The Race for Indy 2016: The Preseason

By Matthew Lundeen on August 31, 2016 at 10:02 am
The race for the Big Ten title is on.
Aaron Doster-USA TODAY Sports
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Let's use math to project how many wins each team will have this season.

Last time we asked the question "How good is our football team?" Today, we ask another important question: How many wins will our football team have this season? 

While the former carries quite a bit of significance, the goal of football is to win football games. You may believe your team to be really good, but if they are extremely unlucky and they lose a number of games, it makes for a disappointing season. (Something that 1997, 2005, and 2010 all taught us.) On the flip side, does it really matter how good your team really is, so long as they win the games on their schedule? (I'm looking at you, 2015.) 

So, yes, estimating the real talent level of your team is important, but at the same time, a ranking only tells us so much; it is only a numerical slot, after all. If you are the #1 or #128 team in the nation, we have a pretty good understanding of what that means. But if you are #23, #35, or #64, what exactly does that mean? Things get especially muddy when we consider that no team plays the same schedule. Thus, the #1 team in the nation could have one or two losses due to playing in the SEC, while the #30 team could go undefeated in the American. Does that make the team playing in the AAC better than the team playing in the SEC? Of course not. That's why we ask the question we did last time, inquiring about a team's real talent level. However, because rankings only tell us so much, at some point, we want to give ourselves an idea of how things will actually play out on the field, based on the schedule each team has been given for the season. And that's what we will do today by looking at win probabilities. 

Now, please note that because the Composite Rankings that we are using in the Tracking Massey posts this season do not aggregate anything more than those numerical slots called "rankings" that I mentioned above, we have to use a ratings system in order to project wins. Since THOR+ has been retired this season, I have decided to use Ken Massey's own independent model (not to be confused with the Composite Rankings he compiles) to estimate win totals as the season goes on. According to Massey himself:

Only the score, venue, and date of each game are used to calculate the Massey ratings. Stats such as rushing yards, rebounds, or field-goal percentage are not included. Nor are game conditions such as weather, crowd noise, day/night, or grass/artificial turf. Overtime games are not treated any differently. Finally, neither injuries nor psychological factors like motivation are considered. While none of these are analyzed explicitly, they may be implicitly manifested through the game scores.

He also gives answers to other frequently asked questions here if you are interested. 

Why Massey's ratings system, you may ask? I don't really have a good reason. At this point, I feel like most models are of similar quality and the differences between them are just splitting hairs. The one thing I do like about Massey's ratings is that he also calculates them for FCS schools, so Iowa playing North Dakota State looks a lot better than Maryland or Rutgers playing Howard. Beyond that, though, I could have used S&P+ or FEI or something else, but I chose not to. 

Anyway, this weekly post this season will be very similar to how the win projections posts worked last season, only with a lot more Tableau and fewer embedded tables. Basically, I took Massey's win probabilities for each Big Ten team and ran a Monte Carlo simulation for the season a thousand times. Massey actually does this too, but he only shows us the total win distribution and ignores conference wins. Those are obviously important, so I ran my own simulations with his numbers and included conference wins. 

I think that's enough explanation, so let's look at the numbers.

2016 Preseason big ten win projections

Based on the thousand simulations, Iowa has the highest ceiling of any team in the Big Ten West. Wisconsin starts the season ranked higher in this model, but the difference in schedules makes the Hawks the preseason favorite in the West. 

On the other side of the conference, Ohio State is favored, but the two teams from Michigan aren't very far behind the Buckeyes. 

For some specific win totals, let's look at the mean, max, and min wins for each team:

win data

With 8.2 mean total wins and 5.7 mean Big Ten wins, the Hawkeyes edge out Wisconsin, Nebraska, Northwestern, and Minnesota for the Big Ten West. Of course, a division that has its top four teams all within 1.5 games of each other means that anything could happen. 

Meanwhile, the East is also anything but a foregone conclusion with Ohio State, Michigan, and Michigan State all within about 1.5 games of each other. 

