Book Review- Million Dollar Arm

Million Dollar Arm
J.B. Bernstein, 2014


Good opportunity to learn some cultural differences between India and the U.S. while reading a sports book. India is crazy.

I haven’t seen the movie yet, but the book is decent. The author, a sports agent, isn’t particularly likeable, but seems to be good at what he does. An underlying theme is the author’s growth as a human being as he goes from helping rich athletes become richer to actually trying to change peoples’ lives and as he goes from pick-up artist to family man. He starts a reality-show-like contest in India to identify athletes who may have the ability to throw a major-league fastball. Long story short: there aren’t many options in crazy India and getting the few options that are there to work out is a ton of work—both physically and culturally.

Two Links Tuesday- September 16, 2014

10 Questions to Ask in a Job Interview: I especially like ‘What is the history of this position? Is it newly created? If not, why did the previous person leave it?’ and ‘What’s the company culture like? Do co-workers eat lunch together? Do you have regular team events?’

95 Student Discounts: Scroll to the bottom to see the fast food savings you could reap. I had no idea.

Book Review- A Funny Thing Happened on the Way to the Future

A Funny Thing Happened on the Way to the Future
Michael J. Fox, 2010

funny thing happened

Short book/audiobook of Michael J. Fox’s insights into receiving an education on the job. We listened to the audiobook on the way to vacation. It was written as an extended graduation speech to graduates, and this book contains a few nuggets of wisdom about succeeding in the face of adversity and seizing opportunities. Fox is known as an optimist, but fancies himself a realist in the book and describes how he reacted and thrived in the face of early-onset Parkinson’s disease. The book is a little interesting, but not life-altering.

While advertised/packaged as a gift for graduating high-school seniors, Maria and I think it is more relevant as a gift to high-school underclassmen. Get ‘em early.

Theory Thursday- Conditional Probability

Now that we know the Three Axioms of Probability, we can understand conditional probability.

First, let’s think about a normal (unconditioned) event. What is the probability of rolling an 8 with 2 normal dice (equally likely outcomes from 1 to 6)? Well, we can roll a 2-6, 3-5, 4-4, 5-3, and 6-2 with the two dice to get a sum of 8. That’s 5 possible outcomes that sum to 8. There are 36 possible outcomes, so the probability is 5/36.

The conditional probability of an event is the probability that the event happens, given that another event has happened or will happen. So, for example, what is the probability that I roll an 8 with 2 dice, given that the first die is a 2? Well, I would need the second die to be a 6 for them to add to 8, and there are 6 options for the second die. So I have a conditional probability of 1/6 of rolling an 8, given that the first die was a 2. The conditional probability of rolling an 8 given the first die is a 2 (1/6) is higher than the unconditioned probability of rolling an 8 with 2 dice (5/36).

What is the conditional probability of rolling an 8 with 2 dice, given that the first die is a 1? Well, we would need the second die to be 7. But the die only has options from 1 to 6. So we cannot roll an 8 with 2 dice if one of the dies is a 1. The conditional probability is 0.

We have an easy way to calculate the probability of a conditional event happening. Let E be the event we want to happen, conditional on the event F happening. Let P(E|F) be the conditional probability of E given F. Then P(E|F)=\frac{P(EF)}{P(F)}, where P(EF) is the probability of both E and F happening.

In our example with the dice, E=roll an 8 with 2 dice and F=roll a 2 with the first die. There is one way to roll an 8 with two dice and roll a 2 with the first die: 2-6. There are 36 possible outcomes, so P(EF)=1/36. P(F)=1/6 because there is a 1 in 6 chance of rolling a 2 with the first die. P(E|F)=\frac{1/36}{1/6}=1/6, as we found above.

Are Sports Broken?

Scott Adams thinks so.

My thoughts on his thoughts:
-Get rid of football? No, just play flag football. Way more interesting.
-Get rid of tennis serves and funky scoring? Yes please.
-Get rid of head balls in soccer? No, because that’s not what causes most concussions. Getting drilled from short range, falling awkwardly, or getting physically hit/headed/kicked by another player cause concussions.
-Make the soccer goal bigger? Maybe. Would be interesting.
-Get rid of offsides in soccer? No, because the defense would have to hang back all the time to guard cherry-pickers. There would be no break-aways. I hate the closeness of most onside/offside calls, but they seem relatively necessary to keep the game interesting.
-Add TV timeouts to soccer play? Why must soccer be TV-friendly like everything else? Why ruin uninterrupted play. Dumb suggestion.
-Add walls so that all soccer is indoor soccer? Yes, but only in the last 15 minutes of each half. I hate how they take so long to do throw-ins and goal kicks when time is running out and they have the ball and lead. Also, awesome moveable walls.
-All his baseball suggestions: No.
-Volleyball and golf suggestions: Don’t care.

