How Canada's Plans to "Own the Podium" Failed

This year at the 2010 winter Olympics, Canada made moves to shed its humble image just a bit with a program they titled "Own the Podium." China was successful with a similar program called "Project 119" during their 2008 Olympic hosting, in part because of their willingness to invest heavily in relatively unpopular, but highly medalled categories.

But, Canada has largely failed to win medals, and Nate Silver suggests it has to do with their investment strategy. A quick graph illustrates this nicely:

Canada has over-invested (relative to the medal count) in its "heritage" sports like curling and hockey and under-invested in sports like biathlon and cross-country skiing -- sports that would be good targets both because they are medal-rich and because they are not professionalized.

You might expect to see an investment strategy based on those two criteria:

• High medal density: each dollar spent will increase the odds of winning several medals at once
• Lack of professional financial support: each marginal dollar spent will have a greater impact

That's just not what we see in the graph. Instead, it appears that they're just trying to avoid the embarrassment of losing in their traditional areas of strength. Ironically, by setting less amitious objectives, Canada increased the chance that it could all go sideways with a single loss.

It looks like "Own the Podium" was more about avoiding embarrassment than dominating the competition. How Canadian.

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VCs' blogs do not appear to drive web traffic to their funds

A classmate of mine from HBS, Rob Go put up an interesting post yesterday about the relationship between venture capitalists’ website traffic and blog traffic. In short, he found that there was very little correlation between the two. I thought a graph might clarify the data:

It appears that most VCs are tightly clustered around 10,000 hits/month to their websites (Sequoia and First Round Capital standing as outliers, but excluding those, the standard deviation was ~2,000 hits). What Rob (and I) found surprising was that while blog traffic varied widely, it didn’t appear to affect website traffic.[1] If we assume that website traffic is a loose proxy for entrepreneurs’ interest in a fund (as opposed to blog traffic, which seems to indicate interest in the person writing), that seems to indicate that blogs may be building independent brands for the entrepreneurs, but it doesn’t (from this data) appear to be increasing deal flow.[2]

This really isn’t enough data to draw a conclusion, but it does raise the question for me: “If not increasing interest in their fund, what value do VCs’ blogs deliver?”

1. The best fit trendlines are all negative (i.e., a negative correlation between website and blog traffic), and statistically insignificant (R-squared<.1). This remains true even when removing the sites with zero blog traffic or when removing the website traffic outliers.

2. Yes, website traffic is a *very* loose proxy. Yes, the blogs could be delivering value by helping entrepreneurs focus on the funds more suited to them, lowering website traffic, but increasing lead quality. But, website traffic still seems like a very preliminary step in investigating a fund; I’m surprised there isn’t a stronger correlation.

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Closer still

To continue my self-analysis of exercise routines, and specifically to follow up on my squash post, @Bain asked the following: “I'd love to see win percentage by game # within a match. I'd guess that Steve was 75% in the first two games; I was 75% in the third and fourth games, and we were even in game five.” His hypothesis sounded right to me—I also perceived that I tended to come out strong, then fade. Turns out, we were wrong again.

Here are the totals for the full set of games. I think that past the first match we've got some pretty small sample sizes and weird incentives with added on 1 or 3 game sets[1]:

But, this isn’t exactly right, since matches don’t always stretch to five games. Someone’s going to try a lot less hard in game 5 if they’ve already lost the match. In the match-relevant games[2], here is my win percentage by game:

It looks like I had a *slight* edge in game 1, Alex had the edge in 2/3 and I completely dominated Game 4 (reflecting, in part that it's often a "must-win" for me, and in part that I tend to win matches 3-1 and Alex tends to win them 3-2). A final note is that within the games that determined matches we're 44-38 in match *games* (my advantage) even though we're 10-9 in matches. I've won more matches 3-1 while Alex has won slightly more 3-2. Here's how our match scores have broken down (again, all from my perspective)[3,4]:

Put one way, Alex converts his game wins more efficiently into match wins than I do.

1. E.g., “Now that I’ve lost, let’s bet lunch that I can take game 6”*

2. (ignoring games after the match was concluded; e.g., counting only the first four of a LWLLW match -- this is why there aren't 18 games for Game 4 and Game 5)

3. There's one match missing because I recorded only that Alex won the match, not the game totals (methodologically, I also credited Alex with one game in the game totals, since you must have taken *at least* one game more than I did from the first five).

4. Also, methodologically, I’ve got two fewer match win/losses in this analysis than I did in the last one because I excluded three round robins in which we played two games against each other (result: 2-0, 1-1,0-2) for simplicity.

