Archive for J.D. Martinez

The Boston Red Sox almost romantic approach to the plate has been one of the major themes on their journey to be the first team with 60 wins. Last night’s expose of producing home runs and precise batting behind Chris Sale’s robotic approach to pitching gave the Red Sox a 10-5 victory over Kansas City Royals for their 60^th victory; another notch in a long-chain of accomplishments. More impressively, however, is the Red Sox micro approach to each game. They have not only revolutionized the average statistics played out through the tenure of a season but have revolutionized how they approach the plate inning-by-inning. The romantic plate approach is more than good batting – it is the beginning to a methodical introspection into opposing pitchers for an evolution in innings five and six.

In an interview with 710 ESPN Seattle’s Danny, Dave, and Moore, Seattle Mariners pitcher Marco Gonzales casually remarked of his struggles against the Red Sox on June 24 that they were “taking swings we haven’t seen before.” Gonzales lasted only six innings against the Red Sox, allowing seven hits and five runs on six strikeouts. The fifth inning was the instant the game changed in the Red Sox favor as they scored three.

Naturally, this observation may have been a microcosm dependent on Gonzales’ pitching, not so much the Red Sox. Yet, the observation was enticing enough to warrant investigation. The results were incredible, explaining why the Red Sox meta of plate patience is about more than being disciplined – they pedantically study batters through the first few innings, leading to innings five and six which are destructive.

Before delving into the data, two notations must be established. First, the Red Sox are, on average, destructive regardless of the inning. Their jump in innings five and six are not why they are good, but why the are atop the MLB this year. Second, analytic rise in statistics in innings five and six is a trend across the league; it might be easy to pass on the Red Sox rise as the best batters popping off on ‘third-time through the rotation’ deterioration. Again, however, the Red Sox are using the seemingly inevitable deterioration of pitchers throughout the game and exacerbating on that analytic.

Within innings one through three, the Red Sox hold a .270 batting average with a 20.5 percent strikeout rate, an 8.4 percent walk rate, a .467 SLG, and a 117 wRC+ – all rates which make the Red Sox a top MLB team intrinsically. Stopping here, the Red Sox would be a good team alone. However, as mentioned, the Red Sox jump to great in inning five and six. They post a .292 batting average, only 15.7 percent strikeouts, 7.9 percent walks, a .538 SLG (.240 ISO!), and a wRC+ of 139.

On a micro-level, the functional output has benefited Mitch Moreland and Mookie Betts the most; Moreland has a .808 SLG and Betts has a 234 wRC+. Even Rafeal Devers has a sharp increase in effectiveness in these innings, raising his egregious .198 average from innings one through three to a .304 average in innings five and six.

Mechanically, the Red Sox, as a team, change the type of pitches they attack. Produced from Baseball Savant, here is a graphic of the pitch movement attacked in innings one through three; here is the comparative graphic for innings five and six. The graphic shows most of the pitches they take at the beginning of the game have little horizontal movement and trend with more vertical movement – hence, pitches which are easier to see. As the game goes on, they dramatically increase their SLG by attacking pitches with sharp horizontal movement, even hitting low.

In application, it might be said the Red Sox study through the first few innings, waiting to see how pitchers will attack under the guise of movement. Their contact is more studied through this span, evidenced by J.D. Martinez’s expected SLG of .936, Bett’s of .843, and Andrew Benintendi’s of .757. Even Devers sees an increase from an xSLG of .389 to .545.

The Red Sox plate discipline is purposed, thoughtful, and intended for the length of a game and season. They literally improve the quality of swings and contact throughout the game; the maxim of why analytical discipline is important to success.

Several days ago the Boston Red Sox acquired J.D. Martinez, presumably under the expectation of adding a lot of power to the lineup. Since 2015, he’s eighth in home runs with 105, a league-best .284 ISO (four-thousandths of a point ahead of Nolan Arenado), and his 147 wRC+ puts him at sixth in all of Major League Baseball.

Yes, he can hit for average as well but I’m not interested in that. What I’m curious about is whether or not the famed Green Monster in Fenway Park will be a hindrance to Martinez’s power.

