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Beta : Dad, can you fix the clock?
Me : Sure, but why is it not working?
Beta : My slider got away from me…

That was in the living room. Not the best place for pitching practice.

Gamma, pointing to a globe : What’s that line?
Me : That’s the equator.
Gamma : What’s the equator?
Me : It’s the middle of the earth.
Gamma : Then where’s the hot lava?
Me : That’s the middle of the inside of the earth. The equator shows the middle of the outside of the earth.

Me : Delta, what are you thankful for?
Delta : Lava.
Me : Okay. How about you, Gamma?

Delta’s answer to most things is “lava”.

Gamma : What’s the opposite of orange juice?
Me : Umm, apple slices.
Gamma : What’s the opposite of lemonade?
Me : Chocolate.

Gamma : Is fish the opposite of less?
Me : ???
Gamma : Because selfish is the opposite of selfless.
Me : Actually, it’s ish. Self-ish. So that would make ish synonymous with more.

Gamma : I just counted to 1000!
Alpha : You did not. That was too quick. What were you counting by?
Gamma : Thousands.

If it looks like a lot of quotes from Gamma, that’s because he’s doing a lot of talking.

Everyone familiar with timed sports (football, basketball, hockey, etc.) knows that the last minute of the game lasts a lot longer than the first minute of the game.

But how bad is it? And how does it change during the game?

I thought I would put together a chart showing the concept. I don’t have any actual data – I’m just going off my instinct here.

Maybe the chart is skewed toward the worst case, not average. For example, how long – real time – does the last 10 seconds of a close NBA game take? How many plays can occur in the last 15 seconds of an NFL game if a team is trying to rally a win? That is what I was thinking when I chose the Y-axis scale of multiples of game time. If 15 seconds of the game clock takes 2 minutes of my life, that’s a scale of 8x.

One of the more annoying aspects of sports is the delay that is part of the game but shouldn’t be. Example #1: intentional fouling near the end of a basketball game. Example #2: trying to ice the kicker for field goals in a football game. I hope at some point they change the rules to forbid those.

Any recommendations for the Y-axis scale?
Any other proposed changes to the rules to make the ends of games less annoying to the fans?

I was reading an article that summarized various studies that concluded that people form group affinities via pain. Pain might not be the only way to bond groups, but shared pain results in identification with and loyalty to that group.

That explains the emotions of the military, especially during basic training or deployments – new shared experiences of pain. And it explains why initiations are popular for fraternities or teams – it increases commitment.

Around the time of reading the article, I was also going through a DVD series on parenting and the family. And one of the incidental points that I took from it was that families need to be together. To bond.

So I combined those two thoughts and came up with this: we need a family activity that causes pain.

You know, to increase bonding.

But that sounds kinda bad – intentionally causing physical pain to one’s family.

Maybe it could be some other sort of pain other than physical pain.

That sounds worse though. What kind of torture is that?

Then I realized I don’t need to invent any activity for that purpose. There already is one, and we’ve already used it.

It’s the road trip.

It’s perfect – everyone is involved and everyone is put through pain. If not pain, then at least discomfort or annoyance.

And the key is that the whole family participates. It can’t be the parents putting the kids through pain. Because then the kids bond with themselves against the parents. You want the kids identifying themselves as part of the whole family.

To use a sports analogy: the parents need to be the captains of the team, not the coaches. You lead, but as a part of the team.

Anyway, find some fulfilling activity for the whole family. And if you all experience pain through it, don’t complain – it is strengthening your family.

For some reason, I’ve been reading books when it’s not summer vacation. Rather than wait until my annual summer book review and write an interminably-long post, I decided to write about them now.

Here they are, approximately in the order that I read them.

• 20 and Counting by The Duggar Family
  This is their life story, telling how Jim Bob and Michelle each grew up and met and everything. I don’t know what I expected before I started, but this book was more interesting than I thought it would be.

  If you have small kids, this book might give you some good ideas on ways to run things.

• The Closer by Mariano Rivera
  This was actually the youth version, not the full version. Beta picked it out at the bookstore. This also was more interesting than I expected it would be, although I did skip a bunch of about the last third of the book. The first part of the book was about his growing up in Panama and getting to the major leagues (not his plan, but he went along with it). Fine for all ages.
• Order of the Unicorn by Suzanne Selfors
  Beta was reading this through school. I forget if it was from the school library or a free-reading assignment or what. But I read it just to keep up with what is going into their minds. This is part of the imaginary veterinary series. The book wasn’t that memorable, but I suppose that’s okay because that means there’s nothing controversial in it.
• Wicked by Gregory Maguire
  Over 1 Million Sold!

  But not 1 million read.

  I doubt that many of the people who bought the book made it through that mess. We had tickets to go see the musical, so I thought I would get a head start and read the book. I started reading it but gave up. It was very crass. I thought it might get better, but about 10% of the way through it, my wife noticed I was reading it and said her friend told her not to bother with the book. So apparently it doesn’t get any better.

  If you’re thinking about reading the book: don’t do it.

  The musical is fine on its own, and does a fine job of removing the bad parts of the book. The currently-popular theme of villains not really being bad, just misunderstood, is still there. But there’s nothing you would censor for your kids, like you would for a lot of the book.

