to play football, not to play trumpet
This article by ScienceDaily sums it up pretty well. Link
Author Kun Ping Lu, MD, PhD, Chief of the Division of Translational Therapeutics in the Department of Medicine at BIDMC and Professor of Medicine at Harvard Medical School (HMS), states "Our study shows that an early neurodegenerative process induced by the toxic tau protein can begin just hours after a traumatic brain injury. In both cell models of stress and in mouse models simulating sport- and military-related TBI, the production of this pathogenic protein, called cis P-tau, disrupts normal neurological functioning, spreads to other neurons and leads to widespread neuronal death.
We have developed a potent monoclonal antibody that can prevent the onset of widespread neurodegeneration by identifying and neutralizing this toxic protein and restoring neurons' structural and functional abilities."
Whether or not this research translates into effective interventions, there's still typically the caveat of new treatments taking years to receive FDA approval. Fortunately, though, that's a topic which is receiving some attention -- Kate Upton's Uncle Fred actually proposed a bill to congress that, if passed, would accelerate the process.
Recent conference expansion talk has fueled more speculation about the Big Ten adding a new member. Without a football powerhouse like Nebraska available, I believe that the only way a new member is added to the Big Ten is with solid athletics and powerhouse academic credentials. One way to measure academic excellence and activity is total research expenditures; I have compiled a list of total research dollars spent for a five year span (2004-2008) from The Top American Research Universities 2010 Report, from Part II starting on p.31. After gathering the raw data in Excel, I made a few simple calculations: summing data from different years, dividing schools into athletic conferences*, and finding the mean, median and mean expenditures per year. This should give some insight to where a potential Big Ten member needs to be (without being a special case like Nebraska), where the Big Ten fits among other conferences academically and which schools pump the most dollars into academic activity. Two notes about calculations: a) only schools with >$40,000,000 of research were included, the median does not include these schools in calculation, but both means heavily penalize a conference for a low-spending member and b) medical schools not on the university main campus are not included in calculations. Off the top of my head, IU, Rutgers, Nebraska and Arkansas are penalized heavily for this, so let me explain why: first, the AAU calculates this way and second, I did not have access to enough accounting data to do anything other than "include" or "not include" and chose the latter.
*Chicago was included in the Big Ten because of their CIC affiliation.
Conferences in order of total spending, a simple sum. (all numbers are *1,000):
Conferences in order of median spending (excludes schools under 40,000,000):
Conferences in order of average spending (includes schools below 40,000,000 as zero):
|Conference||Average||Average per Year|
Big Ten Total Spending by School, descending:
Big Ten Notables:
|Average (includes <40,000,000 as zero)||2,325,875|
|Average Per Year||465,175|
|Highest Spender||Wisconsin (4,116,318)|
|Lowest Spender||Indiana (678,879)|
Pac 12 Notables:
|Average (includes <40,000,000 as zero)||1,979,767|
|Average Per Year||395,953|
|Highest Spender||Washington (3,721,565)|
|Lowest Spender||Oregon (279,875)|
|Average (includes <40,000,000 as zero)||1,499,706|
|Average Per Year||299,941|
|Highest Spender||Duke (3,357,452)|
|Lowest Spender||FSU (898,502)|
|Non Qualifiers||Boston College|
|Average (includes <40,000,000 as zero)||1,052,591|
|Average Per Year||210,518|
|Highest Spender||Florida (2,720,376)|
|Lowest Spender||Auburn (672,043)|
|Non Qualifiers||Mississippi, Arkansas, Alabama|
Big XII Notables:
|Average (includes <40,000,000 as zero)||903,713|
|Average Per Year||180,742|
|Highest Spender||Texas A&M (2,555,789)|
|Lowest Spender||Oklahoma (393,766)|
|Non Qualifiers||Texas Tech, Baylor|
Big East Notables:
|Average (includes <40,000,000 as zero)||1,099,260|
|Average Per Year||219,861|
|Highest Spender||Pitt (2,656,991)|
|Lowest Spender||Connecticut (523,633)|
Possible Big Ten Additions:
|School:||Dollars spent last five years||Rank in CIC using current membership|
Hello Mgoblog users!