He’ll now be playing 82 games each season in Fenway Park, where every time he comes to bat he’ll have the Green Monster in peripheral view; a 37.2-foot high wall 310 feet down the left field line and as far away as 380 feet at left center. There are dozens of hits every year at Fenway that could have ended up as home runs in other parks, but instead, are eaten up by the Green Monster and spit back out as (extra) base hits.

To attempt to approximate the minimum required launch angle and exit velocity to hit a home run over the Monster, I needed visual proof. Using Baseball Savant, I searched all the home runs hit in Fenway Park during the Statcast era.

I keyed in on home runs specifically hit to left/left center field, spanning the entire range of that monstrosity. Using the spray chart tool, I found any and all homers that were as close to the barrier of the GM (Green Monster) as possible. I came across one that seemed to fit perfectly and cleared the wall just enough.

That’s Steven Souza, Jr. driving a home run under (nearly) perfect metrics to breach the wall.

Just to be certain that this was as close as I could get, I wanted to know what the weather conditions were that day. I was able to find the barometric pressure and how mother nature’s influence could have affected this hit, in terms of exit velocity. Air pressure matters because when its low, baseballs go further due to less friction on the baseball and vice versa.

• Game time: 1:35 PM
• Game Duration: 4 hours and 32 minutes
• Approximate time HR was hit 5:00PM
• Conditions at time of HR: 50 degrees, light rain, wind blowing NW at roughly 16 MPH with gusts up to 27 MPH
• Game barometric pressure: A consistent 29 inches
  

OK, so what jumps out at you? Wind speed, right? All Fenway Park’s contact to left (center) head in a northerly direction. The low barometric pressure and wind speeds give me two possible caveats for this examination.

However, as you see in the GIF, the trajectory was fairly high and it cleared the wall by a couple of feet. It’s impossible to tell if the wind was blowing (and how hard) during Souza’s homer, so keep those things in mind since they are variables that don’t make this investigation exact when applying it to Martinez.

Souza’s hit metrics on that homer were as follows:

• Breaking ball at 80 MPH
  
• 93 MPH exit velocity
• 33.5-degree launch angle
• Hit distance of 344 feet

We can use those measurements to get a guesstimate of what Martinez could or would have done hitting regularly in Boston. I produced the following spray chart using his last three seasons under the backdrop of Fenway Park.

Clearly he’s able to hit to all fields; you could suggest that a fair amount of his hard contact is concentrated in the area of the GM and that’s what I’m going to hone in on. Yet with the height of the wall, some of those home runs (hit in other ballparks) could have been inhibited.

I inspected all Martinez’s home runs since 2015, shifted focus to the launch angle and exit velocity using the Souza home run as my model, and ran a query of all his contact using the metrics it would take to clear the wall.

I set the minimum launch angle to 30 degrees, to give a little breathing room because it appears as though Souza’s homer cleared the wall by a foot or two; I did the same for exit velocity, starting it at 90 MPH. For minimum hit projection range, I used the shortest distance to the GM; 310 feet.

Breaking it down even further, I ensured that homers hit to left center had ample room and momentum to clear the wall; e.g. the 310-foot distance wouldn’t work for a ball he actually hit to left center, for example.

Altogether, Martinez had a total of 121 batted ball events under the conditions of my launch angle/exit velocity/distance figures. 24 of those 121 BBEs resulted in contact to left field; 11 would have ended up being GM-clearing home runs if hit in Fenway, but instead were recorded as outs.

So, taking events strictly within the region of left to left-center field in Fenway, Martinez could be expected to hit about 43% more home runs facing the GM over the next three years of his contract.

Remember, that doesn’t include contact to other parts of the field. If you look back to the spray chart, you’ll see several spots marked home runs that would fall short in Fenway.

Furthermore, using his home run total from 2015-2017, we could reasonably surmise that he’ll hit an average of about 35 home runs for the next couple of years. Adding in these 11 outs as home runs, Martinez will be expected to hit roughly 9% more home runs (3 per season) at Fenway, so long as he is a Red Sox.

