Archive for Max Scherzer

The Yankees kicked off their offseason by acquiring LHP James Paxton from the Seattle Mariners to bolster their starting rotation. You won’t find anybody willing to deny Paxton’s immense talent, but it’s natural for people to scrutinize big acquisitions, especially when the big acquisition is on his way to New York. This scrutiny is best exemplified by a conversation I had with my mother on the day the trade was made. My mom followed the Mets of the mid-to-late 1980s when she lived in Brooklyn, went years without watching baseball, and has watched the Yankees for the past decade by product of my fandom. This leads to the amusing circumstance that she is very familiar with current broadcasters Keith Hernandez and David Cone, all of the recent Yankees players, and almost nobody in between. Our conversation on the day of the Paxton trade went something like this:

Me: The Yankees picked up a hell of a pitcher named James Paxton. I think he’s going to do big things for the Yankees next year!

Mom: Yeah, sure. Isn’t that what you said about Sonny Gray?

Okay — she got me there.

Read the rest of this entry »

Admittedly, this is a bit of a stupid topic. These distinctions are often thrown around with an air of importance that is far from earned. Nobody ever mentions that Hank Aaron had the most RBIs in the 1960s. You don’t need to talk about arbitrary endpoints with the Hammer. Mentioning that a player holds one of these “records” is a bit like saying a guy you are trying to set a friend up with has a great personality. It’s likely that this is covering up for something else like a hat covers a balding head.

(*before you head to the comments to blast me, yes, RBI is an incredibly useless statistic)

But they are fun! Hank Aaron did lead in RBI in the 1960s, but he finished second to Harmon Killebrew in home runs. Growing up into a baseball fan in the 1990s, one of the bigger surprises in this genre of record was the hit leader of that decade: Mark Grace. I’d imagine every Cub fan knows this. In addition, anyone who knows a chatty Cubs fan probably knows this, too. Looking at the most recent decade, there are a few surprises: Miguel Tejada had the most games played and at-bats. Andy Pettitte edged out Randy Johnson for most wins. Johnson, along with Alex Rodriguez, dominated most of the categories.

Moving to the point of this article, here is a quick rundown of compelling and not so compelling races to have the most X of this decade, with two seasons remaining:

WAR

You, the Fangraphs reader that goes into the depths of the Community Research section, probably know who leads this category, despite spending 2010 in A ball. But it is a bit closer than you might have thought. While Trout could conceivably win the position player award while sitting out the next two seasons (Joey Votto is the only player that might topple him in this scenario, and he is 9.1 WAR behind), this is the one major statistical category in which position players and pitchers compete with each other.

If I just jogged your memory of that, you probably know the name that is coming: Clayton Kershaw. Trout leads with 54.4 WAR. Kershaw has 52.1 WAR on the pitching side, but has also accrued 1.8 WAR as a batter. That should count. So Kershaw, at 53.9 WAR, is directly on Trout’s heals. Trout is still the heavy favorite, but Kershaw has a puncher’s chance, especially if another injury befalls Trout.

Totally made up odds: Trout, 98%; Kershaw, 2%

Hits

Jose Altuve has put up four straight 200-hit seasons, but he is 251 off the pace and in 15^th place. No, this title will most likely go Robinson Cano. Cano leads with 1501, and the only players within sniffing distance are similarly on the downside of their primes. Miguel Cabrera is second at 1416, and then there is a slew of players, including Fangraphs favorite Nick Markakis, in the low to mid 1300s.

Cano should clear 150 hits the next two seasons, and if he does, he will not be passed. Cabrera, as bad as he looked at times last season, would be the likely beneficiary of some unforeseen collapse by Cano. Elvis Andrus is the end of that slew of players behind Cabrera. He has 1329 hits, but recorded 191 last season and is significantly younger than everyone in front of him. I’m going to give him sleeper status for this title.

Totally made up odds: Cano, 93%; Cabrera, 5%; Andrus, 2%

Home Runs

Currently, this is an incredibly close race, with four players within five homers of each other at the top of the list. Jose Bautista is first with 272. Edwin Encarnacion and Nelson Cruz are second and third, and then you get to Giancarlo Stanton in fourth place with 267. Other than Miguel Cabrera and the remnants of Albert Pujols, no one else is close. Stanton has to be the favorite, here, but his status is extremely tenuous. First, let’s just get Buatista out of the way. He’s unemployed and several steps below the other players even if he does try to gut out two more seasons.

