Putting Out the Vibe Random observations from my day-to-day life

September 25, 2014

Data Abuse – How to cope when your loved ones have a usage problem

In honor of our -1 month wedding anniversary today, I’ve been reflecting on some of the major milestones in our relationship (see below).

Relationship Timeline

Arguably, the most significant date on this timeline, 11/15/13, has also proven to be one of the most bewildering. Little did I know, when considering the (mediocre) cost savings that only a “family” plan could provide, that I was entering into an inequitable relationship. I’m now a firm believer that cell phone companies should be required to provide historical data usage to potential family plan members.

We started with what seemed to be a very sufficient 4 GB of data. Thinking back to my early Napster days, this would have put me somewhere in the ballpark of downloading 1,000–1,600 Dispatch songs/month. A few months ago, I added a GB and now it appears we need another one. I was discussing this conundrum with Greg a few weeks ago and, after comparing my usage versus hers, he requested a blog post on the topic.

Cell Data Usage

Cellular Data Usage by Month

I’ve tried a lot of interventions – forcing her to connect to wifi in public places, changing her facebook settings to not automatically play videos unless connected to wifi, turning off her cellular data altogether – and it doesn’t seem to curb the usage. I have so many unanswered questions… What is she doing all day? How much data could liking an Instagram post possibly use? How many things can one person possibly pin to their Pinterest board in one month? How many pictures does she send to her sister per day (a lot for the record)?

If anyone would like to join our framily plan, let me know.

May 23, 2014

Too Many Girls

Gumpa reading Too Many Girls

Gumpa Rod reading Too Many Girls by Jonty Lees to Camille – the 14th of 16 straight girls in the extended family

There’s a running joke in my fiancé’s family that having boys is impossible – they’ve gone 16 tries without one. It’s clear there’s something weird going on with the Metternichs – they’re pretty good at making wine (my brother-in-laws-to-be and I visited the vineyard this past fall in The Rhine River Valley and Dave made gang symbols during wine tasting) and not so good at making boys. So is it impossible for them to have a male? Is the old wives’ tale that you are 30% or even 70% more likely to keep having the same gender child valid (this post attempts to debunk it)? I’m pretty sure the answer is no – if you consider each child’s birth to be an independent event determined by the male (like this geneticist does), the odds of each girl are roughly 50%, suggesting that the Metternich phenomenon is just really really unlikely. I attempt to estimate just how unlikely this is in the below calculations.

Metternich Female Tree

Fn = Pr(nth female)
Mn = Pr(nth male)

Probability of 16 same-gender-children in a row
(gender of first child doesn’t matter)
→ Pr(F16 | [M1∪F1]∩F2∩F3∩F4∩F5∩F6∩F7∩F8∩F9∩F10∩F11∩F12∩F13∩F14∩F15)

→[M1+F1]*F2*F3*F4*F5*F6*F7*F8*F9*F10*F11*F12*F13*F14*F15*F16

→.5+.5]*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5

= 1*(1/2)15 0.000030517578125 3 times out of 100,000
Probability of 16 girls in a row → Pr(F16 | F1∩F2∩F3∩F4∩F5∩F6∩F7∩F8∩F9∩F10∩F11∩F12∩F13∩F14∩F15)

→ F1*F2*F3*F4*F5*F6*F7*F8*F9*F10*F11*F12*F13*F14*F15*F16

→ .5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5

= (1/2)16 0.0000152587890625 1.5 times out of 100,000
Probability of a 17th girl (F17) → Pr(F17 | F1∩F2∩F3∩F4∩F5∩F6∩F7∩F8∩F9∩F10∩F11∩F12∩F13∩F14∩F15∩F16)

→F1*F2*F3*F4*F5*F6*F7*F8*F9*F10*F11*F12*F13*F14*F15*F16*F17

→.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5*.5

= (1/2)17 0.00000762939453125 8 times out of 1,000,000

Some of you are probably thinking “but aren’t there more men in the world than women?” The short answer is that since this sample size only consists of 16 babies, a fraction of a percentage won’t really skew the result. If you insist, however, the long answer is that a 2002 study found that the natural sex ratio at birth is estimated to be 1.06 males/female (there are likely evolutionary reasons for this that I won’t discuss here). In other words, they found the probability of having a male to be 53/103 ≈ 0.515. This means they found the probability of a female to be 50/103 ≈ 0.485. Changing the probabilities used in our calculations from 0.5 to 50/103, the odds of the Metternich phenomenon become even less likely.

