Well, at least over the last three weeks it did. In previous examples of my pub trivia team’s performance, we have had a lacklustre performance. But a few weeks we had an epic collapse. Having been in 4th place out of 10 in the penultimate round we ultimately finished in 8th out of 9—somebody left early—and 14 points out of first place. It probably didn’t help we put Beyonce down as the artist for three different songs. It probably really didn’t help that none of those artists were Beyonce. And it probably definitely didn’t help that we had no idea who those three artists were.
Then after a middling performance two weeks ago, last week we shocked even ourselves with our first victory since last autumn. Just how shocking? 19 points in that oft ill-fated music round. (It’s not really, but I’ll have to make another graphic about that.)
Credit for the piece is mine. Credit for the score goes to my teammates.
Last week my pub trivia team was debating whether our high score, although only good for second place—we lost by one point—was the highest. So this past weekend I scoured my sketchbooks for the last year and a half and reviewed our scores.
Alas, the earliest appearances were tally-free. And I did not record them consistently until this past autumn, but I had developed a decent system by last summer for the sake of comparing weeks.
Over the summer (not entirely captured) and autumn, we had a string of first-place finishes. Then we cratered towards the new year. And while we have strung together a couple of second-place finishes, we haven’t finished in first since last autumn.
In murders. Not the best of news, no. But this past March London saw more murders than New York. But as I was reading the BBC article this weekend, I wondered why the graphic they chose to use received as much prominence in the article as it did.
The chart as you can see occupied a full column width. But keep in mind, we are looking at a total of six datapoints: the murders for two cities in three months. While the story and data is significant, does the display of the data need to be?
The important point in the story is that in the past three months, London has surpassed New York in the number of murders. But the graphic supporting those six data points should not be overwhelming the significance of the text explaining the trend. After all, the data consists of only three points for two cities. If the data is displayed on an extended horizontal axis, it flattens the change and minimises the increase. To counteract that, the y axis should be increased, but then the amount of screen real estate being devoted to six data points is enormous. The better approach is to use a smaller graphic that displays the data in a better proportion, but also in a proportion that does not blow out the text of the story. The graphic to the right (and maybe above this blurb of text) shows how that can be done in a smaller space.
Credit for the original goes to the BBC graphics department.
Sorry, I ran into some technical problems this morning so this is going up this afternoon with an added bit at the end.
I’m not really sure this piece should go onto the blog. But I like it. And this is still my blog. So what the hell.
I grew up a big fan of games like Sim City, where you could create your own universes. And in the world of infographics, you do occasionally see the isometric drawings of cities, but I find they often lack representative value. Here, in this piece from Politico Magazine, we have the Bitcoin landscape.
The different buildings represent different elements of the cryptocurrency’s ecosystem, from supporting markets, regulators, utility companies, &c. Later on in the article, the different sections are broken out and labelled and annotated. Additional elements are also brought in to explain ancillary parts of the Bitcoin landscape. All the while keeping the same style. Very well done.
This detail looks at some of the things existing outside the specific Bitcoin environment, e.g. other cryptocurrencies. And the aforementioned utility companies that provide the necessary power for the computations.
I kind of wish the universe was larger, though. If only for the purely selfish purpose of getting lost in the illustrations.
Since I’ve had today to think more about this, it reminded me of one of my favourite projects I got to work on from a couple of years ago.
Unfortunately for me, my illustration skills are not quite top-notch. But I did get to direct a similar project, working with a talented designer—now expert craftsman—who can in fact draw. And since it’s not often I get to show this work, why not. We used consumer survey data describing the average middle class household to, well, visualise said middle class household. It took a lot longer than I think anyone thought, so we never attempted the style again. But the designer did some great work on this.
Credit for the Politico piece goes to Patterson Clark and Todd Lindeman.
Credit for the Euromonitor piece goes to Benjamin Byron and myself.
A few days ago, a confidential report by the British Treasury was leaked to the press. It confirmed what many had feared, that the economic forecasts for the regions of the UK were not that rosy under different models for different Brexit scenarios.
The scenarios looked at the change in growth for regions over the next fifteen years under three conditions: leaving the European Union, but remaining in the single market; leaving the single market but crafting a free trade agreement with the EU; and no deal, the so-called Hard Brexit.
I charted the data and it speaks for itself. Brexit is bad. The least worst option would be to remain in the single market. The North East, for my non-British readers that’s the area south of Scotland and home to Newcastle, is particularly not forecast to do so well in a hard Brexit.
As the debate rages on in the UK about how to proceed, the data should contribute to the conversation. While forecasts and projections can be wrong—what is the certainty of these forecasts, for example—it does make one wonder that if a better economy was a selling point of Brexit, do these forecasts make the idea of Brexit still worth it?
Data comes from the BBC. Credit for the design is mine.
Baseball season begins next week. For different teams it starts different days, but for the Red Sox at least, pitchers and catchers report to Spring Training on Tuesday. But the Red Sox, along with many other teams throughout baseball, have holes in their roster. Why? Arguably because nearly 100 free agents remain unsigned.
I do not intend to go into the different theories as to why, but this has been a remarkably slow offseason. How do we know? Well using MLB Trade Rumours listing of the top-50 free agents this year, and the signings reported on Baseball Reference, we can look at the upper and middle, or maybe upper-middle, tiers of free agency.
Kind of messy to look at with all the player labels, but we can see here the projected contracts, in both length and total value, along with the contracts players signed, if they have. And for context we can see how those contracts compares to the Qualifying Offer (QO). What’s that? Complicated baseball stuff that is meant to ensure teams that lose stars or highly valuable players are compensated, especially since they might come from smaller market teams that cannot afford superstar prices. The QO is meant to help competitiveness in the sport. How does it do that? Let’s just say complicated baseball stuff. We should also point out that some players, most notably the Yankees’ Masahiro Tanaka, were expected to opt out of their contracts and try the free market. Tanaka did not, which is why his projection was so far off.