*Most matches included a wager on the match. A post-game Gatorade was common, as was a beer (though those rarely got redeemed). Big bets were usually lunch. Oddly, the post-match bet was often higher stakes than the first bet; e.g., a beer following a Gatorade, or the loser had to listen to a podcast of the winner’s choice or purchase and read a book of the winner’s choice.

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As close as it gets

I’ve been keeping a log of working out since 2003. For the last ~12 months, I’ve been recording the game-level detail of squash matches as well (e.g., WLLWL for a 2-3 loss). I’ve been playing @Bain since 2008, and we’ve made some jokes about how our matches have always seemed very even, but I realized this week that I have the data to test that. I did a quick look through my data and sent off this email to most frequent 2008-09 squash partner:

“So, what I have learned (in addition to the depressing stat that I've averaged 9.5 minutes/day of working out since December 2003) is that Alex and I are 11-10 in matches and 60-60 in games. That's pretty much as close as it gets. Awesome.”

Alex posted this to Twitter with the aside, “I'd thought it was much closer :-)”

Turns out, he was right. Alex had a suspicion that he had a huge advantage in the first few months we played, and that more recently I’ve taken charge. Nope – if that were true, you’d see his game total climb much faster than mine, then see me catch up. Not the case:

In fact, over 120 games, neither of us have ever been ahead by more than five games:

Not only that, but squash is notoriously streaky. If that were true for Alex and me, you’d expect wins to tend to be followed by wins and for losses to follow losses. Or, perhaps each win takes so much out of the winner that he tends to lose the next game. Nope, once again completely even. Following a win, I was 30-29. Our games are exactly as predictable as a fair coin: dead random.

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Red Spidering Wikipedia

Occasionally websites are overwhelmed by the amount of traffic they receive. This is often the result of a Distributed Denial of Service (DDoS) attack in which thousands of computers all try to connect to the website at once. However, sometimes it happens as a result of a popular site (one with millions of visitors) linking directly to a much smaller site, unprepared to deal with the traffic.

This is sometimes called the Slashdot Effect for the popular metablog, Slashdot, although other phrases like being “Farked,” “Drudged” or “Wanged” are also common. Slashdotting can overwhelm a server, or it could just represent a large increase in traffic. What I found interesting recently was that the comic xkcd produced a similar bump in traffic, but without a link. This comic from a few months ago referenced the Voynich Manuscript, a 15th century undeciphered illustrated book.

xkcd is known for a geeky following, but this was a bit too obscure. Wikirank shows a 10,000% increase in wikipedia traffic.

I’d call this indirect effect “red spidering” or “a velociraptor attack.”

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Infinite Failure meets Unbounded Optimism

I've been participating in Infinite Summer, a challenge to read David Foster Wallace's Infinite Jest during 2009's 13 weeks of summer. I greatly enjoyed his nonfiction books, A Supposedly Fun Thing I'll Never Do Again and Consider the Lobster, so I figured I'd give Infinite Jest a chance. Here's the rub: it's more than 1,000 pages long.

Infinite Summer set up a schedule to help people get through it (as well as some great content guides and guest posts by authors, professors, etc.). My problem is that after a strong start, I seem to be falling behind (a real problem, with constant reminers from my friends on Twitter using #infsum).

I'm falling behind at my current rate, and slowing down: a deadly combination. Nevertheless, my Infinite (-related) Failure can be overcome by Unbounded Optimism today (and every day that I haven't yet caught up)....

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Cambridge Brewing Company has Perfect Coasters

Last night I had a beer with my father and two of my friends at the Cambridge Brewing Company. When we first got there, we commented on how much we like their logo of three beer beer rings. It's classic, communicates the brand perfectly, and unlike most coasters, is free of advertising.

Of course, with coasters like that, we were going to have to turn them over and draw graphs. One of my friends quit his job recently to move to San Francisco and just yesterday came to the realization that his living expenses are about to go up 30% (Boston to San Fracisco move) while his income goes down 100%. He's excited about the change.

Just saying it out loud gets the point across, but somehow these graphs always get made in both draft form (back of a coaster) and polished form (PowerPoint). The high quality, adverising free, blank-on-one-side coasters at the Cambridge Brewing Company are a wonderful thing. It's funny how something done in pen on a coaster in 30 seconds can be more compelling than something done in PowerPoint in 10 minutes....

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The importance of asking questions

I’ve been giving a lot of presentations recently at work. We’re rolling out a Six Sigma-like cost savings methodology across a large corporate client and so I’ve sat down with groups of 3-30 a couple times per day to explain what it entails. After about 30 iterations, I’ve got the information-giving down pat. But, I’ve given presentations before. What I’ve been reflecting on recently is the importance of asking questions at the end.

Questions are important to help listeners clarify the material, but they also help listeners demonstrate understanding and set themselves apart from the other members of the audience.