Probability of 16 same-gender-children in a row
(first child is male)
[50/103+53/103]*53/103*53/103*53/103*53/103*53/103*53/103*53/103*53/103*53/103*53/103*53/103*53/103*53/103*53/103*53/103 = 1*(53/103)15 0.0000469439547385414 4.7 times out of 100,000
Probability of 16 same-gender-children in a row
(first child is female)
[50/103+53/103]*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103 = 1*(50/103)15 0.000019588072125144 2 times out of 100,000
Probability of 16 girls in a row 50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103 = (50/103)16 0.00000950877287628348 1 time out of 100,000
Probability of a 17th girl (F17) 50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103*50/103 = (50/103)17 0.00000461590916324441 5 times out of 1,000,000

That means that if future Metternich generations tried to replicate the above scenario 100,000 times, 16 girls in a row is only likely to happen once.

So where do I fit in to this crazy anomaly? I’m marrying F9. She’s pretty great at a lot of things but from the looks of the above diagram, having boys may not be one of them. Fortunately for us, her sister Jane may debunk this for us since she does have Pez in the dispenser (I’m going to trademark that). With Jane and Al’s Baby B to be (F17 or M1) comes another chance to break this ridiculous trend (taking the pressure off Ann and I). What’s your vote for the chances of it being female? Mine is exactly 50%.

October 7, 2013

Why do i get so tired flying every week?

Every time I fly (which over the last three years has been nearly twice a week), I get tired.  Not debilitatingly tired but enough that I just feel ‘off’ and less productive.  Many people would simply chalk this up to jet lag but the reality over the past three years is that I’ve found that this happens to me even if my flight spans only a single timezone or even within the same timezone.  Also, the rule of thumb that it takes one day to recover for every hour of time difference that you fly seems ridiculous.  If this were the case, it would take me the entire work week to recover from my Monday morning flight across the country (in reality, I’m probably productive by Tuesday) or the entire duration of my trip to Europe to recover.  Evidently this can be true for people with extremely rigid sleep schedules (also not me).  So here’s what I’m chalking my weekly flight fatigue up to…

1.  Dehydration

A study published in the New England Journal of Medicine in 2007 found that air cabins pressurized to 8,000 feet lower oxygen in the blood, making passengers feel uncomfortable and dehydrated (source).  Cabins are also very low in humidity, typically ranging between 10-20%.  This is much lower than a comfortable typical indoor humidity of 30-65% and even the lowest humidity cities in the US average around 30%.  Low humidity increases the risk of catching a respiratory virus, such as a cold since the moisture in the air keeps your airways moist so the lining can help trap germs trying to enter your body.

  • Solution:  Obviously, hydrating but it doesn’t help that drinks in airports cost more than a Qdoba burrito and bubblers (yes, bubblers) are hard to come by.  I didn’t realize this until I had traveled for a while but flight attendants will bring you additional water even if their big beverage show is over.  Don’t be afraid to be “that guy” and order a water AND an orange juice or even ask for additional water after the beverage road show.  It’s probably worth the extra trips to the gross plane bathroom even if you’re in a window seat and the guy next to you thinks you have a growing problem.  I’ve also been told to avoid caffeine and alcohol while flying but I’ve decided that I like coffee and Jack & Gingers too much.

2.  Poor Air Quality

In addition to the low humidity on planes described above, the overall quality of air on planes isn’t ideal.  Surprisingly, this is less a result of recycled air but more likely the cause of being in extreme proximity of already sick people.  Cabin air on planes is completely refreshed 20 times per hour (compared with just 12 times per hour in an office building) (source), only about 50% of the air in the cabin is likely to be recycled, and the oxygen level on aircraft remains pretty constant (source).  Also, most aircraft air is circulated through hospital-grade HEPA filters, which remove 99.97 percent of bacteria, as well as the airborne particles that viruses use for transport (unfortunately, many regional jets lack these filters).  Additionally, cabins are divided into separate ventilation sections about every seven rows of seats (source).  There have been reports of infections (including TB) being transmitted during flights but there is disagreement whether this is due to the the very fine filters not working or simply because the victim is seated close to someone with an infectious disease (source).  This is most likely due to either close proximity to a sick person or a result of the poorer air quality circulated through the cabin at the gate (air circulation is greatly reduced when the engines aren’t on).

