Big Ten 2016 Preseason Total Win Probabilities
Pre-Season Ratings
With fall practice just around the corner, it seems an appropriate time to digest some of the Advanced Stats-based ratings for Michigan and the rest of the Big Ten if for nothing else than to get the ol' data analysis engine tuned-up for the new season. Most MGoBlog readers are already familiar with the two principle resources that will feed this analysis: Bill Connelly's S&P+ Ratings (from FB Outsiders and SBNation FB Study Hall) and ESPN's Football Power Index (FPI). The wrinkles with theses forecasts are just that – they're forecasts, and as such use a completely different set of metrics than the in-season ratings. S&P+ uses 3 components: returning production, recent history, and a subjective element called recruiting impact. Similarly, ESPN makes its FPI sausage using three components similar to those of S&P+: returning starters, prior performance, and recruiting rankings; plus a fourth, coaching tenure. In the end, both S&P+ and FPI provide ratings of all 128 FBS division teams, where the rating is equivalent to expected points better (or worse) than the average FBS division team at a neutral site. A positive rating is better than average, and a negative rating is worse than average. Simple enough.
So then, the simplistic take would be to just pull out the Big Ten teams and look at their respective ratings – the team with the highest rating would be expected to win its division and the conference, like in Tables 1 or 2, right?
Team
|
S&P+ Rating
|
Rank
|
---|---|---|
Michigan
|
19.3
|
6
|
Ohio State
|
16.4
|
14
|
Michigan State
|
13.5
|
22
|
Nebraska
|
11.6
|
26
|
Penn State
|
11.3
|
28
|
Wisconsin
|
8.3
|
37
|
Iowa
|
8.1
|
38
|
Minnesota
|
7.0
|
42
|
Northwestern
|
5.1
|
46
|
Indiana
|
3.9
|
56
|
Maryland
|
2.9
|
62
|
Illinois
|
0.4
|
76
|
Rutgers
|
-3.1
|
87
|
Purdue
|
-3.1
|
88
|
Team
|
FPI Rating
|
Rank
|
---|---|---|
Michigan
|
17.2
|
11
|
Ohio State
|
16.4
|
17
|
Nebraska
|
12.9
|
25
|
Wisconsin
|
11.6
|
31
|
Michigan State
|
10.3
|
34
|
Penn State
|
10.1
|
35
|
Iowa
|
9.1
|
38
|
Northwestern
|
4.0
|
52
|
Indiana
|
1.9
|
62
|
Minnesota
|
1.7
|
65
|
Purdue
|
1.4
|
66
|
Illinois
|
0.0
|
73
|
Maryland
|
0.0
|
74
|
Rutgers
|
-0.1
|
75
|
Wrong, wrong, wrong.
Schedules Matter … Big Time
We all know by now, in the aftermath of the B1G moving to nine conference games, that not all schedules are created equal, and that some provide more likely Paths of Glory than others. This is not just because of inter-divisional opponents drawn, but also because half the teams play five home conference games while the other half play only four. That's a six-point year-to-year swing based on the scheduling constraint alone. Thus, the next step is to evaluate each team's schedule and respective matchups, and determine the point spreads therein using the S&P+ or FPI ratings, adjusting for whether games are played at home or on the road. Simple enough.
So then, the simplistic take would be to just sum up the wins and losses and look at the final standings. After working out tie-breakers, it's easy to determine which team should win the Big Ten Championship, like in Tables 3 or 4, right?