I hit the end of the presentation after 20 minutes, which leaves about ten minutes for questions. My audience often take this as an invitation for further information to flow from the presenter to the participants. This is partly true, but not entirely. If, at the end of a presentation, someone’s unclear on some part of what’s been explained, by all means they should ask a question (but only if they’re reasonably certain that their confusion is at least somewhat universal, to avoid wasting everyone’s time. If they can’t tell, they probably should ask later, in private). A well-asked question serves both the questioner and the audience, as they all learn something.

However, a different sort of question is also available. Asking about an implication of the presentation or a subtle detail that might have been overlooked can demonstrate to the presenter that someone has paid attention and is engaged with the material. This can accumulate into awareness if the same person asks that sort of question in several presentations over time. Of course, there’s a danger that the questioner can end up wasting time with a question just meant to score points. It’s a technique to be used sparingly.

Maybe this is all just a cry for greater engagement from my audiences.

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I'm less popular than "Current Resident"

Sarah gets a fair bit of mail based on her professional status. Every day brings at least one piece of mail offering her (what seems like) enormous sums of money to come be a surgeon in a desperately unattractive location. They seem unable to screen for the fact that she’s currently in year two of a six-year program. She also subscribes to several journals and magazines. I, on the other hand, receive household bills and little else. The result? Sarah gets more than ten times as much mail as I do. In fact, we receive more mail addressed to “Current Resident” than to “Steve Davis.” I only received more mail than this accursed “Resident” on two days out of the last 30. Sigh.

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Californians more motivated by Gay Marriage than Obama v. McCain

With nearly the entire vote in, California has produced a very stranger result. Residents had the opportunity to vote in the presidential race as well as on 12 statewide propositions and a number of local and regional elections. Turnout in presidential elections is normally up compared to non-presidential years, and is partially driven by people who vote for president, but leave the rest of their ballot blank.

However, this year, it appears that an even larger number of people turned out to vote exclusively on Proposition 8 (from the LA Times with 95.4% reporting).



I can imagine the sort of person who would cast a presidential-only ballot, but fail to read through the propositions. I have much more difficulty imagining the ~30,000 people who went in to vote on just Proposition 8, and while they were there, decided not to fill in a bubble for president.

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Good argument, questionable chart

The New York Times had a graphic today showing how the economy fared under Democratic and Republican presidents since Herbert Hoover. They seem to be making a shortened and simplified version of the argument presented by Larry Bartels in his book Unequal Democracy (For those who don’t have a book-length period of free time, Steve Benen summarizes).

While I think Bartels’ argument is fascinating, I’ve really got to take issue with the Times' graphic. They obscure the progression of time and the length of term that each president had. Yes, the S&P 500 grew 10.8% under Gerald Ford, but he was only president for about 2 years. And yes, the S&P 500 grew 15.2% under Clinton, but was that his economic genius, or the continuation of a trend started 20 years earlier and lasting through three administrations under both parties?

I think the time series clarifies things greatly. Here’s a recreation of the original NYTimes graph, which sorts by party and orders by growth rate:

Here's a new one that orders by year, and shows term length:

I think the new chart does a much better job of showing the sequence of presidents, which helps the reader understand larger trends. Maybe the economy is more likely to grow under a Democratic President than a Republican one, but if that's the case, I'd like to see it shown more robustly.

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Why I'm in love

The other day I was reading xkcd and came across this fabulous comic.


It really spoke to me, since I think one of the greatest parts of a relationship happens when one partner recognizes and indulges a socially unpopular part of the other. It might be embracing something geeky like in this comic, or providing a hidden pleasure like Peeps, but it’s touching when it happens. Me – I like graphs.

For my anniversary with Sarah, one thing I got her was a pack of “fruit”-flavored Mentos, which we always have enjoyed on our vacations (consumption-based enjoyment, not science experiment enjoyment). The next day she sent me this graph of the contents of the Mentos pack.


I'm in love.

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My early efforts at investing were unsuccessful

I don't fully subscribe to the University of Chicago's disbelief in alpha, but even if there are people who can successfully pick stocks that will perform in excess of their risk-adjusted expectations, I am certainly not among them.

Fortunately, I learned this lesson early in life, with my first (and so far only) investment in an individual stock: Stratos Lightwave. I made my purchase after getting involved in an investment club my sophomore year of college whose sponsor advised everyone to "put a token amount into a stock you choose; this will give you the motivation to follow the market."

It didn't go as well as I'd hoped:


Early experiences have a funny way of having outsized influences on our later lives, but I was more or less convinced by this to stop picking stocks, and leave my money in index funds. Of course, if you'd like to prove me wrong with a can't-lose stock, feel free to drop me a line.