Strength of Schedule

We are going to look at each team's schedule in a minute, but here is an overview of how Massey's model rates each team's slate.

schedules

Note: The numbers indicate the average opponent ranking, with red being difficult and blue being easy. 

Some observations:

  • Every team in the East has a tough conference schedule because the East is rated a bit higher than the West, and they obviously have to play each other. 
  • Ohio State actually edges out Wisconsin for toughest overall schedule, but nobody beats the Badgers' Big Ten slate. 
  • Michigan and Michigan State have their conference schedules flipped. The Spartans get all of the difficult teams at home, while Michigan gets most of their tougher opponents on the road. That could be the difference in who wins the East this season. 
  • Maryland and Rutgers have terrible non-conference schedule ratings because they both play 423rd ranked Howard, which drags their overall schedule rating down. 
  • It should come as no surprise that the teams in the West with the easiest schedules are the three that miss all or most of Ohio State, Michigan, and Michigan State. Those three teams would be Iowa, Minnesota, and Purdue. 
  • You can see why Minnesota is the dark horse pick for the Big Ten West this season. They not only have the easiest overall schedule, but they look to have the easiest Big Ten one, too. Now we will just have to see if they are good enough to take advantage of it. 
  • Of course, Iowa is still the favorite for the West and their conference schedule tells you why. Like Michigan State in the East, the Hawkeyes get all their easy Big Ten games on the road, and all their more difficult ones in front of a home crowd. That should leave them less likely to slip up on the road, and hopefully make their tougher foes more prone to stumble in Kinnick. 

Big Ten WEst

Iowa

iowa
Average Simulated Wins: 8.2 Overall, 5.7 Big Ten
Offensive Rank: #38
Defensive Rank: #22

Again, Iowa is the favorite thanks to returning a good number of guys and because of this schedule. Heading into the season, they are favored in 11 of 12 games. However, I would be lying if I said I wasn't at least a little nervous. All four Big Ten home games are against what looks to be tough competition, and road games against Minnesota and Penn State are far from guaranteed wins. If the Hawkeyes can make it through the Michigan game with only one or two conference losses, they should be in excellent shape to make it back to Indy this season. 

And, yes, Massey's model does think North Dakota State is Iowa's toughest non-conference game.

Wisconsin

uw
Average Simulated Wins: 7.3 Overall, 5.0 Big Ten
Offensive Rank: #63
Defensive Rank: #3

Wisconsin may be good this season, but it could be hard to tell with a schedule like this. There's a real chance that Paul Chryst could find himself 2-4 overall and 0-3 in the conference when he brings his team to Iowa City on October 22nd. And even after they get past the three-headed hydra from the East, the Badgers face three of the top contenders in the West before they get a break. Their season likely depends on them running the ball a lot better than last season, and hoping the defensive fallout from losing Joe Schobert to the NFL and Dave Aranda to their week one opponent isn't too much to overcome. And if Corey Clement can't stay on the field again this year, it could be a long season in Madison. 

Nebraska

nu
Average Simulated Wins: 7.1 Overall, 4.8 Big Ten
Offensive Ranking: #22
Defensive Ranking: #54

If you look at things from a returning production standpoint, Nebraska should probably be in pretty good shape on offense again this season. Yes, Tommy Armstrong demonstrated the tendency to transform into Tommy Armpunt at the most inopportune times, but Nebraska still had quite a bit of offensive talent last season. The big issue in 2015 was on the other side of the ball, and with just 59% of their defensive production returning in 2016, defense could be a problem again this season. 

Schedule-wise, Nebraska also faces an uphill battle on the road this year. Games at Northwestern (who has played them tough basically every single year since joining the Big Ten), Wisconsin, Ohio State, and Iowa make it so the Huskers best chance at winning the West likely hinge on the winner of the division walking away with a minimum of three losses. 