B1G East
|
B1G
|
Overall
|
||
---|---|---|---|---|
W
|
L
|
W
|
L
|
|
Ohio State*
|
8
|
1
|
10
|
2
|
Michigan
|
8
|
1
|
11
|
1
|
Penn State*
|
7
|
2
|
9
|
3
|
Michigan State
|
7
|
2
|
9
|
3
|
Indiana
|
3
|
6
|
6
|
6
|
Maryland
|
2
|
7
|
5
|
7
|
Rutgers
|
0
|
9
|
2
|
10
|
B1G West
|
B1G
|
Overall
|
||
---|---|---|---|---|
W
|
L
|
W
|
L
|
|
Nebraska
|
8
|
1
|
10
|
2
|
Minnesota
|
6
|
3
|
9
|
3
|
Iowa
|
5
|
4
|
8
|
4
|
Wisconsin
|
4
|
5
|
6
|
6
|
Northwestern
|
3
|
6
|
6
|
6
|
Illinois
|
2
|
7
|
4
|
8
|
Purdue
|
0
|
9
|
2
|
10
|
B1G East
|
B1G
|
Overall
|
||
---|---|---|---|---|
W
|
L
|
W
|
L
|
|
Ohio State
|
9
|
0
|
11
|
1
|
Michigan
|
8
|
1
|
11
|
1
|
Penn State
|
7
|
2
|
9
|
3
|
Michigan State
|
6
|
3
|
8
|
4
|
Maryland
|
3
|
6
|
6
|
6
|
Rutgers*
|
2
|
7
|
4
|
8
|
Indiana
|
2
|
7
|
5
|
7
|
B1G West
|
B1G
|
Overall
|
||
---|---|---|---|---|
W
|
L
|
W
|
L
|
|
Nebraska
|
7
|
2
|
10
|
2
|
Iowa
|
6
|
3
|
9
|
3
|
Wisconsin
|
5
|
4
|
7
|
5
|
Minnesota
|
3
|
6
|
6
|
6
|
Northwestern*
|
2
|
7
|
5
|
7
|
Illinois
|
2
|
7
|
4
|
8
|
Purdue
|
1
|
8
|
4
|
8
|
Wrong, wrong, wrong, dammit. It's got to be wrong!
Spreads & Likelihoods
A point spread, of course, is merely a reflection of the odds, or likely outcome, of a game. The trick then is to map the point spread into odds, or better yet, the percent likelihood of each opponent to win, with a 0-point spread being the logical (if not statistically validated), 50/50 boundary condition. Earlier last year, Daniel Griffith, a MiniTab Blog contributor, posted a tidy statistical analysis of the differences between the point spreads and actual results for all NCAA games from 2000 through 2014. Suffice it to say, the distribution of differences was found to be Normal with an essentially zero mean (if it isn't zero-mean, then the bookies aren't doing their jobs, yo!). Knowing the distribution characteristics, one can then compute the likelihood that an actual result is greater (or less) than the point spread.
Just as an aside, the most interesting point from the Griffith analysis is the following, in regard to the distribution of differences:
"The standard deviation ... is 15.5 points. That means that if a game shows a spread for your favorite team of -3 points, the outcome could be with high confidence within plus or minus 2 standard deviations of the point estimate, which is -3 ± 31 points in this case. So your favorite team could win by 34 points, or lose by 28!"
That, dear reader, is why they play the games, and that is also why you may wish to continue reading despite the somewhat disconcerting results shown in Tables 3 & 4.
Total Win Probabilities
After computing projected win probabilities for all the games in each team's schedule, it's possible to use those individual game probabilities to compute a distribution of total expected wins at the end of the season. The one vagary in working this analysis is in regard to FCS opponents. Since FCS teams have no ratings from either S&P+ or FPI, I've taken the liberty of assigning the lowest available rating of -18 to FCS teams (I can already imagine the horror-ific comments on this nugget). The eight B1G vs. FCS games this season are:
- Michigan State vs. Furman
- Maryland vs. Howard
- Rutgers vs. Howard
- Iowa vs. North Dakota State
- Minnesota vs. Indiana State
- Northwestern vs. Illinois State
- Illinois vs. Murray State
- Purdue vs. Eastern Kentucky
The Bottom Feeders & Hopeful Bowl-ers
So, all that preamble aside, it's time for the charts, starting with the (projected) bottom feeders and teams on the bowl-eligibility bubble: your Rutgers and Purdues, your Marylands and Indianas, your Northwesterns and Illinoises.
Rutgers
What can be said about Rutgers? OK, how about this: they've gotten a new coach with some OSU heritage, so now they're acting like it's the second coming of Bo Schembechler. Otherwise, it's not a pretty picture for the Scarlet Knights. Basically, they're staring at a 10% (S&P+) to 30% (FPI) chance of not having a losing season, including a near freebie from Howard University. Their most likely record is 4-8 (S&P+) or 5-7 (FPI). It doesn't look like there's any chance that the '14 win over Michigan is going to be dislodged from the Pantheon of Rutgers Classics anytime soon.
Purdue
It's just about the same story for Purdue as with Rutgers, but maybe not quite so godforsaken. S&P+ shows a most likely record of 4-8, while FPI kicks the Boilers up to 6-6 including its near freebie over Eastern Kentucky. With FPI giving them a 55% chance of not having a losing season, a bowl game is not entirely crazy-talk. S&P+ gives the Boilers only a 21% chance though, so let's not get carried away.
