The top 5 insights into Alabama vs Clemson, Part II

How will Clemson match up with Alabama in the College Football Playoff championship game? Will the result be any different from last year, when Alabama claimed their 4th national title in the last 7 years?

Let’s count down the top 5 insights that will affect the outcome of this game. Yes, we’ll revive the Star Wars analogy from last year’s preview.

5. Clemson dominated the line of scrimmage in Part I

Last season, my numbers favored Alabama by 6.4, and the Crimson Tide won 45-40. Solid victory for analytics, right?

No. Clemson clearly won the line of scrimmage. I’ve never seen this type of domination over Alabama, as the Clemson defensive line in particular made a mockery of attempts to block them.

Despite this edge in the trenches, Clemson lost due to numerous blown coverages in a secondary that had excelled all season. Alabama also recovered an on side kick to provide an extra possession, and it was enough to hold onto a 5 point win.

Will Clemson dominate the line of scrimmage again in Part II against Alabama? Probably not.

However, consider that Clemson’s defense has put 4 and 7 starters in the 2015 and 2016 NFL drafts, respectively. Despite these losses, they continue to dominate, as they allowed 4.56 yards per play, 4th best in the nation this year.

4. Mike Williams vs Marlon Humphrey

Clemson QB Deshaun Watson has many solid receivers, but none more talented than Mike Williams. Watson has targeted Williams 129 times this year for 9.8 yards per target.

Many expect Williams to be a first round NFL draft pick. He can improve his draft stock in the championship game as he will face Alabama cornerback Marlon Humphrey, another projected first round pick.

We’ll put numbers behind the transcendence of this Alabama defense later. But for now, let’s focus on the secondary in the semi-final game against Washington.

Dante Pettis and John Ross had terrorized Pac-12 defenses all season, as Washington had a potent pass offense had gained over 8.5 yards per attempt heading into the Playoff. (Numbers include sacks unlike traditional college football statistics.) Against Alabama, these top receivers had difficulty getting open, as Washington threw for a meager 2.6 yards per attempt.

Clemson’s Williams might have more talent than any of Washington’s receivers, but we’ll see whether he can get open against the Alabama secondary.

3. Can Jalen Hurts lead a come from behind victory?

Before the start of this season, Nick Saban told ESPN “I don’t care who we start at quarterback. He ain’t going to be that good.”

True freshman Jalen Hurts won the job, and he has excelled beyond all expectations. Hurts has completed 64.7% of his passes (college football average is 60%) as well as gained 6.2 yards per carry as a dual threat quarterback.

But how will the freshman play if he must bring Alabama back from a late game deficit? He hasn’t face that situation yet this season.

My member numbers favor Alabama by 9.4 points. However, the clear favorite doesn’t always have a late game lead.

What happens when Alabama no longer gets points from the defense or special teams? They have scored 15 non-offensive touchdowns this season, although randomness has certainly played a role in this astounding number.

If Alabama faces a late game deficit, Hurts will have to throw the ball. This plays right into the strength of the Clemson defense, as they have the 3rd best pass defense by my adjusted yards per attempt.

Then if Clemson doesn’t make the same blunders in the secondary as last year, they could very well pull off the upset.

2. The Alabama defense

In my preview of last year’s game, I made a Star Wars analogy for Alabama.

But Alabama is college football’s empire, a finely oiled machine with infinite resources to destroy the opponent. Their defense is a Death Star aimed at Clemson and another national title.

This season, Alabama acquired more potent Kyber crystals to power their Death Star.

The defense remains the top ranked unit by my adjusted yards per play just like last season. But while they projected to allow 4.3 yards per play to an average FBS defense last season, that number has dropped to 3.9 this season.

To see how the Alabama defense match ups with Clemson’s potent offense, I use data visualization to plot opposing units on the same line. Better defense appear further to the right to facilitate comparisons with the opposing offense. The unit that appears further to the right is predicted to have the advantage.

The visual shows how offense and defense match up in Alabama vs Clemson, Part II.

The top chart shows the expected dominance of Alabama’s defense over Clemson’s offense.

The bottom visual shows an even match up between Alabama’s offense against Clemson’s defense.

1. Deshaun Watson, adolescent Jedi

In keeping with the Star Wars theme, I said the following about Clemson QB Deshaun Watson in last year’s preview.

However, Clemson has played exceptional this season, and QB Deshaun Watson has taken a starring role. He’s a young Jedi beginning to use his full powers, just like Luke Skywalker in the New Hope.

Watson was spectcular against Alabama last year, throwing for almost 8 yards per attempt, a number that accounts for sacks unlike traditional college football statistics. This prompted Nick Saban to call Watson the best college QB since Cam Newton.

If Watson was Luke Skywalker in the New Hope last season, he is now Luke in Return of the Jedi this season. He’s had his full training from Yoda, and he won’t surprise anyone with a big game against Alabama.

Can Deshaun Watson blow up Alabama’s death star? He must have a spectacular game for Clemson to convert their 24.5% chance for the upset.

Podcast: Cade Massey on the NFL Playoffs and College Football Championship Game

On this week’s episode of the Football Analytics Show, I’m joined by Cade Massey, professor at the Wharton School at the University of Pennsylvania. He studies judgment under uncertainty, and there’s no better example than his Massey-Peabody football predictions.

We cover a wide range of topics, which includes:

  • How Cade has learned humility in building a predictive football model
  • The playoff karma of the New York Giants
  • What data says about whether match ups matter in football predictions
  • The sneaky trick for breaking into the sports analytics world
  • The Massey-Peabody prediction for Alabama versus Clemson

For match ups, I discuss a similar study in college basketball.

To listen on iTunes, click here.

To listen here, click on the play button.

Analysis of 2016 College Football Playoff Semi-final games

Let’s not coronate Alabama champion just yet. Over on Bleacher Report, I wrote about the College Football Playoff from an analytics perspective.

Alabama is the clear favorite, and I even like their chances to cover two touchdowns against Washington in the first semi-final.

But that dang football bounces in funny ways sometimes. A few turnovers here, maybe some subpar play from Nick Saban’s team, you never know.

Ohio State and Clemson features some interesting match ups, as both teams have their strengths on offense and defense.

To check out my analysis, click here.

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 Playoff Show with Mike Craig

I had the honor of having Mike Craig on the Football Analytics Show this week. Mike has made a living for ten years investing in the sports markets, and he’s been my partner in running the college football prediction service the past three years.

On the podcast, we discuss the following:

  • The difficulty of rating elite defenses like Alabama and Michigan
  • The key match up in Ohio State versus Clemson
  • The transition Mike has made from models that predict the markets to something else
  • The impossibility of giving only one piece of advice to those that want to start betting on sports

To listen on iTunes, click here.

To listen on the site, click on the play button.