  • Solution:  I suppose you could ask to be moved if the person next to you shares that they are ridiculously sick but on a full plane this isn’t realistic.  Otherwise, hope you have an immune system of steel and get a flu shot.

3.  Dozing off while taxiing on the runway

Something about the comfortable (sometimes) seat, the constant subtle vibration, and the ambient white noise always causes me to fall asleep while planes are taxiing.  Evidently, I’m not alone but few discuss this phenomenon in a scientific way.  It does make sense, however, since the brain naturally craves sensory input (people in sensory deprivation tanks hallucinate) and constant white noise, gives the brain a tonic signal that dampens its own internal systems (source).  I suppose the reasons that the low vibrations of taxiing cause me to sleep are also similar.  The problem, however, is that short naps for me are a crapshoot – sometimes refreshing me and sometimes making me more tired.  On a plane, I often don’t reach the 10-15 minutes required for a refreshing “power nap” and as a result just wake up more tired than when I started.

4.  Nutrition

Have you ever tried to eat healthy in an airport?  It will cost you twice as much as shopping at Whole Foods.  As a result, I always eat garbage while traveling and I believe this compounds my fatigue on my travel days.

  • Solution: Pay more for healthier food if you can afford it.  Otherwise, keep eating double cheeseburgers from McDonald’s and enjoy the 10-15 minutes of happiness.

5.  Jet Lag

I just got back from a vacation to Europe where I experienced many of the classic jet lag symptoms (especially insomnia on my second night there due to circadian rhythm disruption).  Although it’s on a much smaller scale, I suppose this does affect my shorter weekly flights.

(Mondays)

Trying to fit a normal life in to the three days that I’m actually home on the weekends probably doesn’t help the issue.  Over each weekend, I typically relax my sleep schedule so by Monday morning, even if I weren’t flying, I would likely feel a mini jet lag due to slight changes in my circadian rhythms (aka a case of the Mondays).

Let me know your thoughts and if any of you have any that I should add.

October 12, 2012

Where the Beer Flows like Wine: breakdown by state

I have a lot of pride in my Wisconsin roots – especially when it comes to beer. Although, the quality of WI beer (and beer drinkers) is hard to rival, since moving to Colorado, I’ve felt conflicted whenever I hear Coloradans bragging about the number of breweries in this state. Then, a couple of weeks ago I was discussing this point with some coworkers – one from CA and one from WA – who both thought their states had “a lot” of breweries too. When it comes to beer, this isn’t my first rodeo (or my first map) so I feel pretty qualified to get to the bottom of this issue…
 
Number of Breweries by State

Number of Breweries by State
From brewersassocation.org as of 10/8/12
California 512
Colorado 259
Washington 214
Texas 171
Oregon 168
New York 164
Pennsylvania 160
Michigan 150
Illinois 138
Wisconsin 119
North Carolina 105
Florida 104
Ohio 93
Virginia 89
Massachusetts 83
Minnesota 81
Missouri 73
Arizona 68
Indiana 66
Georgia 59
New Jersey 54
Tennessee 54
Iowa 49
Maryland 47
Montana 47
Maine 45
Idaho 38
Connecticut 37
New Mexico 35
Nevada 33
Nebraska 31
New Hampshire 30
Vermont 30
Alaska 29
South Carolina 29
Utah 27
Louisiana 25
Alabama 23
Kansas 21
Wyoming 20
Delaware 19
Kentucky 18
Hawaii 16
Oklahoma 16
South Dakota 15
Arkansas 13
District of Columbia 13
Rhode Island 10
West Virginia 10
North Dakota 8
Mississippi 7
Total US Breweries: 3,725

A table of all of this data is displayed to the right.
 