So is it true that free agency is or has moved slowly? Consider that approximately 100 free agents remain unsigned as of late Thursday night—please no big signings tomorrow morning—and that of the top 50, 22 of them remain unsigned. And if we take the QO as a proxy for the best players in the game, add in two players who were exempt because baseball stuff, we can say that 8 of the 11 best players remain unsigned. Though, in fairness to ownership, three of those players are reportedly sitting on multi-year offers in the nine-figure range.
But if players are unsigned, does that mean they are competing for lower value contracts? Possibly. If we use MLB Trade Rumours’ projected contracts, because in years past they have proven smart at these things, we can see that for the 28 who have signed, it’s a roughly even split in terms of the number of players who have signed for more or less than their projection. Sometimes however, non-monetary factors come into play. Two notable free agents, Todd Frazier and Addison Reed, both reportedly signed lesser value contracts to play closer to a specified geography, in Frazier’s case the Northeast and in Reed’s the Midwest.
But the telling part in that graphic is not necessarily the vertical movement, i.e. dollars, but the horizontal movement. (Though we should call out the cases of Carlos Santana and Tyler Chatwood, signed by the Phillies and Cubs respectively, who did far better than projected.) Consider that a team might not have a lot of money to spend and so might extend a contract over additional years, offering job security to a player. Or in a bidding war, the length of the contract might be what leads a player to pick one team over another. In those cases we would expect to see more left-to-right movement. So far we have only had one player, Lorenzo Cain, who signed for more years than expected. Most players who have signed for less have also signed for fewer years. Note the cluster of right-to-left, or shorter-than-expected, contracts in the lower tiers versus the small, vertical-only cluster in the same section for those signing greater than projected contracts.
Lastly, are these trends hitting any specific positional type of player? Well maybe. Ignoring the market for catchers because of how small the pool was—though the case of Jonathan Lucroy as the unsigned catcher is fascinating—we can see that the market has really been there for relief pitchers as there are few of the top-50 remaining on the market. Starting pitchers and outfields, while with quite a few still on the market, have generally done better than projected. But infielders lag behind with numerous players unsigned and those that have signed, most have signed for less than projected.
But at the same time, I would fully expect that once these higher level free agents come off the board—while one would think they would certainly be signed, who knows in such a weird offseason as this—the unsigned middle and lower tiers will quickly follow suit.
Of course none of this touches upon age. (Largely because lack of time on my part.) Though, in most cases, getting to free agency in and of itself makes a player older by definition the way baseball’s pre-arbitration and arbitration salary periods work. (Again, more baseball stuff but suffice it to say your first several years you play for peanuts and crackerjacks.)
Hopefully by this afternoon—Friday that is—some of these players will have signed. After all, baseball starts next week. If we are lucky this post will be outdated, at least in terms of the dataset, come Monday. Regardless, it has been a fascinating albeit boring baseball offseason.
Credit for the data goes to MLB Trade Rumours and Baseball Reference.
Well there was a lot to poke and prod at in last night’s State of the Union. So over the next couple of days I will be looking at some of the data. I wanted to start with something I could look at over breakfast—unemployment rate data.
President Trump claimed unemployment rates are at the lowest rate in…I forget how many years he claimed. But in a while. And he is correct. But, as this chart shows, he entered office with unemployment rates very near those record lows. A few tenths of a percentage point lower and voila, all-time low. What the data shows is that the bulk of the fall in the unemployment rate actually came under the watch of the Obama administration. The rate peaked at the end of the Great Recession at 10% before falling all the way down to 4.8%, which is about the natural unemployment rate that is somewhere between 4.5% and 5%, what you would expect in a healthy economy.
Data is from the Bureau of Labour Statistics, chart is mine.
Today’s post is a very quick reaction to the news last night about President Trump calling Haiti, El Salvador, and African countries “shitholes” and trying to get rid of immigrants from those countries in favour of immigrants from places like Norway.
Norwegian contributions to American immigrants peaked well before the 21st century. At that time, Norway was poor and lesser developed. The data was hard to find, but on a GDP per capita level, Norway was one of the least developed countries in Western Europe. On a like dollar-for-dollar basis, El Salvador of 2008 is not too far from Norway 1850.
I wish I had more time to develop this graphic for this morning. Alas, it will have to do as is.
A story over the last several days you may not have heard about concerns the disappearance of the ARA San Juan, an Argentinian Navy submarine. Here in the US and over in the UK, we use rather large nuclear-powered submarines. They can travel the world underwater without ever coming up for air. But most of the rest of the world uses much smaller diesel-electric submarines. They have to come up for air every couple days, like in all those World War II submarine movies.
As you know, these kind of stories are right up my alley and I wanted to try and explain the story visually. Unfortunately, it took me way too long to illustrate the two submarines you will see. So instead, we have more of a comparison of the San Juan, a Type 1700 submarine, and the movie-famous American Los Angeles class attack submarine.
I had a lot of other things planned, but had to drop them. The point is that the Argentinian submarine is a lot smaller, has fewer crew, but needs to come to the surface in the next day or two, most likely. Time is beginning to run out.
This week I covered a lot of Red Sox stuff. (And I received some great feedback from people, so maybe more baseball-related stats things will be forthcoming.) But, since it is Friday, I wanted to keep today late. So over breakfast I worked on a flowchart to help you choose whom to root for in the playoffs now that Boston, Colorado, Arizona, Minnesota, Washington, and Cleveland have all been eliminated.
To be fair, my second choice was good old Terry Francona and the Indians (like last year). But, the Evil Empire is returning.