Baseball’s Free Agency Problem

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.

The upper tiers of baseball's free agent market, as of 9 February
The upper tiers of baseball’s free agent market, as of 9 February

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.

Comparing the signed to the unsigned free agents
Comparing the signed to the unsigned free agents

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.

How are the signed players doing versus their contract projections
How are the signed players doing versus their contract projections

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.

Are there any trends at the position level
Are there any trends at the position level

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.

The World Grows On (Part III)

A few days ago I posted about the front cover graphic for the New York Times that used a choropleth to explore 2017 economic growth. Well, this morning whilst looking for something else, I came across the online version of the story. And I thought it would be neat to compare the two.

A very nice graphic
A very nice graphic

Again, nothing too crazy going on here. But the most immediately obvious change is the colour palette. Instead of using that green set, here we get a deep, rich blue that fades to light very nicely. More importantly, that light tan or beige colour contrasts far better against the blue than the green in the print version.

The other big change is to the small multiple set at the bottom. Here they have the space to run all twelve datasets horizontally. In the earlier piece, they were stacked six by two. It worked really well, but this works better. Here it is far easier to compare the height of each bar to the height of bars for other countries.

Credit for the piece goes to Karl Russell.

Gerrymandering Pennsylvania

Here in Pennsylvania this week, the state Supreme Court will hear arguments on the legality of congressional districts drawn by Republicans in 2010. The state is rather evenly split between Republicans and Democrats, e.g. Donald Trump won by less than one percentage point or less than 45,000 votes. But 13 of its 18 congressional districts are represented by Republicans, roughly 72%.

This graphic is from the New York Times Upshot and it opens a piece that explores gerrymandering in Pennsylvania. The graphic presents the map today as well as a nonpartisan map and an “extreme” gerrymander. The thing most noticeable to me was that even with the nonpartisan geography, the Democrats are still below what they might expect for a near 50-50 split. Why? One need only look at Philadelphia and Pittsburgh where, using the Times’ language, the Democrats “waste” votes with enormous margins, leaving the suburban and rural parts of the state open for Republican gains.

Three different ways of drawing Pennsylvania's congressional districts
Three different ways of drawing Pennsylvania’s congressional districts

Credit for the piece goes to Quoctrung Bui and Nate Cohn.

The NHS Winter Crisis

In the United Kingdom, the month of January has been less than stellar for the National Health Service, the NHS, as surgeries have been cancelled or delayed, patients left waiting in corridors, and a shortage of staff to cope with higher-than-usual demand.

But another problem is the shortage of hospital beds, which compounds problems elsewhere in hospitals and health services. The Guardian did a nice job last week of capturing the state of bed capacity in some hospitals. Overall, the piece uses line charts and scatter plots to tell the story, but this screenshot in particular is a lovely small multiples set that shows how even with surge capacity, the beds in orange, many hospitals are running at near 100% capacity.

Some of the worst hospitals
Some of the worst hospitals

Credit for the piece goes to the Josh Holder.

The Internationalism in Sport

Whilst away, I came upon this piece in the following of my offseason baseball news. The New York Times published it between Christmas and New Years and the piece looks at the origins of sports persons in European football leagues compared to several American sports leagues, including American football, baseball, and basketball.

I was most confused by US women's football, which I had not realised has not been a single continuous organisation
I was most confused by US women’s football, which I had not realised has not been a single continuous organisation

The piece features an opening set of small multiples comparing all the leagues. Maddeningly, I wanted details and mouseovers and annotations at the start. Fortunately, as the reader continues through the article, each small multiple becomes big and the reader can explore the details of the league.

Credit for the piece goes to Gregor Aisch, Kevin Quealy, and Rory Smith.

How to Choose the Match to Broadcast

I was reading the Sunday paper yesterday and whilst I normally skip the sports section, especially during baseball’s offseason, this time a brightly coloured map caught my attention. Of course then I had to read the article, but I am glad that I did.

On Sunday the New York Times ran a print piece—I mean I assume I can find it online (I did.)—about CBS chooses which American football matches to air in the country’s markets. It is a wee bit complicated. And if you can find it, you should read it. The process is fascinating.

But I want to quickly talk about the design of the thing. Remember how I said a map caught my attention. That was pretty important, because the map was not the largest part of the article. Instead that went to a nice big photo. But the information designer I am, well, my eyes went straight to the map below that.