I acknowledge this map has limitations. For example:

  • Texas is ginormous – so 171 breweries really isn’t that impressive.  Actually, looking at breweries per capita by state may be more indicative of quality beer culture.  The Brewers Association does just that and found Vermont to be number one.  Wisconsin was an unfortunate number nine in 2011.
  • This data is from the Brewers Association’s Find US Brewery page and was retrieved on 10/8/12.  While I believe this list to be pretty comprehensive,
    1. Breweries throughout the US are constantly changing from year to year
    2. The list includes both “breweries in planning” and chains, such as BJ’s (counting multiple BJ’s locations in one state seems like cheating)
  • The Beer Mapping Project takes breweries in each state a step further and plots actual location. It’s very interesting to look at density of breweries in certain regions of the country. For example, while the above map shows that Illinois has 138 breweries, almost all of these are located in the Chicago area.

Regardless of Wisconsin’s rank, either by total breweries or breweries per capita, there is one thing that Wisconsin has that no other state does:
 
Spotted Cow Logo

December 29, 2011

Wedding Season

Weddings got real this year.  Real real.  So I plotted out my wedding attendance (to the best of my memory).  Check out that exponential growth (directly proportional to the amount of money I spent on wedding presents)!

 My Wedding Attendance Graph

 

1996

  • Laurie & Stan*

2003

2005

2008

2010

2011

2012

2013

2014

  • Doug & Lindsay
  • Dre & Tom
  • Shelby & Ethan
  • Jessica & Steve
  • Chris & Molly
  • Ashley & Rob
  • Our Wedding

2015

  • Mike & Jenna
  • Kailey & Al
  • Katie & Kyle
  • Bailey & Cody
  • Erin & Justin
  • Dan & Kerstin
  • Sam & Natalie
*Ring bearer *Crashed, not really invited

Why did my friends take a break in 2009?

October 28, 2011

The Packers Season Ticket Waitlist: Only a lifetime away

During the month of October, a lot of people (9,786 in Oct 2010) read my blog because of my blog post about possible Halloween costumes.  Throughout the rest of the year, my brother is pretty much the only reader.  So Dave, this one’s for you.  Towards the end of my High School career (not sure exactly when), I did what everyone else in the state of Wisconsin does – I added Dave and I to the Green Bay Packers Season Ticket Waitlist.  Ironically, in the days before stubhub and ebay, our Dad had a chance at some Packers tickets while he and our Mom lived in California for a few years.  If he found a way to pick them up, today I’d probably be sitting in section 120, row 10.  Roughly 30 years later, Dave and I got in on the ground floor of a 70,000 story building but the length of the season ticket waiting list has increased over the years. How long is the Packers Season Ticket Waitlist?

Every year, the Packers send Waitlist members a postcard to let you know where you stand on the list.  I haven’t always tracked my progress but in wading through facebook posts and old e-mails to Dave about our status, I was able to dig up the following data.
 

Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Season Ticket Waitlist Number 65,959 Data
unavailable
64,276 Data
unavailable
62,556 62,139 61,656 61,206 55,995 55,250 54,768
Estimated Year of Receiving Tickets   2082.5 2089.1 2095.2 2101.2 2094.6* 2094.4 2097.4

*Assumes no other seating expansions

Packers Season Ticket Waitlist Graph
 
The linear trendline for this data, y = -1172.4x + 68238, has an inflated slope because of the 2013 7,641 seat expansion which resulted in ≈5,000 season ticket holders receiving tickets.  This means a couple of things:

  1. Our true slope (excluding 2013) suggests an average decrease of 664.44 spots per year (not 1,172 spots/year as the linear trendline suggests).
  2. Finding the x-intercept (excluding 2013) suggests that our name will likely come up in ≈82.4 years (the year 2097.4).
  3. Winning clearly doesn’t help our cause. Unfortunately, an exponential trendline may provide a better fit but it’s just too depressing. I’m hoping that fluctuations in the Packers’ performance will smooth this out over time, making the linear trendline a better estimate. As a fan, however, I’m not sure I can handle fluctuations in their performance.

I’ll be sure to update this graph each year for the rest of my life…then pass it on to my grandchildren.

And for the record, I’m one spot ahead of Dave on the list.