Illinois
As for Illinois, S&P+ and FPI appear to be in fairly close agreement, both forecasting a most likely record of 5-7 including a near freebie over Murray State, with S&P+ tipping to the low-side, and FPI tipping upward. The chances for Illinois to go bowl-ing range from 31% and 41%. Hey, at least it’s looking way better than Rutgers!
Maryland
Maryland is also a-tap-tap-tapping on a bowl-game chamber door, with most-likely records of 5-7 and 6-6 from FPI and S&P+, respectively - both tilting toward 5-½ - including a near-freebie vs. the Bison from Howard. Here’s where D.J. Durkin’s motivational skills may effectively put a shine on the Terds (I mean Terps, damn autocorrect!) and in the end garner some appeal to a bowl selection committee.
Indiana
Indiana is looking like the penultimate bubble-team. With an FPI mean of 5.5 and S&P+ mean of 6 and no FCS cupcakes on its schedule, Indiana is not to be taken lightly. Both distributions are nearly perfectly balanced, favoring neither the over or the under. However, with a solid shot at post-season glory, the Hoosiers will have a fire in its belly and could be the Ultimate Danger Team this season.
Northwestern
If Indiana is the penultimate bubble-team, then that must make Northwestern the ultimate bubble-team. Both forecasts see a 6-6 record as most likely, with S&P+ leaning ever-so-slightly to the over and FPI conversely to the under. Either way, the Wildcats have a 60-70% likelihood of seeing post-season action.
The B1GW Contenders
In the B1G West, quite frankly, there’s not a distinct separation between the so-called Contenders and the rest of the division. But on the simple basis of expected total wins, a Contender for the purpose of this discussion is taken to mean a those teams that by one rating or the other, are shown to be one of the top three teams in the division, and/or within 2 total wins of the top rated team. In the B1GW, those teams are Wisconsin, Iowa, Minnesota and Nebraska.
Wisconsin
Of all the teams in the B1G, it would appear that Wisconsin suffers the most from the ill effects of both scheduling constraints and interdivisional draws. Not only do the Badgers have five B1G road games, but three of them are at Michigan State, at Michigan, and at Iowa within a span of 4 games – the fourth being at home versus Ohio State. As a result, a team that common wisdom might say is the team to beat in the B1GW looks like a team more likely to end up in a non-CFP/New Year's Six bowl. FPI expects a 7-5 record with a 70% chance of a winning season, whereas S&P+ expects only 6 wins, and gives them only a 44% chance for a winning season.
Iowa
The Hawkeyes appear to be right on track to regress from the millennial celestial alignment that took place last year. That said, with an S&P+ mean of 7.5 wins and FPI pushing toward eight, Iowa retains a punchers chance of bringing home the B1GW bacon, if not Floyd of Rosedale. S&P+ gives Iowa a 25% chance, FPI a 30% chance, of 9 wins or more. That many wins will probably be more than enough for a ticket to Indy the first Saturday in December.
Minnesota
Minnesota is a riddle, wrapped in a mystery, inside an enigma. The Gophers could eat the shark, or the shark could eat the Gophers. With a mean of 7.5 wins from S&P+ and a 26% chance of 9 wins or more, the Gophers could waltz all the way to Indy. On the other hand, FPI gives the Gophers a 63% chance of a non-winning season. Either way, the road to the B1GW trophy passes through the Gophers’ Black Hole.
Nebraska
So last but certainly not least in the B1GW is Nebraska. It turns out that it's the Cornhuskers that are the true team to beat in the B1GW. Perhaps overlooked by many CFB pundits on account of a confluence of bad breaks that torched their record last season, expectations are low and so the Huskers can fly under the radar. Both S&P+ and FPI numbers however, are giving them some love. S&P+ estimates about 8 wins and FPI, 8.5 wins, with both leaning to the over. Indeed, S&P+ gives Nebraska a 39% chance of 9 wins or more, and FPI gives them a 51% chance. By either measure, Nebraska looks to be the B1GW representative in Indy.
Overlay
To summarize, here are overlays of the total wins probabilities for the B1G-W contenders. Nebraska, by the slimmest of margins, leads in both S&P+ and FPI, with Iowa consistently lagging behind them in close competition for the second place. Wisconsin and Minnesota essentially swap places for the third and fourth slots depending on the rating source.
The B1GE Contenders
In the B1G East, there is in fact a clear separation between the four Contenders and the three teams mentioned above (Rutgers, Maryland and Indiana). Thus in the B1GE, the Contenders are the 3 “State” teams (Penn State, Michigan State, Ohio State) and Michigan. Otherwise the classification applied to the B1GW also applies to the B1GE. That is, the Contenders are those teams that by one rating or the other, are shown to be one of the top three teams in the division, and/or within 2 total wins of the top rated team.
