (#58).

In the Big Ten West, it might seem strange to that Nebraska has the highest conference win probability. However, the Huskers went 1-5 in games decided by a touchdown or less, which included a loss to BYU on a Hail Mary. A turnover margin of -12 didn’t help either.

Luckily for Nebraska, my research shows that their record in close games and turnover margin most likely improve in 2016. QB Tommy Armstrong returns, and Nebraska could be really good if they can fix their porous pass defense.

However, the real reason Nebraska has the highest odds to win the Big Ten West is Wisconsin’s schedule. After two years of playing Rutgers and Maryland in cross division games, the Badgers get Ohio State, Michigan and Michigan State. Nebraska also plays Ohio State but gets Indiana and Maryland. Advantage Nebraska.

And I guess we should discuss defending Big Ten West champion Iowa. The Hawkeyes had a magical season last year, but quickly regressed in the Rose Bowl against Stanford. My numbers give them a 19.3% chance to win the division, much less than the even odds in the markets.

Big Ten East

Michigan (#9) has a 37.8% chance to win.
Ohio State (#11) has a 34.9% chance to win.
Michigan State (#29) has a 19.0% chance to win.
Penn State (#43) has a 5.7% chance to win.
Indiana (#67) has a 1.4% chance to win.
Maryland (#78) has a 0.7% chance to win.
Rutgers (#84) has a 0.5% chance to win.

Big Ten West

Nebraska (#25) has a 34.2% chance to win.
Wisconsin (#22) has a 31.1% chance to win.
Iowa (#36) has a 19.3% chance to win.
Minnesota (#60) has a 7.7% chance to win.
Northwestern (#58) has a 4.8% chance to win.
Purdue (#76) has a 2.5% chance to win.
Illinois (#88) has a 0.5% chance to win.

Pac-12

pac

My numbers understand some of the hype surrounding the Washington Huskies. They return 15 starters from last season, including 7 players on a defense that ranked 9th by my adjusted yards per play.

The subjective adjustments also seem to favor Washington, as QB Jake Browning returns as a sophomore after a promising freshman season. Coach Chris Petersen enters his third year and might find the same success he had at Boise State.

But it’s pure insanity to make Washington the Pac-12 favorite, as the markets have them in early August.

While Washington showed promise last season, they finished 7-6 and 31st in my team rankings that take margin of victory and adjust for schedule. Not exactly playoff material.

Last season, Washington had one signature win, a 17-12 win at USC. However, it almost doesn’t count, as USC coach Steve Sarkesian got fired the next week and possibly wasn’t sober while preparing for the Huskies.

Washington has yet to prove itself on the field, which makes it difficult to think they’ll win the Pac-12 North over proven teams.

  • Stanford has to replace their QB and fill holes on both lines, but they still have this guy named Christian McCaffrey.
  • Even though they’re replacing the quarterback, Oregon has most of its weapons back on offense. And the defense can’t get worse, can it?

My numbers like Stanford (35.8%) and Oregon (21.4%) over Washington (10.1%) to win the Pac-12 North.

In the Pac-12 South, the odds makers might be overlooking Utah. It’s not just that Kyle Whittingham has the Utes back on the rise with stellar play on defense. It’s the schedule.

When the Pac-12 split into two divisions, UCLA and USC wanted to keep their rivalries with Stanford and California. However, this has implied a more difficult schedule for all four of these teams.

USC gets the worst of it this season, as they not only play their two northern California rivals but also Oregon. The Trojans always have talent. However, Clay Helton went an uninspiring 5-4 as interim head coach last season, so there’s reason to doubt his ability to get this talent to play at a championship level.

UCLA catches a break in getting Oregon State as their third cross division game. In addition, I think my numbers underestimate Jim Mora’s team this year. My preseason rankings are based on their team rank of 41st last season, but this seems inconsistent with an offense and defense that ranked 27th and 14th last season by my adjusted yards per play.

My numbers make Utah the favorite in the Pac-12 South because they play Oregon State, California and Oregon in cross division games. If the offense can get better with new personnel, Utah could become a legitimate Pac-12 contender.

Pac-12 North

Stanford (#6) has a 55.1% chance to win.
Oregon (#18) has a 21.4% chance to win.
Washington State (#30) has a 11.8% chance to win.
Washington (#26) has a 10.1% chance to win.
California (#56) has a 1.5% chance to win.
Oregon State (#87) has a 0.1% chance to win.