• Holes by Louis Sachar
  Good. One bad word. Interesting storylines.
• Animal Farm by George Orwell
  Not for kids. No reason for them to read it. What age is appropriate? Once they’ve had a government class in middle or high school, probably.
• Reclaiming the Sufficiency of Scripture by Rob Rienow
  Great book. I liked it so much I bought a few copies and mailed them to people. If you’re not going to watch his DVD series on marriage or his DVD series on parenting, at least read this book.
• A Reader’s Manifesto by B. R. Myers
  I thought this might be interesting, given a positive review I read.

  But it wasn’t.

  And the passages of bad writing that it critiques (or condemns) are not necessarily clean. I’d say avoid this book.

Okay, okay, it is 2015 at this point, but the results are headlines as 2014 because they match with the 2014 predictions made in 2014 for the 2014 season. Also, the results are not all-haiku, just the predictions were. A more accurate title would be “Results for the All-Haiku Predictions made in 2014”.

Before the bowl games commenced for this past college football season, I made some predictions. Here, for your reading enjoyment, is the tally of those predictions. Note that the results are not in haiku form, in contrast to the predictions.

Results

Here is the list (correct predictions in green, incorrect in red):

Nevada over ULL

Utah State over UTEP

Colorado State over Utah

Air Force over Western Michigan

South Alabama over Bowling Green

Memphis over BYU

Marshall over N. Illinois

San Diego State over Navy

Western Kentucky over Central Michigan

Rice over Fresno State

Louisiana Tech over Illinois

Rutgers over North Carolina

NC State over UCF

Virginia Tech over Cincinnati

Arizona State over Duke

Miami over South Carolina

Boston College over Penn State

USC over Nebraska

West Virginia over Texas A&M

Oklahoma over Clemson

Arkansas over Texas

LSU over Notre Dame

Georgia over Louisville

Stanford over Maryland

TCU over Ole Miss

Boise State over Arizona

Mississippi State over Georgia Tech

Auburn over Wisconsin

Baylor over Michigan State

Missouri over Minnesota

Oregon over Florida State

Alabama over Ohio State

Pittsburgh over Houston

Iowa over Tennessee

Kansas State over UCLA

Washington over Oklahoma State

Florida over East Carolina

Toledo over Arkansas State

Oregon over Alabama

And here are the results of the various forecasting methodologies (see the first year for description of the methodologies) (also, use the word methodologies if you want to sound important; methods would work just as well and is shorter) :

• Some Blog Site picks were 21-18 (similar to last year)
• CBS120 picks were 22-17
• HTW was 22-17 for the official Home Team Wins (HTW)
• HTW was 25-14 for the Geographical Home Team (GHT)
• Isaacson-Tarbell Postulate (ITP) was 22-17 if using HTW
• ITP was 23-16 if using GHT

I won’t analyze the results as much as I did last year, mainly because I had more time and more sleep last year. But it was a good year for all predictors – every method was over 50%. I just need to figure how to better predict outcomes. Especially against the spread.

Because of the disparities between institutions and between conferences, it is tougher to predict bowl games than NFL games. But one thing seems to be pretty consistent: if you don’t want to do a lot of research, just pick the team whose campus is closer to the bowl game.

Thoughts on the season’s results

I bet TCU agrees with me that an 8-team playoff would be an improvement on the current format of 4 teams. But 4 teams is better than the previous format of 2.

Conferences

Since the strength of the conference has something to do with the results, I thought I would tally each conference’s bowl game record for the 2014 (and the first bit of 2015) season.

• AAC: 2-3
• ACC: 4-7
• Big 10: 6-5*
• Big 12: 2-5
• Independent: 2-1
• MAC: 2-3
• MW: 3-4
• PAC12: 6-3*
• SEC: 7-5
• Sun Belt: 1-2
• USA: 4-1

* additional win/loss due to playoff + championship game

So the best conference was Conference USA (they won 83% of their bowl games) and the worst was the Big 12 (at 29%).

Or maybe the Sun Belt is the worst conference because they sent the fewest teams to bowl games again this year.

Perhaps you could say that the SEC was the best because they had 12 teams go to bowls. Or you could say they were just the most popular conference.

Perhaps you could say that the Big Ten was the best because they won the championship. Or maybe the SEC is the best because they won the most bowls (at 7).

Next year: playoffs again! TCU and I will be awaiting the expansion of the format to 8 teams. It might be too early to tell with only one sample year, but 8 seems to be the most reasonable number to whittle down 120 teams to a champion.

For a variety of reasons, I moved the Australian accent generator to its own site.

At the site Accenterator, you can generate not only an Aussie accent, but also Irish (needs work) and Mock Swedish (no one can tell if it’s wrong anyway).

Go visit the Accenterator and try some phrases.

It is time once again to update Some Blog Site readers on the results of my Some Fun Site project to create a more accurate football prediction method.

The 2014 NFL season is over, and here are the most accurate methods for predicting regular-season game results (wins-losses):

• MPWLS: 69%
• MPWHFA: 66%
• ITPLS: 66%

MPWHFA is listed first because it was one game better than ITPLS.

This year saw the addition of MPWHFA to the prediction methods. “MPWHFA” stands for More Points Wins with Home Field Advantage and contends that the team that will win is the team that scores more points than its opponents, adding a few points to the home team. It did great, capturing the long-term title among prediction methods. (For the ideas behind the methods, please visit the Some Fun Site page.)

And if you think you have a formula that can predict the winner of an NFL game better than 63.8% of the time, let me know and I’ll add it to the list.