March 26, 2011

The history of NCAA Tournament upsets

Every year I hear people say “the upsets this year destroyed my bracket.” While some years this is probably valid, most years these people (who are probably just trying to justify the hundreds of hours they spent filling out their bracket) are just making excuses. Nonetheless, I’ve always wondered what the real upset history in the NCAA Basketball actually is. Unfortunately, since the modern 64 team bracket structure just began in 1985, it really only makes sense to go back that far. So on my flight last Thursday, I did just that (and throughout the process felt a lot like Douglass Bates)…

A lot of people focus most of their bracket destruction excuses on the first round upsets. While this is perhaps the most memorable round of upsets, I will also consider the subsequent rounds and the total upsets in the entire tournament to evaluate just how prevalent upsets are from year to year. Additionally, since a nine seed defeating an eight seed is technically an upset, albeit not a large one, I will also consider the magnitude of the upsets in a given year by summing the total upset differential of all of the upsets which occurred.
 

 
1st Round
2nd Round
Sweet 16
Elite 8
Final 4
Championship
 
TOTAL
 
Average
Upset
Differential
#
Upsets
Total Upset
Differential
#
Upsets
Total Upset
Differential
#
Upsets
Total Upset
Differential
#
Upsets
Total Upset
Differential
#
Upsets
Total Upset
Differential
#
Upsets
Total Upset
Differential
#
Upsets
Total Upset
Differential
1985
7
33
6
37
1
3
2
7
1
6
1
7
18
93
5.17
1986
6
38
8
43
2
13
1
10
0
0
1
1
18
105
5.83
1987
9
45
5
23
2
11
2
6
0
0
0
0
18
85
4.72
1988
5
29
6
26
2
7
2
3
1
4
1
3
17
72
4.24
1989
12
54
1
1
4
9
1
1
2
3
0
0
20
68
3.40
1990
7
35
9
53
4
15
2
8
0
0
0
0
22
111
5.05
1991
9
57
0
0
4
12
1
2
2
3
0
0
16
74
4.63
1992
8
36
3
16
1
4
2
6
1
2
0
0
15
64
4.27
1993
6
36
4
12
1
4
1
1
0
0
0
0
12
53
4.42
1994
9
29
5
28
2
5
2
2
0
0
0
0
18
64
3.56
1995
8
48
2
4
2
6
2
3
0
0
0
0
14
61
4.36
1996
9
37
3
18
1
4
2
5
0
0
0
0
15
64
4.27
1997
7
39
6
26
1
3
0
0
1
3
1
3
16
74
4.63
1998
9
47
5
21
1
1
2
3
1
2
0
0
18
74
4.11
1999
12
50
7
44
3
8
1
1
0
0
0
0
23
103
4.48
2000
3
11
9
45
4
13
3
5
0
0
0
0
19
74
3.89
2001
13
65
3
16
2
8
2
3
1
1
0
0
21
93
4.43
2002
7
43
5
34
3
15
0
0
1
3
0
0
16
95
5.94
2003
8
30
6
26
2
2
3
5
1
2
1
1
21
66
3.14
2004
4
18
7
33
2
7
2
3
2
2
0
0
17
63
3.71
2005
8
38
6
28
3
8
1
3
0
0
0
0
18
77
4.28
2006
9
51
5
27
2
7
4
15
0
0
1
1
21
101
4.81
2007
5
13
5
10
0
0
2
2
0
0
0
0
12
25
2.08
2008
8
42
3
14
2
8
0
0
0
0
0
0
13
64
4.92
2009
10
46
1
1
2
2
2
3
1
1
0
0
16
53
3.31
2010
10
48
4
25
2
8
2
4
0
0
1
4
19
89
4.68
2011
6
30
4
31
5
13
3
18
0
0
0
0
18
92
5.11
 
Total
214
1048
128
642
55
183
44
101
15
32
7
20
463
2026
Average
7.93
38.81
4.74
23.78
2.22
7.26
1.74
4.41
0.56
1.19
0.26
0.74
17.44
76.19
 
Average Upset Differential
4.90
5.02
3.27
2.53
2.13
2.86
4.37

NCAA Tournament Graph

NCAA Tournament Graph

NCAA Tournament Graph

 

My Qualitative Observations:

