Mark Simon is a man of many hats: he's researcher at ESPN, a writer at ESPNNY.com and the ESPN Stats and Info Blog, and a constant advocate for sabermetrics. While writing for a very mainstream news source, Mark still uses advanced statistics in his articles, explaining things in a very easy-to-access way for many new readers. As a part of our "Saber Ed." series, Mark was gracious enough to answer some questions for us about his perspective on making sabermetrics and writing / reporting mesh.
Feel free to contact Mark either on Twitter (@msimonespn) or email (
Steve Slow: Could you give a bit of background about yourself? How'd you get into baseball writing, and how did you end up at ESPN? What exactly is your role there?
Mark Simon: Sure. I'm originally from New York City. I went to Stuyvesant High School, which has a very strong math and science emphasis, and then graduated from The College of New Jersey in 1997 with a journalism degree.
From 1995 to 2002, I was a sportswriter for the Trenton (NJ) Times, a daily newspaper with a circulation of 75-80,000 in a two-paper market. I covered everything from little league to the pros (three years of trying to be the Jayson Stark/Tim Kurkjian of minor league hockey with all sorts of fun tidbits on players and teams), and did a lot of feature writing (from the 12-year-old figure skating prodigy to the octogenarian 5K running champ).
In 2002, I moved on to ESPN, working on helping our MLB and college basketball game telecasts. In 2004, I transitioned into working on Baseball Tonight on a full-time basis.
As a show researcher (and there are 40+ of us), it's our job to make the shows sound smart. We create the graphics and generate ideas for things that you see on SportsCenter, ESPNNEWS and shows like Baseball Tonight. We deal directly with our production crew and on-air talent, answering their questions and supporting their opinions. It's a job that requires strong sports knowledge, computer skills, and the ability to communicate both in print and verbally. Often, the key isn't necessarily knowing the information off the top of your head, but knowing how to look it up.
The work involved is a team effort. A lot of the time, an idea will be circulated in our area and someone else may build on it ... I may help someone working on an ESPNNEWS show with a graphic that maybe Baseball Tonight wouldn't want...and then 5 minutes later, they may circulate something that ends up leading our Baseball Tonight show (one luxury of Baseball Tonight is that we often have 2 people and sometimes 3 from our department, working on a show). We have great people in Stats and Information and I think one of our biggest strengths is how well we work together.
Currently I hold that role, and I also do research related to what we do for ESPN.com, which includes helping write and edit the Stats and Information Blogs for MLB, NFL, NBA and college football.
In my "spare time," I write for the Mets and Yankees blogs at ESPNNY.com and am a regular guest on the Baseball Today podcasts. We did a segment each week during the season where I'd talk stats and tidbits, and answer listener questions.
SS: Your articles are always great reads and I love how you include sabermetric principles and stats in many of them. How did you first get introduced to sabermetrics? What hooked you?
MS: First of all, thank you for the compliment and thank you for noticing what we try to do here.
I would guess I was one of Bill James youngest readers (age eight). My dad bought me the Bill James 1982 Baseball Abstract after I devoured "This Date in Mets History," probably thinking it was just another baseball book, and since I liked math at an early age, why not?
I remember when I first started reading, I didn't understand how the formulas worked ...that if two values were next to each other, you were supposed to multiply them. So I couldn't execute the formulas. But the player comments were funny, the team summaries were well-written, and while I might not get the math, Runs Created as "ultimate baseball stat" didn't strike me as that hard to grasp.
Funny story: When I was home for Thanksgiving, I found a notebook from when I was 13 years old, in which I took a closer look at the 1980 to 1984 Cy Young races and re-voted based on my opinions. For one year (1980 AL, I think), my notes were "Yes, the winner (Steve Stone) had more wins, but Mike Norris had better ERA AND better K/BB numbers." Guess it was meant to be for me to go into this sort of work ...
What hooked me? I guess I found it interesting as one of many aspects of the game. My general thing is that I'm a sucker for a good story. And you can tell some good stories with all kinds of statistics.
SS: Considering you're writing at ESPN, what audience do you try and reach? Do you assume prior sabermetric knowledge in your readers, or do you approach each article as though you're writing to a saber-newbie?
MS: With the Mets and Yankees material, I'm writing to the hard-core, knowledgeable fan. With the Stats and Info Blog, I'm writing to the baseball fan who likes stats and information (otherwise, why would they click on the link?). A lot of the time, I use myself as the gauge, since I know how intensely I follow the sport. If I think it's something I would read, I pursue it.
I don't presume prior Sabermetric knowledge, but I hope that if I try to summarize a sabermetric concept in two paragraphs, that the reader can follow along.
SS: Similarly, how do you approach integrating advanced statistics into your articles? Are there any tricks you've found that make it easier for people to grasp a concept or statistic?
MS: This is a great topic for discussion. A couple weeks into when I started writing for ESPNNY, one of the editors said to me "Stick with the approach you're using ...explanation without sounding professorial." I find that to be a good guideline.
I look at it from the approach of focusing on concepts and rankings rather than math, and relating the material to current events as much as possible.
A few examples
WAR, at its most basic, is me and you debating who the best player in baseball is. You have your ingredients, I have mine. But it's not an exact science for either of us. WAR has its own, in the form of concrete statistical information. At one point in the season, the WAR metric on both Fangraphs and Baseball-Reference.com rated Angel Pagan among the best outfielders in the NL. That runs counter to what you or I might think of him. But let's look more closely at how WAR evaluates Pagan. We can drill down to a really close-up look at Pagan's positives and negatives. Turns out that he rates above average in a lot of areas. So, that's an article.
Also with WAR and WPA-- I did an interview with John Olerud and it was a pretty standard "Where are they now?" sort of piece. But if you check out the historical WAR and WPA numbers on Baseball-Reference.com, during his time with the Mets, he was really, really really good. So I figured it was worth devoting a couple of paragraphs to explain this. I think the Met fan who remembers John Olerud probably got what I was going for there.
Another example, using what I guess we'd consider an "antique" stat-Offensive Winning Percentage, a Bill James metric from 30-or-so years ago. Baseball-Reference.com tracks it on every player page and in looking at Derek Jeter late in the season, it was clear by late August for the first time in his career, his offensive winning percentage was going to finish below .500.
We have it in our heads what a "winning player" is supposed to be. Well, it can be a mathematical concept too. So let's look at what this stat tells you - how good a player is at creating positive events on offense and avoiding negative ones relative to others in the major leagues. That was another article.
SS: So keep it simple, remove the math, and use the new stats to highlight topics already on people's minds - that sound about right? I also think it's really helpful to introduce a new statistic by showing how it shows something we all know is true, and then showing how it can show us something new and surprising. Like your Angel Pagan article - I think that's a great example.
MS: Yes on all three counts. And people really like rankings, so sometimes I'll emphasize rankings very heavily, and I'll note if the gap between #1 and #2, or #2 and #5 is big...and maybe you give an example, like the difference between a WAR of 5 and a WAR of 3 is a big deal, but a WAR of 5 vs a WAR of 4.7 is small.
We'll have more with Mark Simon on Thursday, covering the areas he sees as the toughest to convey to saber-newbies.