Northwestern

nw
Average Simulated Wins: 6.7 Overall, 4.5 Big Ten
Offensive Rank: #85
Defensive Rank: #9

Northwestern has one of the toughest conference schedules in the West, outside of Wisconsin and Illinois. Road games against Ohio State, Michigan State, Iowa, and Minnesota pretty much guarantee two or more conference losses in those four games alone. Toss in home contests against Nebraska and Wisconsin, and Pat Fitzgerald is really going to need his close game wizardry to keep Northwestern in contention in the West in 2016.

Minnesota

minnesota
Average Simulated Wins: 6.7 Overall, 4.2 Big Ten
Offensive Rank: #67
Defensive Rank: #38

Minnesota's season could very likely come down to their performance in close games. They have a nice, soft middle portion of the conference schedule, but their performance in the first two and final three games of the Big Ten season will likely be the determining factor in whether or not they challenge for a title in the West. If they can win two or more of those games -- and not slip up in the middle of the conference schedule -- they could be real contenders this season. 

Illinois

illinois
Average Simulated Wins: 4.9 Overall, 3.0 Big Ten
Offensive Rank: #90
Defensive Rank: #47

With North Carolina and what is normally a pesky Western Michigan team popping up in their first three games, Illinois runs a decent risk of starting this season 1-2 entering Big Ten play. I probably wouldn't bet money on them losing at home to Western Michigan, but I also wouldn't be terribly surprised, either. However, once Illinois does get into Big Ten play, they run a much higher risk of losing their final six games of the season. Welcome to the Big Ten, Lovie!

Purdue

pu
Average Simulated Wins: 4.3 Overall, 2.4 Big Ten
Offensive Rank: #70
Defensive Rank: #101

Nutshell: It's year four of the Darell Hazell project, Purdue actually has a gift of a schedule this season, and this team still looks screwed. 

Big Ten East

Ohio State

osu
Average Simulated Wins: 10.0 Overall, 7.6 Big Ten
Offensive Rank: #9
Defensive Rank: #2

The Buckeyes are currently favored in every game to start the season. And, for the second straight year, Ohio State gets both Michigan teams back-to-back to end the year. So as long as this young Buckeye team doesn't trip up one too many times during the Wisconsin, Penn State, Northwestern, and Nebraska four game stretch, the Big Ten East could likely be a three team race until the very end of the regular season. 

Michigan

michigan
Average Simulated Wins: 9.1 Overall, 6.2 Big Ten
Offensive Rank: #27
Defensive Rank: #5

Everybody is jumping on the Harbaugh train again this offseason, and rightfully so. But the fact that Michigan was dealt a schedule that forces them to play three of their toughest games on the road could be the biggest reason they don't win the East in 2016. 

Michigan State

msu
Average Simulated Wins: 8.4 Overall, 6.1 Big Ten
Offensive Rank: #30
Defensive Rank: #6

Michigan State's schedule is quirky as hell this season. They start the year with Furman and then immediately take an early bye week to prepare for Notre Dame. On the one hand, an extra week to prepare for the Irish is probably a good thing. On the other hand, having a bye in week two and then having to play 11 straight weeks of football could be damaging come November.

By the time they get to Ohio State and Penn State, the Spartans will have played 9 and 10 straight weeks of football, which is taxing even on the best of athletes. They are fortunate enough to get Wisconsin, Northwestern, Michigan, and Ohio State all at home this year, but that non-conference game at Notre Dame, a potentially healthy Taysom Hill in week 6, and Penn State at the end of the season in Happy Valley still make for a tough schedule. Essentially, Dantonio is probably going to need some more of his trademark good luck to get to 10 wins again. 

Penn State

psu
Average Simulated Wins: 6.3 Overall, 4.3 Big Ten
Offensive Rank: #73
Defensive Rank: #26

Penn State is breaking in a new quarterback and two new coordinators in 2016 and they have to go to Pittsburgh in week two and then face a what has recently been a feisty Temple team in week three. They get the Owls at home this season, but James Franklin and Co. still play a pretty tough non-conference schedule overall and then start Big Ten play in Ann Arbor on September 24th. 3-1 would be outstanding, but 2-2 or even 1-3 are very real possibilities by week four.