  • 1985: As a number eight seed, the 1985 Villanova Wildcats remain the lowest seeded team to ever win the tournament. They also caused the largest Final Four upset in tournament history over number two seeded Memphis (upset differential of six) and the largest championship upset in tournament history over number one Georgetown (upset differential of seven).
  • 1985–1987: At the onset of the 64 team structure, Navy was good at basketball. Weird. Since these first three years, they have never made it back to the big dance. The highlight of these appearances was 1986 when Navy advanced to the Elite Eight.
  • 1986: The largest Cinderella team in tournament history (by inflicting the most total upset differential on its opponents) was number 11 seeded LSU in 1986. LSU defeated number six Purdue, number three Memphis, number two Georgia Tech, and number one Kentucky, on its way to the Final Four. LSU’s defeat of Georgia Tech was also the largest sweet 16 upset in tournament history. In this year, number 14 Cleveland State had a memorable run in the fairly new 64 team tournament structure, defeating number three Indiana and number six Saint Joseph’s. Little Rock had a memorable first round win over number three Notre Dame. This was also the season that the NCAA officially adopted the 19’9” three point line.
  • 1987: A memorable run from number 14 seed Austin Peay, who defeated number three Illinois in the opening round.
  • 1990: The year with the most severe overall upsets in tournament history was 1990, when the total seed differential of all upsets totaled 111. In 1990, the total number of upsets (22) was only one upset shy of the all time high, which occurred in 1999. 1990 also saw the most second round upsets (9) in tournament history. Although this number of second round upsets also occurred in 2000, the total second round upset differential in 1990, 53, makes this the most severe second round of upsets in tournament history.
  • 1992–1993: Michigan’s Fab Five made unsuccessful runs at two championships prior to ruining Michigan’s basketball program and Weber’s timeout. Who knows what would have come from a third Fab Five season, rather than a sort-of-fab four in 1994.
  • 1993: The total number of upsets in 1993 (12) is tied for the least all time. This number also occurred in 2007.
  • 1997: During my freshman year at the University of Minnesota, I tried to be a gopher fan. I really did. However, their underperforming football and basketball teams made being a Minnesota sports fan exhausting. During my review, it was strange to see Minnesota (1) make a run to the 1990 Elite Eight, (2) make a run all the way to the 1997 Final Four, and (3) be a 1997 one seed. I realize that it recently became “tubby time” up north, but I don’t expect to see this ever happen again in my lifetime. Perhaps this is like my name coming up in the Green Bay Packers season ticket waiting list (currently 62,139th) and my kids can expect to see it happen in their lifetime.
  • 1999: The most upsets in tournament history (not factoring in seed differential) occurred in 1999 with a total of 23 upsets.
  • 1999–2001: From 1999 to 2001, Gonzaga busted brackets like it was their job, defeating six teams for a total upset differential (difference in seeds) of 33.
  • 2000: The fewest first round upsets in tournament history occurred in 2000, with only three. In this year, the smallest first round total upset differential, 11, also occurred and Wisconsin, the greatest team in the history of college basketball, advanced to the final four.
  • 2001: The most first round upsets in tournament history occurred in 2001. That year, 13 upsets occurred in the first round for a total upset differential of 65 (this is also the largest first round upset differential in tournament history). The average seed differential in these 13 first round upsets was 5.0.
  • 2002: The largest average upset differential in tournament history occurred in 2002. Each upset this year averaged a seed difference of 5.94.
  • 2006: Davidson’s 2006 Final Four run was the second largest infliction of upset differential on its opponents in tournament history (a total seed difference of 27), behind only 1986 LSU. This was also the year that the NBA began requiring high school players to wait one year after graduation before being eligible for the draft, encouraging more players to pursue one-and-done college careers.
  • 2007: The least upsets in tournament history occurred in 2007, with only 12 (12 upsets also occurred in 1993, however, they were more severe). This year also yielded the least severe upsets in tournament history, when the total upset differential (difference in seeds) was a mere 25 and the average upset was by a seed difference of only 2.08.
  • 2008: The only year that all number one seeds made it to the Final Four.
  • 2009: The three point line was officially lengthened from 19’9” to 20’9.”
  • 2011: The most severe round of elite eight upsets in tournament history occured (considering total seed differential). Both VCU and Butler’s cinderella runs were memorable, but are still not as large of a seed differential as occured during LSU’s 1986 run and Davidson’s 2006 run.
     