Pac-12 South

Utah (#24) has a 35.8% chance to win.
USC (#19) has a 29.9% chance to win.
UCLA (#37) has a 15.9% chance to win.
Arizona (#38) has a 12.3% chance to win.
Arizona State (#53) has a 4.9% chance to win.
Colorado (#77) has a 1.3% chance to win.

ACC

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It seems like Clemson should win the ACC over Florida State in 2016.

Clemson beat Florida State on their way to the national title game against Alabama. Despite the 5 point loss against Bama, you could argue Clemson should have won. They dominated the line of scrimmage but couldn’t overcome blown coverages in the secondary.

However, my preseason ranking like Florida State, as the Seminoles rank 2nd over Clemson at 5th. The returning starters variable plays a critical role in this rank.

Florida State has 17 returning starters, which includes star running back Dalvin Cook. In contrast, Clemson returns only 12 starters. The Tigers also had heavy attrition in the secondary, including 3 players that got drafted by the NFL.

In addition, while Clemson beat Florida State by 10 last year, it was a closer game than the final score indicated. Florida State had more yards per play than Clemson. The Seminoles couldn’t overcome a 2 for 12 rate in converting third downs.

However, Clemson might have the trump card. They bring back Deshaun Watson, the best quarterback in the nation. Florida State is still deciding between returning starter Sean McGuire at QB or a few younger players.

In the Coastal division, the markets have the same odds for Miami as for defending champion North Carolina. This shows major respect for new Hurricane coach Mark Richt, who won 145 games in 15 season at Georgia.

My numbers, which do not consider the coaching change, give Miami the fourth largest win probability for the Coastal division.

ACC Atlantic

Florida State (#2) has a 53.3% chance to win.
Clemson (#4) has a 31.3% chance to win.
Louisville (#14) has a 13.9% chance to win.
Boston College (#55) has a 0.6% chance to win.
North Carolina State (#59) has a 0.4% chance to win.
Syracuse (#64) has a 0.4% chance to win.
Wake Forest (#73) has a 0.2% chance to win.

ACC Coastal

North Carolina (#20) has a 37.3% chance to win.
Virginia Tech (#31) has a 25.0% chance to win.
Pittsburgh (#33) has a 16.4% chance to win.
Miami (FL) (#40) has a 10.2% chance to win.
Georgia Tech (#47) has a 6.7% chance to win.
Duke (#75) has a 2.3% chance to win.
Virginia (#72) has a 2.1% chance to win.

Big 12

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Can any team topple Oklahoma from the top of the Big 12?

Bob Stoops has had consistent success as coach at Oklahoma. Only once in his 17 years have the Sooners finished the season outside the top 25 in my team rankings (2005).

Stoops has had his bad years. In 2014, Oklahoma went 1-3 in games decided by a touchdown or less and had an 8-5 record. However, despite an embarrassing bowl loss to Clemson, they still finished 15th in my team rankings.

My preseason model that looks over the past four years appreciates this type of consistency, and it ranks Oklahoma 5th. They could slip like they did in 2014. But with QB Baker Mayfield back, don’t count on it.

The Big 12 win probabilities do not consider the departure of Baylor coach Art Briles. There should be some type of adjustment downward for the Bears. They have one starter returning on both the offense and defensive lines, which suggests they might regress even with Briles as coach.

The team most likely push Oklahoma is TCU. Gary Patterson had the 17th ranked defense by my adjusted yards per play despite a rash of season ending injuries. With the return of a few of these players, who do not count towards the number of returning starters, TCU’s defense should be elite.

On offense, TCU lost almost all of their skill players on offense. However, they will reload with Texas A&M transfer Kenny Hill at quarterback.

How many conferences will my numbers get right?

The Power Rank’s preseason model predicted the game winner in 73.3% of games in 2015. Despite appearances, it is possible to make accurate game by game college football predictions right now.

However, that doesn’t imply we know which teams will win their conferences with any certainty. Teams play a small sample size of 8 or 9 games to determine a champion, which provides an opportunity for teams to steal a conference title.

It only takes one game. In 2015, Michigan State traveled to Ohio State without QB Connor Cook. The markets made the Spartans more than a two touchdown underdog. Michigan State won the game anyway, and this one loss eliminated Ohio State from Big Ten title contention.

For the Power 5 conferences, no team has better than a 50% chance to win their conference by my numbers. Oklahoma has the highest odds at 47.6%, a number that could be higher because of the coaching changes at Baylor.

This means that if three of my predicted champions actually win, I would have benefitted from some good fortune in making my predictions. This leaves plenty of room for surprise teams to make a run at the College Football Playoff, just like Michigan State in 2015.