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Sleep greatly impacts my productivity

Some days seem so productive. Other days, not at all. I find that the amount of sleep I've gotten is the best predictor. I wonder if inability to do work when fully rested is just a visceral reminder that humans aren't meant to sit still for 60% of their waking hours.

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Seasonality lowers the 2008 projection

An unknown Ken brings up a good point about my annualization of 2008 numbers in an earlier post about exercise. He asks if there is a seasonal effect, for instance, a spike in activity in early January while New Years' resolutions are still fresh. I don't think the particular example is right since I tend to make resolutions like "Spend more time at charity events," or "Save money elsewhere to spend it on occasional fancy groceries," but I acknowledge there may be seasonality.

Other than a consistent spike in July (a beautiful outdoor month in Boston), it's pretty hard to see the pattern in this data.

One thing that is clearly highlighted is my 2007 effort to train for my first marathon (the red line that jumps up in February). I went out hard, and while you'd hope to see that line trending upward as the mid-April race date approached, it actually trended down, revealing the results of my increasing knee pain.

Another big jump comes from a decision to start lifting weights in the spring of 2008. That heightened level of activity may be unsustainable, and points to a regression to pre-2007 levels unless I maintain the weight-lifting goal, or establish a new one.

However, the question remains – is there a difference between the seven months of data I've collected and the rest of the year? This next graph should clarify the issue:

Using this new information, we can prepare new estimates for the 2008 full year. With 205 days on record, we can figure the number of remaining projected workouts by multiplying 60 sessions by (365-205)/205 and then applying a 25% discount and arrive at a total of 35 additional sessions (as opposed to the original estimate of 41).

While this doesn't change the previous conclusions, which were based on year-over-year changes, and not just the 2004-2008 change, it does make the increase in '08 seem more reasonable, although 2008 still projects to be quite an increase over past years:

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Workout length poised for a regression to pre-graduate school levels

It appears that 2004-2006, I averaged about 50 minutes per session, while in 2007 and 2008 I averaged about 20 minutes more. The most obvious driving force here is that I attended graduate school September 2006-June 2008, which left me with much more free time than when I was working.

So, what caused the longer sessions? Was it simply that I didn't have work waiting for me at home, and that allowed me to run farther? Partially, yes. I began playing squash on weekdays, something that had been strictly a weekend pursuit for me in the past. That sort of gain is likely to be reversed. Then again, having more time off also inspired me to set larger goals. I ran a marathon in the spring of 2007, and started lifting weights in spring of 2008, both of which made me spend more time at the gym. Those gains may be maintained.

A shift in the type of exercise might also help explain the change in workout length, but the exact composition and its change is unclear. It's also unclear why 2006 shows a decrease in workout length when the last 6 months were in graduate school or on vacation.

It seems clear that when predicting the future, the rise in number of workouts could be sustainable, but that the increase in workout length may or may not be in for a regression to the historical mean, depending on whether changes in exercise mix and goals or weekday squash was a larger driver of the 2007-2008 increase.

Of course, there is a significant observer/actor bias, but we'll assume that exercise is driven by stronger forces than graph creation.

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Number of workouts per week has strongly driven increase in exercise since 2004

Last time I looked at how much I've been exercising over the past five years. It looked as though exercise has been increasing, but I wanted to know why. The first question to address is how more frequent sessions and longer sessions have impacted total exercise. Have totals been padded because I've made exercise a more integrated part of my life or because I've had more time to spend at the gym? First let's look at frequency of workouts:


This shows a very steady growth of ~10 extra sessions/year. I'd expect this data to be pretty noisy since the decision to exercise or not on any given day is based on so many factors, and because the data refers to ~50-70 events per 365 days. Nevertheless, four years of increases of similar magnitude is enough to convince me that something is going on.

I interpret this as a steady integration of exercise into my daily life. While I did occasionally work out in the years before 2004, it was mainly pick-up sports at infrequent intervals. I had never jogged, never used a weight room (with the exception of 3 months in 2000), and never set goals to improve my endurance, strength, flexibility, or agility.

What this means for the future is that I would expect this trend of increasing exercise to continue and gradually level off. This stands in contrast to the other factor responsible for my increase in total exercise time, which I will investigate next: length of workout.

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Time devoted to exercise has been growing

Since December of 2003 I've kept an exercise log. It started as a way to track how far and how fast I ran. At first glance it looks like I've increased the amount I've worked out pretty steadily over the past five years. The graph raises a number of questions, though. Why has exercise time gone up? Has it been from longer sessions? More frequent workouts? Is it driven by free time or is it independent of free time? Are the averages even over the years or do they represent periods of intense activity separated by periods of sloth?

Clearly, this needs some more attention.

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