So, the monster won’t be as problematic as I originally assumed upon hearing of this acquisition for Boston; it might actually improve Martinez’s power.

-This post and others like it can be found over at The Junkball Daily.

While baseball fans wait for the free agent market to finally unthaw, J.D. Martinez waits for a contract offer enticing enough for him to sign. Early reports suggested that Martinez and his agent, Scott Boras, set an early asking price at seven years, $210 million. Clearly, nobody has taken the bait. Among Martinez’ likely suitors, many have moved onto other options; the Cardinals traded for Marcell Ozuna, and the Giants traded for Andrew McCutchen, seemingly leaving the Red Sox as Martinez’ lone serious suitor.

The latest report, from Buster Olney, is that Martinez has an offer on the table from the Red Sox worth five years, $100 million. Taking the reports at face value (although Boras himself has simply declared the report “inaccurate”), the offer obviously comes up short of Martinez’ demands, which is why this article is being written in late January to begin with. To that end, here’s an excerpt from Jeff Passan’s recent column at Yahoo Sports on baseball’s economic system:

“Recently, one of the best free agents available this offseason met with a friend, and he admitted something shocking: He was preparing to sit out until the middle of the season. The market for his services this winter was so thin, the offers so incompatible with his production, that he worried he was going to need an external force to compel teams to pay him what his numbers say he’s worth. Maybe it would take a playoff race.”

Can we assume that the hitter in question is Martinez? Of course not, but considering the discrepancy between his asking price and the reported Red Sox offer, it wouldn’t be an outlandish guess. While I understand that the Red Sox have leverage in that they presumably don’t have anyone to bid against, I will argue that Martinez will be well worth a contract in excess of 5/$100M.

From 2014-2017, his Age 26 through  Age 29 seasons, Martinez posted an astounding 149 OPS+ (my apologies for not using wRC+ in this column!), with a low of 139 and a high of 166. To that end, I researched players from the DH era (circa 1973) that posted an OPS+ between 140 and 160 in their Age 26 through Age 29 seasons. Presumably, these players would make for suitable Martinez comps as we attempt to project his offensive production over the next five to seven years. Of course, some of these players are still active and haven’t played enough to give me complete data, such as Ryan Braun, so they have been eliminated from the dataset. I was left with 38 comparable players, which is a large enough sample for our purposes today.

In this chart, I condensed the sample into averages because 40 rows and 9 columns doesn’t embed so cleanly. These are Martinez’s comps for their age-26 through age-29 seasons, their offensive production for the next five years (through age-34, which is Martinez’ floor value at this point) and then their production in the sixth and seventh following years (ages 35 and 36, which represent Martinez’ ceiling value at this point).

The average player from my sample posted a 147 OPS+ in their age-26 through 29 seasons, which matches up neatly with Martinez’ 149 mark. You’ll first notice the drop off in production for these players in their age-30 through 34 seasons. There are several reasons for this. Yes, natural decline was at work, but the original search for Martinez comps included a 2000 plate appearance minimum; this means I was guaranteed to be given players both as good and as healthy as Martinez in their Age 26-29 seasons without the same guarantee they would be healthy in the years that followed. This also means players like Mark McGwire (146 OPS+ in 1913 PA) were excluded from the sample because he was injured, despite the 189 OPS+ he would put up in 3462 plate appearances through Age 36.

Nevertheless, it’s a reasonable regression one can expect for players entering their 30s, and the good news is that they were, on average, very productive (134 OPS+) and very healthy (559 PA). This is what the Red Sox believe to be worth 5/$100M, but I would argue that this data shows they should be willing to tack on a sixth year without blinking. Of the original 38 player sample, 36 players played their age-35 seasons; they were still very productive (Khris Davis has been producing along these lines the past two years) and healthy enough to play a full season.

The real question surrounding Martinez is – or at least should be, if the market weren’t so cold – whether he should be given a seventh year or not. From his comps, the sample size drops significantly for the first time down to 33, the average playing time falls below the league qualifying minimum for the first time, and the production drops below what you’d want from your DH (the reference point here would be Miguel Sano from the last couple of seasons).

