Following on yesterday’s post about the Red Sox offence, I wanted to follow up and look into their power numbers. So here we have a smaller scale graphic. Nothing too fancy, but the data backs what my eyes saw all year. A definite power drain up and down the Red Sox lineup 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.
Well the 2017 season ended yesterday afternoon for my Boston Red Sox as we lost 5–4 to the Houston Astros and they took Game 4 of the ALDS. So this morning we will surely see the critiques and hot takes on what to do to improve the team begin to make the internet rounds.
But before we get into all of that, I wanted to take a look at the 2017 season from a data perspective. At least, the regular season. After all, we can see how Sale in Game 1 and Kimbrel in Game 4 just had poorly timed bad days. But what about the other 162 games? After all, we will need to win a lot of them if we want to make it back to the playoffs in 2018.
I just pulled a couple quick stats from Baseball Reference. Now we can quibble about which stats are best another time, but from my experience the more sabremetric datapoints are lost on a general audience. So here we are using OPS, basically a hitter’s average combined with his power/slugging ability, and ERA, the amount of runs a pitcher can be expected to allow every nine innings. I also threw in defensive runs saved above average, i.e. is the player saving more runs than an average player.
You can read the graphic for the details, but the takeaway is that Boston, we need not panic. The 2017 Red Sox were a good team. Far from perfect—here is looking at you lack of middle-of-the-order power—but a solid lineup, good rotation, good defence, and a fantastic bullpen. How can we add without subtracting too much?
Well news definitely happened whilst your author was on holiday. So today we look at an informative piece from the New York Times that compares the weapons fire from the Las Vegas shooting to that of Orlando and a fully automatic weapon.
This piece makes good use of both audio and motion graphics to show how the bump stock makes a semi-automatic rifle more like what we might call a machine gun. It also includes some nice illustrations that demonstrate how the stock does what it does.
From an audio standpoint, I do want to point out that the designers made a wise decision in opting not to use authentic sounds. Instead they chose an abstracted sound, allowing the user to focus on the rapidity and steadiness of the sound.
Credit for the piece goes to Larry Buchanan, Evan Grothjan, Jon Huang, Yuliya Parshina-Kottas, Adam Pearce, Karen Yourish, C.J. Chivers, and Thomas Gibbons-Neff.
I rarely watch American football. But I do like charts about it. So today’s post looks at a piece from Benjamin Morris who explored the scenarios in which a team should opt for the two-point conversion. For those of you who know even less about American football, you can attempt such a conversion after your team scores a touchdown. More often than not your team will go for the far safer and more assured one-point conversion, which if made makes a touchdown of seven points.
It turns out that teams should probably be looking for those two points a wee bit more often than they presently do. And to help teams figure that out, Morris made a small multiple chart looking at many different scenarios.
Credit for the piece goes to Benjamin Morris.
You may recall how over two years ago I posted about a piece from the New York Times that explored the levels of Arctic sea ice. It showed how the winter sea ice of 2015 was the lowest level ever recorded. Well last week the Times updated that piece with new data. And instead of the static graphic we enjoyed last time around, this time the piece began with a nice animation. It really helps you see the pattern, so you should click through and check out the whole piece.
But this isn’t just a visually top heavy piece. No, the remainder of the article continues to explore the state of Arctic sea ice through a number of other charts and maps.
Credit for the piece goes to Nadja Popovich, Henry Fountain, and Adam Pearce.
Last month, two massive earthquakes devastated Mexico. Now, if you were like me, you were captivated by the photos and videos of the quakes striking and tearing down buildings and infrastructure. But, think about it for a second, how did people know to take out their mobiles and record the tremors for posterity’s sake?
Well, the first thing you should know is that earthquakes consist of a number of different waves of energy. Some move quicker and are less damaging than the slower travelling ones. And it turns out that scientists have been able to use that speed differential to build early warning systems along and around fault lines.
The Washington Post did a really nice job of explaining how earthquake-prone California is developing just such a system to deal with its tremors. I won’t spoil all the details, you should go read the article if earthquakes are of any interest to you.
Credit for the piece goes to
I had dinner with an old friend earlier this week and in the course of our conversation we discussed the bans of knives and guns from hospitals. That reminded me of this xkcd comic from last week.
Credit for the piece goes to Randall Munroe.
On Monday, Attorney General Jeff Sessions and the Justice Department released figures for violent crimes in 2016. The administration talked about the rise in violent crime. And yes, such crime did rise in 2016. But, what was not raised nearly as much is that we are also living in an era of historically low crime. FiveThirtyEight broke down the crime numbers through a series of charts and put them in their historical context.
The screenshot below looks just at murder rates. And again, nobody denies that the murder rate is up. But it still below the level it was in the 2000s, 1990s, and 1980s. One has to go back to the 1960s to find murder rates so low.
The point is really just to reiterate that context matters. If we were to look at the rise over the last year, yes an increase from 4.9 to 5.3 would look bad. But, really, we are still living in a far safer country than we were for most of the latter half of the 20th century. You just need to extend the endpoints of the chart to see it.
Credit for the piece goes to Jeff Asher.
Pretty bad.
Less than a week after posting about the satellite views showing entire villages razed to the ground, we have a piece from the Economist looking at refugee outflows. And they are worse than the outflow of refugees during the Rwandan genocide back in 1994.
To be clear, they are not saying that nearly a million people have been killed—though there is quite a bit of evidence to say the Burmese security forces are cleansing the state of Rakhine of one of its primary ethnic groups.
But when it comes to the chart, I am not quite sure what I feel about it. It uses both the x and y axis to show the impact of the refugee outflow. But the problem is that we are generally rubbish at comparing areas. Compounding that, we have the total number of refugees represented by circles, another notorious way of displaying areas. (Often people will confuse the circle’s area with its radius or diameter and get the scale wrong.)
I wonder, would a more straight forward display that broke the dataset into two charts would be clearer? What if the designers had kept the Marimekko-like outflow display, but represented each crisis and its total outflow as a straight bar chart to the right of the timeline? (I do think the timeline is particularly good context, especially since it highlights the earlier persecution of the Rohingya.)
Credit for the piece goes to the Economist’s Data Team.