My suggestions:
-In baseball, add an “acceptable lead-off line” past each base. The runner on that base can lead-off up to the line but can’t go past the line. The pitcher is allowed to try to pick off the runner, but each time he does, it counts as a ball to the batter. This will eliminate most pick-offs.
-In baseball, stop allowing the batter to leave the batter’s box. If the ball wasn’t hit foul, the batter must remain in the batter’s box, and the pitcher must pitch or try a pick-off within 10 seconds of receiving the ball. Any violation by the batter is an automatic strike; any violation by the pitcher is an automatic ball.
-In soccer, give teams a 1 minute, 30 second shot clock. If you don’t score, kick the ball out of bounds, or hit the goalie or the goal post within 90 seconds, it’s an automatic turnover. Shots in the air after 90 seconds count, the same way they do in basketball.
-In soccer, get rid of the referee timing. Keep a clock that counts down like in every other sport. It’s fine to have stoppage time still, just add it to the clock at the end of each half.
-In basketball, call fouls whenever the defender uses his arms to touch an opponent. Then eject players after 4 fouls. This would lower the incentive to foul and get rid of the physicality on defense. The game would be smoother.

We can fix this.

Theory Tuesday- 3 Axioms of Probability

Everyone has an intuitive concept of chance/probability. When we say that there is a certain probability of an event happening, what do we mean?

First, you need to understand the concept of an “event”. An event is one possible outcome of some probabilistic scenario. Say you are flipping a coin. The two possible events are “heads” and “tails” (though I guess you could argue that there is a third event: “coin lands on its edge”). As you will see in Axiom #3, since a coin cannot land on both “heads” and “tails, “heads” and “tails” are mutually exclusive.


There are three axioms upon which probability theory is built:
1. Let P(E) be the probability of an event. Then 0 \leq P(E) \leq 1. The probability of any event is between 0 and 1.
2. Let S be the set of all possible events. Anything that could possibly happen is contained in S. P(S) = 1. The probability of some event happening is 1.
3. Let E_1, E_2, …, E_n be a sequence of mutually exclusive events. Two events are mutually exclusive if only one of the two can happen at any time. P(\cup_{i=1}^n E_i)=\sum_{i=1}^n P(E_i). This says that you can add the probabilities of two or more mutually exclusive events together to get the probability of any one of them happening.

With these three axiomatic building blocks, all of probability theory can be built.

Two Links Tuesday- September 9, 2014- Model Building Edition

In Defense of Model Simplicity: Examples from Laura McLay about problems in data science and optimization that respond better to a simple model than a complex one.

Learning from the Best: Good write-up on Kaggle’s blog about suggestions from past data science competition winners. Spend the most time focusing on extracting the right features to solve the problem. Without the right features, it doesn’t matter how complex your model is, it won’t work.

Albert Einstein: “Everything should be made as simple as possible, but not simpler.”

Code Monkey Monday- Notepad++

If you like to read data in from text files or save lots of data to text files, you’ve probably discovered that Window’s default text reading program, Notepad, sucks. It can’t open large (MB or larger) text files, sucks at formatting, and seems slow. I prefer the freely downloaded program Notepad++. It can handle large files with ease, allows multiple text files to be open in the same program, highlights all equivalent words if a word is highlighted, gives line numbers, and probably has a ton of other capabilities that I’m not familiar with. You should upgrade to Notepad++.

Book Review- Think Like a Freak

Think Like A Freak
Steven Levitt and Stephen Dubner


I read this book over the span of perhaps 3-4 hours one afternoon. It was short. In following the Freakonomics blog, I had already seen/read podcasts of 3 of the book’s 8 chapters; I don’t think there were many surprises for me in the book. I also happened upon Stephen Dubner giving a public lecture in the atrium of IU’s business school in March/April, where he talked about the content of one of the chapters of the book.

I think the best advice from the book is to look for small problems to solve. Big problems are typically hard to solve, and you won’t be the first person to try to conquer a big problem. But a little problem may have been overlooked and may offer significant opportunity.

Do you think Steven Levitt and Stephen Dubner get into recurring fights about the proper way to spell their first names?