Michigan State
The gig appears to the up for the Spartans. The build-up of Spartan pride from an accumulation narrow wins last year, including the win-which-shall-not-be-named, has already led to their spectacularly catastrophic fall in the CFP semifinal. That decline appears to be sustained looking ahead next season. S&P+ gives Sparty less than a 4% chance of matching (or improving) its regular season win total from last year; FPI, less than 2%. Indeed, it's slightly more likely that Sparty will have a losing season. Eight wins is the most likely total from S&P+, with only seven expected as per FPI... and these numbers include a virtual freebie against Furman. In both forecasts, five of MSU's games this season have spreads of less than one score.
Penn State
Penn State, on the other hand, looks to provide some salty competition in the B1GW. With eight wins most likely from S&P+ and 7-½ from FPI, PSU could just win its last five games. If it can manage to take four or more of its first seven as well, and with a little help, it could be the team in Indy come December. The Nittany Lions stand a 25% to 29% chance of closing with nine or more wins. More realistically, it has 50% to 60% chance of improving its record over last season's, which should be sufficient to preserve James Franklin's job.
Ohio State
Ohio State, comparatively speaking, is poised to show some marginal separation between themselves and MSU or PSU, with a solid 8-½ wins expected based on both the S&P+ and FPI ratings. Nonetheless, 2016 looks to be a definite retrograde movement from last season's CFP near-miss. Indeed, OSU is a two-score road underdog at Oklahoma, and beyond that has 5 other games within a one-score margin as per FPI, and 4 one-score margins per S&P+. Thus, the Buckeyes are showing a seemingly depressed mean wins number. Of course, a likely early loss at Oklahoma does little to hurt tOSU's CFP prospects, and absolutely nothing to help Michigan's Big1T4en Championship prospects. The proof is in the Big1T4en pudding, thus the expected 3-½ overall losses maps strongly into 2-½ conference losses. That could be significant, even if Michigan is not one of the losses.
Other fun statistical observations:
- Chances of tOSU improving on last season (i.e. going undefeated): less than 1%.
- Chances of tOSU losing 3 or more games: 78-80%.
- Chances of tOSU having a losing season: 2-3%.
Michigan
Michigan is the one team in the B1G that stands apart from all others in the results of this analysis, with expected win totals of 10 from S&P+ and 9-½ from FPI. It’s just that sort of separation that Michigan will need to have come the last Saturday of November in Columbus. The Buckeyes at this point are favored by both S&P+ and FPI, although the favorite would be the Wolverines were the Game to be played in Ann Arbaugh. Notwithstanding playing Sparty on the road as well, Michigan still benefits from otherwise having five B1G games at home, its first five games at home, and its first road game at Rutgers.
Here are some fun statistical observations:
- Chances of a Michigan losing season: vanishingly small.
- Chances of Michigan not improving on last season’s win total (losing 3 or more games): 37-51%.
- Chances of Michigan improving on last season's win total (10 or more wins): 49-63%.
- Chances of Michigan going undefeated: 4-7%. This is at least 4-10 times greater than any other team in the B1G!
Overlay
In summary, here again are the overlays for the B1G-W contenders. As you can see, Michigan shows a separation of 1 to 1½ games over the Buckeyes as per the FPI and S&P+, respectively. The peakedness of the Michigan S&P+ distribution is unique across the conference. This is due largely to a soft-looking schedule full of double-digit underdogs and only 2 games within one score (@MSU and @tOSU). The Buckeyes hold down second place by a solid game over the neck-and-neck MSU and PSU in the FPI profile. The margin shrinks to about a half game over MSU in the S&P profile.
So there you have it. In the process of assembling this, as many new questions would come up that I wanted to delve into as were answered in doing this in the first place, but exploring those tangents would have prolonged posting this even further out. For example, what's really important are the conference records, so part of me wanted to break out the conference games into separate distributions and focus more on those. Also, the projected separations between particular teams beg the questions one can already envision regarding the various tie-breaker scenarios that may well pop up near the end of this season as they did last year. Also, a couple of weeks ago, Ed Feng of The Power Rank posted his ratings, so now I've actually analyzed his numbers as well, but sets of 3 charts is getting even busier than this already is, so I was wondering what some sort of composite rating of the three might look like but ... it's summer time and I've got my copy of HTTV calling my name, so I'm going to end this here. For now.