The story dominated the section page
The story dominated the section page

There is nothing too special about the map in particular. It is a choropleth where media markets are coloured by the game being aired yesterday. (The piece explains the blackout rules that changed a few years ago from what I remember growing up.)

But then on the inside, the article takes up another page, this time fully. It runs maps down the side to highlight the matches and scenarios the author discusses, reusing the same map as above, but because this is an interior page, in black and white. It probably looks even better online as they likely kept the colour. (They did. But the maps are smaller.)

To have that much space in which to design an article…
To have that much space in which to design an article…

Overall, I really enjoyed the piece and the maps and visuals not only drew me into the piece, but helped contextualise the story.

Credit for the piece goes to Kevin Draper.

Murder Rates in the US

Yesterday we looked at an article about exporting guns from one state to another. After writing the article I sat down and recalled that the copy of the Economist sitting by the sofa had a small multiple chart looking at murders in a select set of US cities. It turns out that while there was a spike, it appears that lately the murder rate has been flat.

Chicago is higher than Philly, to be fair
Chicago is higher than Philly, to be fair

It’s a solid chart that does its job well. That is probably why I neglected to mention it until I realised it fit in with the map of Illinois and talk about gun crimes yesterday. Because there is plenty of other news through data visualisation that we can talk about this week.

Credit for the piece goes to the Economist Data Team.

The Ratio

And I’m not talking about walking into a bar late at night. Instead, I am talking about the ratio of likes to retweets to replies, which, for those of you unfamiliar with the service, refers to engagement with a person’s tweets on Twitter.

The Ratio does not come from FiveThirtyEight—read the article for the full background on the concept, it is well worth the read—but they applied it to President Trump, whom we all know has a penchant for tweeting. The basic premise of the ratio is that you want more retweets and likes than replies. Think of it like customer reviews. Rarely do people bother to put the effort in to complement good service, but they will often write scathing reviews if something does not fit their expectations. Same in Twitter. If I do not care for what you say, I will let you know. But if I do, it is easy for me to like it, or even retweet it.

Anyway, the point is they took this and applied it to the tweets of Donald Trump and received this chart.

The interactivity makes this chart worth checking out
The interactivity makes this chart worth checking out

What I truly enjoy is the interactivity. Each dot reflects a tweet, and you can reveal that tweet by hovering over it. (I would be curious to know if the dots move. That is, do they, say, refresh daily with new tabulations on the updated numbers of likes, retweets, and replies?)

But the post goes on using the same chart form, in both other interactive displays and as static, small multiple pieces, to explore the political realm of previous tweeting presidents and current senators.

A solid article with some really nice graphics to boot.

Credit for the piece goes to Oliver Roeder, Dhrumil Mehta, and Gus Wezerek.

Speaking Freely About Free Speech

Last week the Economist published an article looking at the attitudes of the young at university in the United States. The examination was sparked by the recent-ish waves of news about stifled speech on campuses. Thankfully, we have a long-running survey from those on the ground in our universities and it reveals some interesting facts. You should head on over to the article if you want the full set, but in general, to perhaps nobody’s surprise, the media is exaggerating the confrontations we have seen.

You said what?
You said what?

My only quibble with the graphic is the height of the small multiples. I probably would have increased the height a little bit to allow any real fluctuations over the years to show more readily. But, for all I know, that could have been a limitation of the space in which the designers had to work, i.e. converting a print graphic to work on their blog.

Credit for the piece goes to the Economist’s Data Team.

The Red Sox Offence in 2017

Like I said yesterday, the Red Sox season is over. And the coverage on offseason needs began in the morning papers. But I wanted to follow up on the data from yesterday and delve a bit more deeply into the offence.

Yes, we know it was roughly league average across the team. And we know it took a hit with David Ortiz’s retirement at the end of last year. But what happened? Well, I took those same OPS+ numbers for the starting nine and compared 2017 to 2016. I then looked further back to see how those same players performed throughout their careers (admittedly I skipped Hanley Ramirez’s 2 plate appearances in 2005.)

You should take a look at the full graphic, but the short version, pretty much everyone had an off year. And when everyone has an off year, it is a pretty safe bet the team will have an off year.

You can't all take a break…
You can’t all take a break…