Once they get past that fourth week, though, the schedule lightens up a bit, and their games against Ohio State, Michigan State, and Iowa all come at home. If they can survive weeks 2-4, they have the chance for a pretty good season if they can pull off some magic in Beaver Stadium. If they can't, though, then another seven-ish win season is waiting in the wings. 

Indiana

iu
Average Simulated Wins: 5.9 Overall, 3.6 Big Ten
Offensive Rank: #21
Defensive Rank: #114

The quarterback competition in Bloomington has been interesting this offseason, and not just because the announced starter wears #21 on his jersey. (I can't be the only one who finds this odd, can I?) The battle of contrasting styles in Zander Diamont and Richard Lagow seems to have been won by the latter's arm over the former's legs. However, even if Lagow starts, I would be very surprised if Indiana didn't use Diamont in special packages this season to get their offense some more explosive plays. Either way, I expect Indiana's offense to be its usual high-octane self, while the defense tries to get its thing together under yet another new defensive coordinator.

The Hoosiers should start the year 3-0, but stand a very real chance of being 3-4 after October 22nd. Hoosier fans should expect 6-6 from this schedule and be very happy if they reach 7-5. 

Maryland

maryland
Average Simulated Wins: 5.8 Overall, 3.1 Big Ten
Offensive Rank: #57
Defensive Rank: #75

I'm not really sure why, but the Terps play back-to-back non-conference road games against FIU and UCF in weeks two and three. Despite being away from home a lot to start the season, though, Maryland does get a nice buffet of cupcakes that should help them start the season at 4-0. But after they play Purdue, things get very real and they could easily lose their next seven games.

This team could finish with five or six wins in 2016, but they will probably be five or six very hollow wins with this schedule.

Rutgers

rutgers
Average Simulated Wins: 4.5 Overall, 2.6 Big Ten
Offensive Rank: #55
Defensive Rank: #94

Kudos to Rutgers for starting off the season with a real opponent. They should get shellacked, but at least the players get a free trip to Seattle out of the deal. (The city is absolutely gorgeous this time of year.) In weeks two and three the Scarlet Knights should get fairly easy wins against Howard and New Mexico, but then should brace for a long Big Ten season. There is some potential for conference wins against Illinois, Indiana, and Maryland, but those are far from being sure things. With this schedule, Rutgers is probably a 5-win team at the absolute best, and a 1 or 2-win team at worst. The truth, of course, will probably fall somewhere in the middle. 

The Week Ahead

wk 1

In week one, we have the usual amount of noncompetitive warmup games that usually accompany the season's kickoff. However, aside from the Hawkeyes, there are a few interesting games to watch this week.

I, for one, am always happy when there is Big Ten football on opening Thursday night, and this year we not only have Minnesota to watch but we get Indiana, too. Neither game is projected to be all that close, but at least we get to see our old pal Gary Andersen take on Minnesota again. Not to mention, we get to watch Richard Lagow play the quarterback position while wearing the #21. (It looks so weird, you guys.)

On Friday night, Michigan State kicks off what is essentially their preseason scrimmage with Furman at 6:00. That leaves you with an hour to get an idea of what the new quarterback situation will look like for the Spartans this season before switching it over to something actually competitive when Colorado takes on Colorado State at 7:00. And then at 8:00, Kansas State at Stanford and Toledo at Arkansas State also look to be better options than watching the second half of the MSU game.

On Saturday, Northwestern and Western Michigan may be worth watching to see if P.J. Fleck's team can give the Wildcats a run for their money. And the grand finale gives us Wisconsin vs. LSU at "neutral" Lambeau Field. I'm hoping this game is competitive, but if it isn't, this is at least your first chance to watch Leonard Fournette in 2016. He is pretty fun, after all.

Overall, while it's not a great slate of games in week one, we should be glad to have it on our televisions again. Welcome back, college football. You have been sorely missed. 

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