Yours in football, and Go Blue!
Sent from MGoBlog HD for iPhone & iPad
But I do appreciate your efforts and am encouraged by Michigan info.
That's exactly right. Oklahoma is by far OSU's most difficult game with about a 25% chance to win, so that game counts about 0.75 toward OSU's total losses column.
The conference standing projections are up there. OSU is projected to go 8-1 or 9-0, and we're projected to go 8-1 in each. In both cases they win the East. Lame.
those projections are based on individual game W-L likelihoods aggregated, which is the wrong way to do it, as noted. That table is not expected wins in a true probabalistic sense.
The conference loss expectation for them is, as noted, about 2-2.5. And for us it's about 1.5-2. The division is likely to come down to The Game, but there is a better chance of us entering with two fewer losses and thus already having won the division, than of us being two games back without a chance to win it. So depending on how much edge they have in that game, we still may be the favorites in the division, statistically. It's very close at this point.
And in the case that both teams go 8-1, it's not a given that they win the East. They would if they beat us and lose a different game, but we win if we beat them and lose a different game.
Thanks!
How will Rutgers make the National Championship playoffs wtih an FCS team on their schedule? That has to hurt their strength of schedule. They aren't thinking like champions yet. LOL
"Chances of Michigan improving on last season's win total (11 or 12 wins): 49-63%."
When I add the numbers above the 11 and 12 I get 31.2%-20.8%. It would seem you included the 10-win percentage in your odds that they get 11 or 12. Am I reading this wrong?
That's correct. 10 wins in the regular season would be an improvement over the 9 wins last year (not including the bowl game).
How accurate have these projections been in the past?
Great analysis, thanks for posting. Hope you / the bookies are right!
Why the eff is MSU playing Furman?
Same reason M has played App St (twice), Deleware State, etc...
Cupcakes are delicious.
The same reason they played Jacksonville State?
Great analysis and well written. Fear the Terds!
Some of these preseason S&P+/FEI predictions will be pretty good, and some will no doubt we wildly off. Of course, one can't really predict that until the season starts.
FWIW, here is how the B1G did in 2015, in terms of preseason S&P+ vs. end-of-season S&P+:
Ohio State Preseason 24, End of season 24 (exactly on mark!)
Michigan Preseason 8.8, End of season 21.1 (B1G's biggest over-achiever)
MSU Preseason 17.2, End of season 15.9
Penn State Preseason 8.4, End of season 10.4
Maryland Preseason 0.7, End of season 1.8
Indiana Preseason -4.3, End of season 3.9
Rutgers Preseason -3.6, End of season -12.4 (B1G's biggest under-achiever)
Wisconsin Preseason 11.8, End of season 10.3
Nebraska Preseason 9.7, End of season 7.1
Northwestern Preseason -0.8, End of season 5.5
Iowa Preseason 0.7, End of season 7.3
Illinois Preseason -0.8, End of season 3.7
Minnesota Preseason 5, End of season 9.1
Purdue Preseason -3.2, End of season -3.9
------
Summary:
On average, each B1G team overachieved their pre-season S&P+ mark by 2.16. The standard deviation of their over/under-achievement was 5.32.
If this variation was incorporated into the predictions (more work, of course!), we'd see even more wildly distributed win probability predictions for 2016. But the big picture wouldn't change, it would still be U-M/OSU as the favorites in the East, Nebraska out West.
What would the numbers look like without Rutgers?
average among the remaining 13 B1G teams is +3 (final S&P+ ranking minus preseason S&P ranking), with a standard deviation of 4.46.
I'm too lazy to look up all the numbers, but in theory for all 128 FBS teams the average should be zero. At the least, the numbers seem to tell us that in 2015, the B1G over-achieved on the whole.
Thanks for all your hard work. WHile we could sit here for hours pointing out potential problems with the probablities generated by your sources, they stand as the best quantifiable analysis available anywhere.
Overall, ths makes me feel more confident about the Rutgers game and less confident about the Indiana game.
Also, I think "wearing down" and talented or well coached back ups play a HUGE role in winning the B1G title. I wish that could be incorporated into the source stats somehow. BUt, my feeling is that consistancy in coaching staff over the years helps with that the most. Michigan's back ups should be better "coached up" as a result of Harbaugh's system setting in better.....
I'll need to Google the contextual reasons for Penn St optimism. I'm not getting it.