I am currently doing research on the nature of online communities, specifically for mgoblog.com. If you could please take this survey (<10 minutes), it would greatly help my research! I will also be sharing the results with Brian to help better the blog in the future. You DO NOT have to be a poster to participate!
(Mods, if possible, please sticky this for a few days so it doesn't get lost in 24 hours)
Now that we've reached the conference midpoint and looked at the conference outlook, it's time to take a look at the team stats. Unlike in previous editions, the graphics will include some pitching related stats despite too small of a sample size to be that meaningful. The pitching stats are starting to show some trends, though.
As another reminder, these stats aren't official, but they should be pretty close. I have to compile these by going through every box score and input them into Excel tables. Many times, box scores contain errors that are corrected in the official statistics, but they may not be adjusted in the online box score.
So, as I start each of these posts, we'll look at the three major derived stats that are readily available in the college game (batting average, on base percentage, and slugging percentage):
In that AWESOME EXCEL GRAPH, you can see each of the percentages as they accumulate over the season. It should be pretty obvious that as the season goes along, the lines should normalize to the average as more data comes in. What may be a bit more difficult to see is that Michigan's offense peaked in the Central Michigan game. At that time Michigan was hitting .328 (BA) and .411(OBP). The slugging picked up a bit since then, peaking in the offensive explosion in Illinois game one, with a .477 slugging percentage.
Michigan currently sits at .321 (BA), .404 (OBP), and .470 (SLG). That ranks 3rd, 3rd, and 4th in the Big Ten respectively (more on this below). In terms of conference only stats, Michigan is at .322 (BA), .411 (OBP), and .469 (SLG), which means we've done a little bit better in conference in terms of getting on base, but everything else has been pretty similar to the non-conference season. That's pretty surprising given the difference in talent we've faced, but at the same time, Michigan has had a couple of anemic offensive games against some of the Big Ten's best pitchers (Hippen, Bischoff, Leininger), and they've had some explosive games against some of the not so good (Illinois win).
Speaking of talent difference between conference and nonconference, the purple line in the above graph, for those who didn't pay attention last time, represents the RPI of our opponents. The number one team in Boyd Nation's pseudo-RPI would be a 1.000, and a team holding the #302 RPI (or any non-D1 opponents if you're a Buckeye who plays AND LOSES to D2 and NAIA teams) would register as a 0.000 score. From that, you can see that our non-conference schedule was pretty difficult with two games against #1 Coastal Carolina, but our last few games, as well as the Big Ten regular season are quite a drop in competition.
The second graph I tend to post up is per nine innings stats, particularly runs, hits, strikeouts, and walks. These are just the sum of our total stats accumulated over the number of innings Michigan has batted (a home win normally only has 8 innings, as compared to any road game having 9 innings). Taking a peak:
Looking at the above, we can clearly see the differences between "OMG WE LOST LAMARRE" and the the team becoming stable. LaMarre came back against Central Michigan, where we can see a small jump in hits and runs, but not much in terms of long term changes. The only long term pattern that comes from the post-LaMarre return is a slight drop in strikeouts, a product of Krantz and Stephens getting less at bats.
At the time of LaMarre's return, I probably would have predicted an increase in hits and runs per game, but as we'll see in a bit, a couple of players have really cooled down over the last few weeks, most notably Coley Crank.
For individuals and a brief look at pitching, follow the jump. Warning, it gets long. Probably unnecessarily long. But it is what it is.
I'm doing a research project, and the official MGoBlue page isn't helping me very much.
Is there anywhere I can get historical schedules/results for every Michigan hockey team ever (or at least since 1922)?