At face value, I would absolutely give Martinez the sixth year, and absolutely not give him the seventh. At the same time, we should dive into our sample a little deeper and discover why some players did well and why others tanked in their 30s; perhaps there is something we can correlate with Martinez so we can get an even better projection. From the original sample, here are the twenty best performers in their age-36 seasons (based on a combination of plate appearances and OPS+).

The reason I picked the twenty best rather than the top and bottom ten is that the bottom ten would be littered with folks such as Cliff Floyd or Dale Murphy, who only came to the plate 17 and 63 times respectively during their age-36 seasons. Using the ten best players captures those who were magnificent offensive performers with full playing time. Using the next ten players captures those who were mediocre in full playing time. This looks good to me.

This would be the time for me to explain why I haven’t mentioned WAR in this piece: J.D. Martinez has been horrible on defense!

He was best suited as a DH years ago, but being on a roster with Victor Martinez and then being traded to the National League forced him to play right field, which depressed his value. If Boston signs him, he’ll see absolutely no time in an outfield that will be covered by Jackie Bradley, Mookie Betts, and Andrew Benintendi for the foreseeable future. As a DH for the rest of his career, Martinez will be solely judged by his offensive production and ability to stay on the field.

Again, our question is whether Martinez receiving a seventh year is justified. More specifically, this boils down to “In seven years, will Martinez be in the left column or the right column?” Both sides of the list contain incredible players, but there’s a way to make a reasonable projection. Here’s the same list, but instead of rank, you’ll see the positions these players spent significant time. Those who had significant time at 1B/DH are highlighted in gold.

In this exercise, let’s consider 1B/DH to be significantly less stressful positions than the others. After all, there is a significant correlation between time spent in the field and sustaining an injury that leads to decline. While players like Brian Giles, Dave Parker, and Ken Griffey Jr. saw injuries and offensive decline catch up to them after years chasing down balls in the outfield, players like Rafael Palmeiro, Carlos Delgado, and Jim Thome aged extremely well by not exerting the same stress in the field.

Martinez is almost certain to spend no time in the field at Age 36. Hell, he might not spend much time in the field ever again. So I consider him a slam dunk to be placed in the group on the left. Referring to the averages from the first chart in this article, I’ll the over on Martinez when the time comes. To be clear, I donJD’t necessarily think he should be given the seventh year outright – an option would probably be most appropriate – but I think this data solidifies my comfort in giving him a sixth guaranteed year.

In a winter in which the market is changing in ways we have never seen before, it’s difficult to predict what  Martinez will earn. It’s important to remember that dollars are a construct; we can’t assume Martinez will get $150 million from the Red Sox because Adrian Gonzalez did after amassing similar numbers. Teams like the Red Sox are wary of contracts like the one given to Gonzalez, who will earn $21.5M from that deal this year. In this market (or lack thereof), it’s impossible for me to put dollars or years on Martinez, but I do know this: Martinez is a special hitter, and he’ll age especially well.

He will be a productive hitter for the next six or seven years, and there’s no dollar amount that can change that.

I, like you, have been hearing and reading a lot about the postseason and which teams are best positioned to go deep into October. The rationales aren’t always based on more tangible factors — like, say, which teams are good — but rather on “hidden” or “insider” clues (use of scare quotes completely intentional) drawn from other qualities. I decided to test each of the factors I’ve heard or read about.

Full disclosure: This isn’t exactly original research. Well, it is, in that I made a list of various hypotheses to test, decided how to test them, and then spent hours pulling down data from Baseball-Reference and FanGraphs in order to create an unwieldy 275×23 spreadsheet full of logical operators. But it isn’t original in that some of the questions I’m addressing have been addressed elsewhere. For example, I’m going to consider whether postseason experience matters. David Gassko at the Hardball Times addressed the impact of players’ postseason experience on postseason outcomes in 2008, and Russell Carleton at Baseball Prospectus provided an analysis recently. I’m not claiming to be the first person to have thought of these items or of putting them to the test. What I’ve got here, though, is an attempt to combine a lot of narratives in one place, and to bring the research up to date through the 2013 postseason.