  • 1985–1991: Although known today mainly for its buffets and Celine Dion concerts, Las Vegas used to have a basketball team. I was merely a young warthog at the time, so I don’t remember these years, but UNLV appeared in every tournament from 1985 through 1991 and advanced to the final four in 1987, 1990, and 1991.
  • 1991, 1993, 1997, 2001: The largest upsets in tournament history occurred four times in the first round 15 seed versus the two seed matchup (upset differential of 13). The games included Richmond over Syracuse (1991), Santa Clara over Arizona (1993), Coppin State over South Carolina (1997), and Hampton over Iowa State (2001). In tournament history, no 16 seed has ever defeated a one seed in the first round.
  • 1986, 1988, 1990, 2000, 2004: More second round upsets occurred in these years than first round upsets.
  • 1986 and 2006: The largest Elite Eight upsets in tournament history (both 11 seeds over one seeds for an upset differential of 10), occurred. The games included George Mason over Connecticut (2006) and LSU over Kentucky (1986).
  • 1986–2000: While Bob Knight wasn’t throwing chairs at Indiana, he was making an impressive run of tournament appearances. These included a 1987 National Championship, three Sweet Sixteens (1989, 1991, and 1994), a 1992 appearance in the National Semifinals, and a 1993 Elite Eight appearance. Later, while coaching Texas Tech, knight made four more appearances in the tournament in 2002, 2004, 2005, and 2007.
  • 2001-Present: Bo Ryan, the winningest coach in Big Ten history (among coaches with more than 5 years experience) with a 71.4% winning percentage, hasn’t missed the tournament since becoming the head coach at Wisconsin 10 years ago. Prior to Ryan, the badgers had only been to the tournament seven times in their history.
     

With upsets seeming fairly consistent since the inception of the 64 team tournament structure, contrary to popular belief, it doesn’t seem as though the selection committee has gotten worse at their job (although they stiffed Colorado pretty badly in 2011).

In all the years that I’ve finished last in my own pool, I think the less time I spend trying to predict upsets the better I do. These people will probably always beat me anyway.

My data and graphs spreadsheet is available here.

April 2, 2010

Athletic Prime: Men vs. Women

US Olympic Team – Average Age by Year
Year   Men Women All
1896 Summer 23   23
1900 Summer 23   23
1904 Summer 25   25
1908 Summer 26   26
1912 Summer 26   26
1920 Summer 26 19 26
1924 Summer 25 21 24
1924 Winter      
1928 Summer 24 20 23
1928 Winter 22.2 21.356 22.17
1932 Summer 25 21 24
1932 Winter 27.08 21.241 25.24
1936 Summer 25 22 24
1936 Winter 26.11 23.345 25.28
1940 Summer 28   28
1940 Winter      
1948 Summer 26 22 26
1948 Winter 27.01 21.035 26.09
1952 Summer 25 22 25
1952 Winter 25.32 20.252 25.03
1956 Summer 26 20 25
1956 Winter 26.25 20.21 25.29
1960 Summer 25 21 24
1960 Winter 24.17 20.094 23.2
1964 Summer 25 21 24
1964 Winter 26.09 21.036 25.1
1968 Summer 25 21 24
1968 Winter 24.17 20.275 23.28
1972 Summer 25 22 24
1972 Winter 24.16 21.315 23.26
1976 Summer 25 22 24
1976 Winter 23.33 21.033 23.05
1980 Summer 25 22 24
1980 Winter 24.24 21.273 23.33
1984 Summer 26 25 25
1984 Winter 25.02 22.229 24.14
1988 Summer 26 25 26
1988 Winter 26.1 23.278 25.19
1992 Summer 26 26 26
1992 Winter 26.04 25.059 25.29
1994 Winter 24.3 24.323 24.31
1996 Summer 27 27 27
1998 Winter 26.07 24.312 25.23
2000 Summer 27 27 27
2002 Winter 27.32 25.19 26.31
2004 Summer 27 26 27
2006 Winter 27.28 24.224 26.16
2008 Summer     26.8
AVERAGE: 25.4 22.4 24.9

