At press time, Harbaugh had sent Michigan’s athletic department an envelope containing a heavily annotated seating chart, a list of the 63,000 seat views he had found unsatisfactory, and a glowing 70-page report on section 25, row 12, seat 9, which he claimed is “exactly what the great sport of football is all about.”
Hoke has said that he is against zone blocking being an offenses main blocking scheme. I hope he realizes that that you can run power football out of spread formations. Nevada does it out of the pistol and Auburns base running plays are the power and counter, which are used by all pro style teams.
Here is a link on Auburns offense http://offensivebreakdown.blogspot.com/search/label/Gus%20Malzahn
I hope that Hoke and Borges decide to incorperate some spread power running game into their offense, so we can increase our chances of keeping Denard.
I know it is early, but I would like to hear some oppinions. I was just playing NCAA Football 11 in dynasty mode (Using Michigan of course, but under SDSU playbook.) I'm starting Stephon Hopkins at runningback, and I personally think he would be a great option for starting runningback next year because of the power he would bring to the spot. Any thoughts? What other postition changes might we see in the roster with the CC?
This is a question for Brian, but I'd like everyone to view it.
With the recent ground-shaking change in our program, site traffic exploded and mgoblog went into a slightly-altered shell to weather the storm. User log-ins limited, and the site slowing up at times.
At a time like this, I feel it is most important for people to be able to log on, and express their opinions. My question to Brian is, can we as users, do anything to help improve the site?
In other words, if it takes money to upgrade the traffic this site can handle, I will gladly pitch in a few hundred (I probably should have done so by now anyway).
I hope that others will do the same, and pitch in whatever they can.
For a number of years now, it has been a popular position that the time off between the end of the regular season and the beginning of bowl season is excessively long, and leads to poor play early in games. Certainly I have found this to be an attractive explaination for the prodigous quantities of DERP we saw this bowl season.
But DERP is subjective, and the plural of anecdote is not data. Is there any substantial quantitative support to the notion that bowl games start off unusually sloppy? There are a great many factors at play; I chose to look at relevant statistics on a quarter-by-quarter basis. I don't have the massive database that seems popular around these here parts, and the typical box score doesn't give a per-quarter breakdown of anything but score. Bummer. Well, maybe if we go ahead and look anyway at a
chart of percent of total points scored per quarter, we can find something elucidating. All bowl games are included. Each team's per-quarter scoring is normalized by their total score in the game. Averages and standard deviations are then computed, based on the entire bowl team population. It seems plausible that excessive pre-bowl layoff will result in a substantially higher standard deviation in the early part of the game, when either offense or defense might be DERPerrific.
|U of A||70.00||0.00||30.00||0.00||10|
Well, hmm. We could weight the per-quarter score fractions by the total number of points scored per team (0-3-3-3 is less telling than 0-21-21-21), but we find that this makes little difference. In the unweighted case, we find that the first half standard deviation is 29% higher than the second half standard deviation. The first quarter standard deviation is about 16% higher than the average quarter.
This seems to lend mild support to the idea that bowl games start off unusually sloppy. How does this compare to regular-season results? I compared to games from weeks 12-15, but only if the game involved two teams that ended up bowl-eligible (I counted Arizona State, because I graduated from there and it was Wisconsin's/SJSU's fault anyway and if you don't like it then tough). I toyed with the idea of removing rivalry games, because rivalry games are weird, but I did not.
|U of A||48.28||17.24||10.34||24.14||29|
|Fresno||thanks for breaking the chart Fresno||0|
|U of A||0.00||0.00||70.00||30.00||20|
Stupid Fresno. Anyway, we continue to see elevated stdev for the first quarter of regular season games between bowl eligible teams, but by a lesser degree. For these regular season games, the first half standard deviation is 10.8% higher than that for the second half. The first quarter standard deviation is about 11% higher than the average quarter.
There are certainly some serious issues with this methodology. Does a sloppy defense give up more scores to a sloppy offense than when both are playing carefully? I don't know the best answer, but I'm sure it varies on a case-by-case basis. There are also many late-game effects for which I have not accounted - a prevent version of a dominant defense might give up the only score of the game in the 4th quarter when the game is out of reach (hi there Sparty!). This would give a large standard deviation value to the 4th quarter, erroneously implying sloppiness. I do not know how to account for these sorts of errors with the data set I have available. Further, I do not suggest that this is an all-inclusive list of methodological problems.
Still, 29% vs 10.8% seems vaguely compelling, give 70 bowl and 98 regular season scores. My statistical background has faded badly since undergrad, so I'm going to refrain from a hilariously misguided attempt at error bars. The sample size is large, but boy those data are noisy. Any time my standard deviation is as big as the average, I start to feel a little woozy...
This was requested somewhere on the board, so here ya go. My photoshop skills aren't great, but let's see what ya got! The Lloyd Brady thread was epic, I'm sure we can do some great things here...
Your "blank canvases"
Show me what ya got MGoBloggers