I’m going to look at seven questions:

• Does prior postseason experience matter?
• Do veteran players have an edge?
• How important is momentum leading into the postseason?
• Does good pitching stop good hitting?
• Are teams reliant on home runs at a disadvantage?
• Is having one or more ace starters an advantage?

For each question, I’ll present my research methodology and my results. Then, once I’ve presented all the conclusions, I’ll follow it up with a deeper discussion of my research methodology for those of you who care. (I imagine a lot of you do. This is, after all, FanGraphs.) In all cases, I’ve looked at every postseason series since the advent of the current Divisional Series-League Championship Series-World Series format in 1995. (I’m ignoring the wild card play-in/coin flip game.) That’s 19 years, seven series per year (four DS, 2 LCS, 1 WS), 133 series in total.

DOES POSTSEASON EXPERIENCE MATTER?

The Narrative: Teams that have been through the crucible of baseball’s postseason know what to expect and are better equipped to handle the pressures–national TV every game, zillions of reporters in the clubhouse, distant relations asking for tickets–than teams that haven’t been there before.

The Methodology: For each team, I checked the number of postseason series they played over the prior three years. The team with the most series was deemed the most experienced. If there was a tie, no team was more experienced. I also excluded series in which the more experienced team had just one postseason series under its belt, i.e., a Divisional Series elimination. I figured a team had to do more than one one-and-done in the past three years to qualify as experienced. In last year’s NLCS, for example, the Cardinals had played in five series over the past three years (three in 2011, two in 2012), while the Dodgers had played in none. So St. Louis got the nod. In the Dodgers’ prior Divisional Series, LA played an Atlanta team that lost a Divisional Series in 2010, its only postseason appearance in the prior three years, so neither team got credit for experience.

The Result: Narrative debunked. There have been 101 series in which one team was more experienced than the other, per my definition. The more experienced team won 50 of those series, or 49.5%. There is, at least since 1995, no relationship between postseason experience and success in the postseason.

DOES VETERAN PLAYERS HAVE AN EDGE?

The Narrative: The pressure on players grows exponentially in October. A veteran presence helps keep the clubhouse relaxed and helps players perform up to their capabilities, yet stay within themselves. Teams lacking that presence can play tight, trying to throw every pitch past the opposing batters and trying to hit a three-run homer with the bases empty on every at bat. (Sorry, I know, I’m laying it on thick, but that’s what you hear.)

The Methodology: For each team, I took the average of the batters’ weighted (by at bats + gamed played) age and the pitchers’ weighted (by 3 x games started + games + saves) age. I considered one team older than the other if its average age was 1.5 years older than that of its opponent. For example, in the 2012 ALCS, the Yankees’s average age was 31.5, and the Tigers’ was 28.1, so the Yankees had a veteran edge. When the Tigers advanced to the World Series against San Francisco, the Giants’ average age was 28.9, so neither team had an advantage.

The Result: Narrative in doubt. There have been 51 series in which one team’s average age was 1.5 or more years greater than the other. The older team won 27 of those series, or 53%. That’s not enough to make a definite call. And if you take away just one year–2009, when the aging Yankees took their most recent World Series–the percentage drops to 50%–no impact at all.

HOW IMPORTANT IS MOMENTUM LEADING INTO THE POSTSEASON?

The Narrative: Teams that end the year on a hot streak can carry that momentum right into the postseason. By contrast, a team that plays mediocre ball leading up to October develops bad habits, or forgets how to win, or something. (Sorry, but I have a really hard time with this one. We’re hearing it a lot this year–think of the hot Pirates or the cold A’s–but there are other teams, like the Orioles, who have the luxury of resting their players and lining up their starting rotation. I have a hard time believing that the O’s 3-3 record since Sept. 17 means anything.)

The Methodology: I looked up each team’s won-lost percentage over the last 30 days of the season and deemed a team as having more momentum if its winning percentage was 100 or more percentage points higher than that of its opponent. For example, in one of last year’s ALDS, the A’s were 19-8 (.704 winning percentage) over their last 30 days and the Tigers were 13-13 (.500), so the A’s had momentum. The Red Sox entered the other series on a 16-9 run (.640) and the Rays were 17-12 (.586), so neither team had an edge.