Yeah, that's the chart that stood out most to me as seeming too optimistic. Here's their schedule:
9/3 vs. Kent State
Sat. 9/10 at Pittsburgh
Sat. 9/17 vs. Temple
Sat. 9/24 at Michigan
Sat. 10/1 vs. Minnesota
Sat. 10/8 vs. Maryland
Sat. 10/22 vs. Ohio State
Sat. 10/29 at Purdue
Sat. 11/5 vs. Iowa
Sat. 11/12 at Indiana
Sat. 11/19 at Rutgers
Sat. 11/26 vs. Michigan State
I really only see two easy wins on there (Kent State & Rutgers), and I would have to say Penn State is a real longshot to win against Pitt, M, OSU, Iowa, and MSU. That means getting to 7 wins would require them to win all their 50/50 games; 8 wins would take that plus an upset. Personally I see them going about 5-7.
S&P+ had PSU as the 4th best team in the B1G (and better than any team in the West) last year.
Now, take that 2015 number FWIW. Feel free to discard it, saying it doesn't pass the "eye test."
But from the point of view of S&P+ trying to predict 2016 --- they will (1) take that number as the baseline, (2) see a decent amount of returning players, and also (3) see Top 25 (generally 15th-25th) recruiting classes for 3 straight years.
It's not entirely shocking to see why S&P+ has the preseason ranking it has.
I'm one PSU fan who (1) doesn't like our coach, and (2) does wonder about the QB position this year. But I do think we're a bit "oversold" right now by most college football fans. Talent exists, and depth has rebounded off the sanctions years. 5-7 would really surprise me, much more so than, say, 9-3.
football games are won on the lines, as you said.
FWIW, PSU ranked 8th in the B1G in FEI in 2015. A PSU projection for 2016 leveraging FEI would likely look worse. FPI: I ingore that metric completely given that ESPN provides zero transparency in terms of how it is calculated. It could be a good metric, but who really knows?
"the Returning Production ranking you see below is based on the impact of returning talent on last year's S&P+." I do read that to mean that losing an Ezekiel Elliott or Carl Nassib type player matters much more than losing some no-name below-average RB or DE.
http://www.sbnation.com/college-football/2016/2/8/10922288/2016-college…
I think the fundamental disconnect you have is with Penn State's final 2015 ranking --- which inevitably is used as a bit of a "starting point" for 2016. Despite the 7-6 record with no memorable wins, S&P+ saw Penn State at #30 overall and as the B1G's 4th best team in 2015. Better than anyone in the West.
Such was S&P+'s result. S&P+ sometimes does weird stuff. It had Alabama, Clemson and OSU as last year's 1-2-3 (looks right), but it also ahd WKU at #11 (!!!), and Houston at #44 (???) and Iowa at #47 (???).
FEI, as stated earlier, had Penn State at 8th best in the B1G in 2015.
I will admit to preferring FEI over S&P+. FEI is more drive-based and as such is IMO more holistic, as opposed to S&P+, which can be influenced more by individual big plays.
Overall, good conversation here, I enjoy talking football analytics!
Thanks for pointing that out. The article was a little confusing but there is a link to a different post in which Connelly explains his methodology for calculating "returning production." I guess it does take account of which players you are losing and bringing back, so I stand corrected.
Excellent analyis! I'm both excited and dissappointed by the results. Although I'm not positive the OP knows what the word penultimate means...
Edit: I was wrong.
Nebraska and Michigan won't be sniffing the B1G championship game this year. Both will be lucky to get to 9 wins.
August 1st, 2016 at 12:02 AM ^
what ?
August 28th, 2016 at 2:25 AM ^
I don't see any scenario where Nebraska wins the West. This is a team that beat ONE team in the West last season.
Mike Riley knows how to sweet talk the Nebraska media and a lot of fans love him, which I guess is all that matters.
Nebraska is the aging beauty queen that needs to be told how pretty she still is.
But Mark Banker's ability to coordinate a defense is atrocious.
No way in hell Penn State beats Michigan State, in my opinion. James Franklin is the ultimate derp (he replaced Brady Hoke in that roll).
I expect PSU to be reeling/the players not to care, by the time they get to MSU at the end of the season.
Has anyone done a test to see how these pre-season ranking perform? Like for example Ed Feng touts predicting over 70% of games right last year with pre season predictions. Which sounds really great but when you really think about it probably only about 30% or 35% max of games would you consider a toss up. I'd best most of us could get 70% of power 5 games right without any formulas needed.
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Logged in just to upvote the OP. Good stuff.
Just how great the additions of Rutgers and Maryland were. Three cheers for Jim Delany!
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