Without a doubt, it would be shocking if a healthy Stanton didn’t win this. But a healthy Stanton would be at least a little bit of a shock. The once-oft-injured Cruz and Encarnacion are 37 and 35, respectively, but are still mashing and project for mid-to-high 30-something homers apiece. Cruz has played four straight full seasons and E5 has three straight under his prodigious belt. Stanton is projected by Steamer for a literally—but not really literally—bananas number of 53 home runs. The Fans of Fangraphs are more modest, pegging him with only 48. But Stanton is injury prone. You all know that. There is no argument that he is not. So this is a fairly open race.

Totally made up odds: Stanton, 55%; Encarnacion, 25%; Cruz, 20%

RBI

Again, I do know this is a stupid statistic. But artificial endpoints of decades are pretty stupid, too, so this is fitting. This is Miguel Cabrera’s title to lose, and as long as he plays, he should easily win. And guys making the cash Cabrera is due for the next thousand years generally get every opportunity to play. Sitting behind Cabrera’s 860 RBI are Albert Pujols at 806 and Robinson Cano at 789. The aforementioned Edwin Encarnacion and Nelson Cruz round out the top five with 763 and 756 respectively.

If Cabrera falters, this looks like it would be a wide-open race. Pujols achieved the remarkable 100+ RBI season while losing 2.0 WAR last year. He likely will do much worse, but as long as he is playing, he will continue to accrue a decent number of RBI. E5’s Indians outscored the M’s by 68 runs last year and seem to be a better offensive team, but Cano does have a 26 RBI lead. Honestly, this looks like a virtual toss-up if Cabrera doesn’t win, but the idea of Edwin Encarnacion or Nelson Cruz leading the decade in home runs and RBI is rather delicious.

Totally made up odds: Cabrera, 80%; Cano, 7%; Encarnacion, 6%; Cruz, 4%; Pujols, 3%

Stolen Bases

Be honest, which would you rather be known for: a surprise answer to the question “who stole the most bases in the second decade of the new millennium?” or hitting an epic World Series Game Seven home run… for the losing team. Rajai Davis might say porque no los dos? Davis has the most stolen bases this decade with 301. However, he is actually a longshot to keep this title. Davis just signed a minor league deal with the Indians that includes a non-roster invitation to spring training. He will likely struggle to ever get regular playing time again. He’s 37 years old.

This will likely come down to a race between the two guys behind him. Dee Gordon has 278 stolen bases, had 60 last year, and only turns 30 in April. He has a 35 stolen base lead on 3^rd place, which would seem more insurmountable if that person was not arguably a full tick or two faster. Billy Hamilton has 243 stolen bases since coming into the league in 2013, and has been remarkably consistent, stealing one more base each year than the year before. The fans think he’ll do that again this year, hitting 60 stolen bases. Hamilton is over two years younger than Gordon, and might be faster, but the 35 stolen base edge Gordon enjoys makes him the clear favorite.

Totally made up odds: Gordon, 66%; Hamilton 33%; Davis, 1%

Wins

This is likely a two-person race between Max Scherzer and Clayton Kershaw who have 132 and 131 wins respectively. Justin Verlander and Zack Greinke sit enough off the pace at 123 and 122 to make a comeback very improbable absent an injury, but close enough to make a comeback very possible if both players in front of them miss significant time.

Moving to who I give the edge to: there just isn’t a lot separating these two. Scherzer is older, but Kershaw has had a bit more in the way of nagging injuries lately. If it truly were a push going forward, I could just go with Scherzer since he is one ahead at the moment. But I’m going to give Kershaw the ever-so-slight edge because the Dodgers are almost assuredly going to be one of the best teams in baseball the next two years while the Nationals might only have that status for the next season. Verlander gets the nod as more likely spoiler for a similar reason: the Astros are ballers.

Totally made up odds: Kershaw, 45%; Scherzer 43%; Verlander, 7%; Greinke, 5%

Saves

Craig Kimbrel should put this away by midseason. At 291, he ranks 61 ahead of Kenley Jansen and Fernando Rodney, who are tied for second with 230. Aroldis Chapman sits in 5^th with 204. Kimbrel’s consistency and consistently light usage should ensure that he continues to rack up saves the next two seasons. Even a repeat of his comparatively modest 66 saves over the last two seasons would give him a realistic lock on this honor.