The Result: Narrative in doubt, and then, only for the Divisional Series. There have been 64 series in which one team’s winning percentage over its past 30 days was 100 percentage points higher than that of its opponent. In those series, the team with the better record won 33, or 51.5% of the time. That’s not much of an edge. And when you consider that a lot of those were in the Divisional Series, where the rules are slanted in favor of the better team (the team with the better record generally gets home field advantage), it goes away completely. Looking just at the ALCS, NLCS, and World Series, the team with the better record over the last 30 days of the season won 13 of 27 series, or 48%, debunking the narrative. In the Divisional Series, the hotter team over the last 30 days won 20 of 37 series, or 53%. That’s an edge, but not much of one.

DOES GOOD PITCHING STOP GOOD HITTING?

The Narrative: Pitching and defense win in October. Teams that hit a lot get shut down in the postseason.

The Methodology: I struggled with a methodology for this one. I came up with this: When a team whose hitting (measured by park-adjusted OPS) was 5% better than average faced a team whose pitching (by park-adjusted ERA) was 5% better than average, I deemed it as a good-hitting team meeting a good-pitching team. For example, the 2012 ALCS featured a good-hitting Yankees team (112 OPS+) against a good-pitching Tigers team (113 ERA+). The Yankees were also good-pitching (110 ERA+), but the Tigers weren’t good-hitting (103 OPS+).

The Result: Narrative in doubt. There have been 65 series in which a good-hitting team faced a good-pitching team, as defined above. (There were four in which both teams qualified as good-hitting and good-pitching; in those cases, I went with the better-hitting team for compiling my results.) In those series, the better-hitting team won 32 times, or 49%. That is, good hitting beat good pitching about half the time. That pretty much says it.

ARE TEAMS RELIANT AT HOME RUNS AT A DISADVANTAGE?

The Narrative: Teams that sit back and wait for home runs are at a disadvantage in the postseason, when better pitching makes run manufacture more important. Scrappy teams advance, sluggers go home.

The Methodology: I calculated each team’s percentage of runs derived from home runs. In every series, if one team derived 5% more of its runs from homers than another, I deemed that team as reliant on home runs. For example, in last year’s NLCS, the Cardinals scored 204 of their 783 runs on homers (26%). The Dodgers scored 207 of their 649 via the long ball (32%). So the Dodgers were more reliant on home runs. In the ALCS, the Red Sox scored 36% of their runs (305/853) on homers compared to 38% for the Tigers (301/796), so neither team had an edge.

The Result: Narrative in doubt. There have been 60 series in which one team derived a 5% or greater proportion of its runs from homers than its opponent. In those series, the more homer-happy team won 27 series, or 45% of the time. So the less homer-reliant team won 55%, which is OK, but certainly not a strong majority. And if you remove just one year–2012, when the less homer-reliant team won six series (three of those victories were by the Giants)–the percentage drops to 50%.

IS HAVING ONE OR MORE ACE STARTERS AN ADVANTAGE?

The Narrative: An ace starter can get two starts in a postseason series (three if he goes on short rest in the seventh game of a Championship or World Series.) Assuming he wins, that means his team needs win only one of three remaining games in a Divisional Series and only two of five or one of four in a Championship or World Series. A team lacking such a lights-out starter is at a disadvantage.

The Methodology: This is another one I struggled with. Defining an “ace” isn’t easy. I arrived at this: I totaled the Cy Young Award points for each team’s starters. If one team’s total exceeded the other’s by 60 or more points — the difference between the total number of first- and second-place votes since 2010 — I determined that team had an edge in aces. (The difference was half that prior to 2010, because the voting system changed in 2010, when the voting went from three deep to five deep and the difference between a first and second place vote rose from one point to two.) For example, in last year’s Boston-Tampa Bay Divisional Series, the only starter to receive Cy Young consideration was Tampa Bay’s Matt Moore, who got four points for two fourth-place votes. That’s not enough to give the Rays an edge. But in the other series, Tigers Max Scherzer (203 points) and Anibal Sanchez (46) combined for 249 points, while the A’s got 25 points for Bartolo Colon. That gives an edge to the Tigers.