Wednesday has long been known by many Madisonians as “wing night,” however, I’ve gotten tired of this guy at brothers and Brats’ wings are simply ok.  This week I discovered my new favorite gluttonous Wednesday activity at Chasers (formerly Quint-ins): 50 cent tacos.  They also have $1 high lifes, which doesn’t hurt.  While enjoying 10 tacos for $5, I was complaining about my plans to tackle a half marathon in two weeks and how my laziness has really gotten in the way of my training.  My friend Sam suggested to me that as a male, I’m just about in my “athletic prime,” so I should be ok anyway.  The idea that I, as a college student who eats QDoba at least once a week, might be in my athletic prime seemed ridiculous to me, so I thought I would check it out…

US Olympic Team - Men vs. Women Average Age

US Olympic Team - Men vs. Women Average Age (Source)

If the US Olympic data is any indication, I won’t be in my athletic prime for another 1.1 years. I’m sure that in this time, my athletic prowess will turn around on its own, and I’ll be doing this in no time.  I did find the Men’s and Women’s trend lines interesting, however.  I’m sure that a similar graph for China would look very different because of their crazy gymnast ages, but in the US, it appears that male and female Olympians are converging to similar ages, despite the averages over time being about a three year difference.

By the way, sexual primes, although variable, are believed to be between 18-22 for men and 35-40 for women.  Interesting that this occurs three years before the athletic peak for men, but 13 years after the athletic peak for women.

January 16, 2010

Finally punctuation we really need(insert SarcMarc)

Filed under: Nerdiness — Tags: , — Matthew @ 11:00 pm

I’ve written other posts on the difficulties of conveying tone over the internet and I’ve long viewed the written exclamation point as useless, unless preceeded by an expletive.  However, much to the chagrin of Strunk & White, it turns out inventing new punctation is possible.  Google News just informed me of the SarcMark.  My whole life I’ve been suffering with phrases like “lol,” “jk,” and “lmao.”  Now I have punctuation which truly captures my dry sense of humor   Possibly the greatest invention since the snuggy

December 17, 2009

Christmas List #1: Invisibility Cloak

Filed under: Creepiness,Nerdiness,Products — Tags: , , — Matthew @ 4:28 pm

For those of you who don’t know, while working on my master’s degree I’ve worked in the RFID Lab on campus.  Last week at one of our workgroup meetings, another Engineering Graduate student (the electrical kind) was presenting his recent research entitled, “RFID and Metamaterials: Now things get interesting.”  The title was misleading.  The incredibly theoretical presentation, along with a painfully practical audience made for what one would consider a “tough gig.”  However, a few minutes into the presentation, something was said that led me to believe that in the midst of my spacing out, J.K. Rowling had slipped up to the front of the room and taken over the presentation without me realizing it.

The negative indices of refraction present in many metamaterials has been demonstrated to provide a “cloaking” effect at microwave frequencies.

With metamaterials, awakward moments like this one may one day be avoidable

A cloaking effect!  Instantly, I stopped contemplating whether or not I would actually find a date to that weekend’s drumline formal (a high school homecoming-esque event that involves dressing up, dinner, and a lot more alcohol than dances in the Eisenhower cafeteria) and was completely engaged in the presentation.  The moment I had been waiting for since Harry Potter and the Sorcerer’s Stone had finally arrived: I could finally add an invisibility cloak to my Christmas list!  However, to my shock, the nerdy audience didn’t even acknowledge the incredible breakthrough mentioned by the presenter and the subject was quickly changed when the next slide read, “Metamaterials can be created in broad ranges of the electromagnetic spectrum as well as acoustics.”  Shit.

As disappointing as the remaining 20 minutes of the presentation were, science is acknowledging that metamaterials may one day make an invisibility cloak a possibility (due to 2008 research at UC Berkley, 2006 research at Duke, and research in Scotland).  Just imagine the possibilities:

  • I could have totally dominated the recent 3,000 person snowball fight on Bascom Hill.
  • Sneaking drinks into Summerfest would become a joke.
  • A few years ago I could have stolen Rob’s textbooks and he would have had no other choice but to go out with us instead of studying.
  • I wouldn’t miss a Packer Game at Lambeau for the rest of my life
  • Mess up Andrew’s immaculate bedroom

What would you do?

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