If Kimbrel does fall apart, the 30-year-old Jansen would be the likely beneficiary, as he has a much stronger hold on his 9^th inning role than the 40-year-old Rodney. While Kimbrel might have this decade locked down, he will likely fall short in his quest to surpass Rivera’s total from the last decade. Rivera saved 397 games that decade. It should be noted, however, that Kimbrel barely pitched in the majors in 2010 and recorded only one save. On the other hand, he’s already blown one more save than Mariano did all of last decade.

Totally made up odds: Kimbrel, 97%; Jansen, 2%; Rodney, 1%

Strikeouts

Stop me if you’ve heard this before, but this is a two-man battle between Max Sherzer and Clayton Kershaw. Only this time, there is a much clearer favorite. Scherzer leads Kershaw 1909 to 1835. He essentially built that entire lead last season when he recorded 66 more strikeouts than the limited Kershaw. But Kershaw’s innings shortfall was not the only thing at play here. Scherzer struck out 1.63 more batters per nine innings. For the decade, Scherzer has a 74 strikeout lead in only 14 1/3 more innings. The only realistic path for Kershaw to overtake Scherzer is injury. Of course, with pitchers, injury is always a legitimate and significant risk.

Behind Scherzer and Kershaw is Justin Verlander with 1670. No one past Verlander has any legitimate shot barring a mass retirement of the some of the game’s best starting pitchers. At the end of the day, this is really a question about health. But for Kershaw to overtake Scherzer, he’d not only need Scherzer to get hurt, but he’d have to stay healthy himself.

Totally made up odds: Scherzer, 79%; Kershaw, 19%; Verlander 2%

Runs

This has been a very positive article, but let’s get a bit negative for a second. Which pitcher will give up the most runs in this decade? A big factor in this, of course, is that giving up a lot of runs is bad, and playing bad usually leads to not playing. You have to be good enough to get the ball on a regular basis, but bad enough to rack up the runs allowed. Our frontrunners are honestly not terrible pitchers. Rick Porcello leads the way with 789 runs allowed. James Shields is just behind with 778 runs allowed. Porcello is 29, started a playoff game last year, and is owed a lot of money through the end of the decade. He also won the Cy Young Award in 2016 while accruing 5.1 WAR on the mound. He should have opportunities to add to this total. Porcello underperforms his peripherals, but only by a little. He is basically good enough to never get moved out of the rotation, and durable enough to throw over 1500 innings this decade, but has a suddenly-not-great-for-the-era ERA of 4.29 over the last eight seasons.

James Shields is slated to maybe start opening day 2018. Unlike Porcello, Shields has been dreadful the past two seasons. Yeah, the White Sox starting pitching this year might be awful. Shields is owed a lot of money in 2018, but 2019 is an option that will only be picked up if Shields has a dramatic turnaround. Thus, there is a bit of a catch-22 here. If Shields plays well enough to keep getting the ball regularly into 2019, it seems unlikely that he’ll chase down Porcello. Of course, this could also come down to injury. If either player gets hurt, the other will very likely take this notorious (dis)honor.

Ubaldo Jimenez sits in 3^rd with 734 runs allowed. He will thankfully have a hard time adding to that total. If Porcello and Shields find themselves with quick hooks and no jobs, there are a few possible dark horses, including Ervin Santana and Jon Lester, who at the very least should get two full seasons of starts barring injury. For this one, I’m just going to put the field as a third choice rather than trying to single out who might suck, but play.

Totally made up odds: Porcello, 60%; Shields, 30%; Field, 10%

Other Interesting Battles

(My favorites in italics)

Games: Robinson Cano, 1264; Alcides Escobar, 1250 (that would be something)

Runs: Ian Kinsler, 785; Miguel Cabrera, 741; Andrew McCutchen, 740; Robinson Cano, 738

Strikeouts: Chris Davis, 1266; Mark Reynolds, 1250; Justin Upton, 1249

HBP: Shin-Soo Choo, 98; Anthony Rizzo, 98; Chase Utley, 92

Games: Tyler Clippard, 576; Luke Gregerson, 551

Innings Pitched: Justin Verlander, 1705; Max Sherzer, 1670.2; Clayton Kershaw, 1656.1

HBP: Charlie Morton, 82; Justin Masterson, 77 (23 in AAA in 2017)