The Result: Narrative in doubt. There have been 82 series in which one team’s starters got significantly more Cy Young Award vote points than its opponents’. The team with higher total won 44 series, or just under 54%. That’s not much better than a coin flip. And again, one year — in this case, 2001, when the team with the significantly higher Cy Young tally won six series — tipped the balance. Without the contributions of Randy Johnson, Curt Schilling, Roger Clemens, Freddy Garcia, Jamie Moyer, and Mike Mussina to that year’s postseason, the team with the apparent aces has won just 38 of 76 series, exactly half.

Conclusion: None of the narratives I examined stand up to scrutiny. Maybe the team that wins in the postseason, you know, just plays better.

Now, About the Methodology: I know there are limitations and valid criticisms of how I analyzed these data. Let me explain myself.

For postseason experience, I feel pretty good about counting the number of series each team played over the prior three years. One could argue that I should’ve looked at the postseason experience of the players rather than the franchise, but I’ll defend my method. There isn’t so much roster and coaching staff turnover from year to year to render franchise comparisons meaningless.

For defining veteran players, there are two issues. First, my choice of an age difference of 1.5 years is admittedly arbitrary. My thinking was pretty simple: one year doesn’t amount to much, and there were only 35 series in which the age difference was greater than two years. So 1.5 was a good compromise. Second, I know, age isn’t the same as years of experience. But it’s an OK proxy, it’s readily available, and it’s the kind of thing that the narrative’s built on. Bryce Harper has more plate appearances than J.D. Martinez, but he’s also over five years younger–whom do you think the announcers will describe as the veteran?

For momentum, I think the 30-day split’s appropriate. I could’ve chosen 14 days instead of 30 — FanGraphs’ splits on its Leaders boards totally rock — but I thought that’d include too many less meaningful late-season games when teams, as I mentioned, might be resting players and setting up their rotations. As for the difference of 100 points for winning percentage, that’s also a case of an admittedly arbitrary number that yields a reasonable sample size. A difference of 150 points, for example, would yield similar results but a sample size of only 39 compared to the 64 I got with 100 points.

For good hitting and good pitching, I realize that there are better measures of “good” than OPS+ and ERA+: wRC+ and FIP-, of course, among others. But I wanted to pick statistics that were consistent with the narrative. When a sportswriter or TV announcer says “good pitching beats good hitting,” I’ll bet you that at least 99 times out of a hundred that isn’t shorthand for “low FIP- beats high wRC+.” If you and I were asked to test whether good pitching beats good hitting, that’s probably how we’d do it. But that’s not what we’re looking at here OPS and ERA are more consistent with the narrative.

For reliance on home runs, it seems pretty clear to me that the right measure is percentage of runs scored via the long ball. Again, my choice of a difference of five percentage points is arbitrary, but it’s a nice round number that yields a reasonable sample size.

Finally, my use of Cy Young voting to determine a team’s ace or aces: Go ahead, open fire. I didn’t like it, either. But once again, we’re looking at a narrative, which may not be the objective truth. Look, Roger Clemens won the AL Cy Young Award in 2001 because he went 20-3. He was fourth in the league in WAR. He was ninth in ERA. He was third in FIP. He was, pretty clearly to me, not only not the best pitcher in the league, but also only the third best pitcher on his own team (I’d take Mussina and Pettite first). But I’ll bet you that when the Yankees played the Mariners for the ALCS that year (too far ago for me to remember clearly), part of the storyline was how the Yankees got stretched to five games in the Divisional Series and therefore wouldn’t have their ace, Roger Clemens, available until the fourth game against the Mariners. Never mind that Pettite was the MVP of the ALCS. The ace narrative is based on who’s perceived as the ace, not who actually is. (And a technical note: Until the Astros moved from the NL to the AL, the difference between first- and second-place votes in the two leagues were different, since there were 28 voters in the AL and 32 in the NL. The results I listed aren’t affected by that small difference. I checked.)