Balks: Clayton Kershaw, 17; Franklin Morales, 15; Johnny Cueto, 13

Bonus Trout Stuff

You will notice that, apart from WAR, Mike Trout was not mentioned at all in this article. Of course, Trout played zero MLB games in 2010 and only 40 in 2011. But he is also an all-around performer. He doesn’t even show up in the top 10 for most counting categories. So for the lazy, here is where Trout ranks in the decade (if among top 30, must be qualified for rate stats):

Triples: T-8^th (40)

Home Runs: T-16^th (201)

Runs: 8^th (692)

RBI: 30^th (569)

Walks: 7^th (571)

Intentional Walks: T-14^th (61)

HBP: T-27^th (55)

Sac Flies: T-16^th (40)

Stolen Bases: 17^th (165)

Batting Average: 6^th (.306)

OBP: 2^nd (.410) (not close to first, Joey Votto, .438)

Slugging%: 1^st (.566) (biggest threat is probably Giancarlo Stanton, at .554)

Trout is about to play his age 26 and 27 seasons to round out the decade. He’ll be an “old 27” with his August birthday. We don’t know how he’ll age. But it is possible that he plays his whole career, a career of an inner-inner-circle Hall of Famer, and never leads a decade in any traditional counting stat. This on top of his frustratingly low MVP totals. If nothing else does, perhaps that should tell you how stupid this whole exercise is, and how stupid rigid benchmarks for greatness are in general. If Trout were born three years earlier, he could have dominated the counting stat leaderboards of this decade. If he played for a better team, he could have 2-3 more MVP awards.

So what does it all mean? Probably not much. If Albert Pujols squeaks out the most BRI of the decade, will that make it less of a disappointment? Does Nelson Cruz having the most home runs over an arbitrary 10-year period mean that he’ll one day be enshrined in Cooperstown? Well, no. However, I hope you had fun. I know that I did.

Confusion and “what ifs” among the industry on Orioles’ starter Dylan Bundy are everywhere, so I’ll cut through the present state of takes like a knife: Bundy is a great starting pitcher.

Red flags and disapproval rise because of circumstances surrounding Bundy that make it easy to dislike his past, present, and even future. I get it. His struggles with injuries, and Baltimore notoriously failing to develop viable starters, are two tenets the anti-Bundy fan club champions. But when any pitcher puts together multiple oh-my-god outings at different points in a season, underlying causes for those sprinkles of success reveal important trends.

One theme in Bundy’s flashes of success is a pitch the Orioles nixed as an option in the past, fearing excessive stress on his elbow. Some call it a slider, others a cutter, and the Baltimore Sun moderates the argument with a simple hyphen. It’s a pitch that possesses average to below-average break on both horizontal and vertical planes, yet still generates impressive swing-and-miss capabilities. Bundy’s cutter-slider — the Baltimore Sun method of indifference — sits fifth in whiffs generated per swing among pitches that Baseball Prospectus classifies as a “slider” (95th percentile, >200 pitches thrown). The four names above Bundy are Corey Kluber, Carlos Carrasco, Max Scherzer, and Mike Clevinger. Three objectively great pitchers, and an up-and-comer who I’ve profiled before.

Despite possessing average movement, the pitch might benefit from Bundy’s ability to tunnel all of his pitches.

Baseball Prospectus has taken the plunge in quantifying “tunneling” to the masses, and although intimidating at first, the theory makes intuitive sense. The “tunnel point” is the point in time where hitters have to make a decision whether or not to swing, and if hacking, where to do so. Above-average movement past the tunnel point would seemingly make a pitch harder to hit.

Bundy’s “Break Differential” — how much spin-induced movement is generated between the tunnel point and home plate — is 3.7 inches, substantially higher than the major-league average mark of 2.6 inches (87th percentile, 1,000+ pitch pairs). Bundy is also in the 85th percentile for a metric that signals how closely nestled his pitches are at the point of tunnel, known as the “Break:Tunnel Ratio.” We can’t say with certainty that his cutter-slider is the main culprit for this particular kind of niche success, but with the knowledge he uses it more often than any other non-four-seam pitch — especially in two-strike counts — we can infer it has some inflationary quality in this new-age stat.

Inflator number two might be the pitch that takes a back seat to Bundy’s cutter-slider, his changeup.

Bundy’s approach against right-handers is 75% fastball and cutter-slider usage, while versus left-handers, his mix in terms of offspeed is relatively even between the cutter-slider and his other three pitches, with this changeup basking in the spotlight of favoritism at 20%. Bundy uses this changeup when he needs a strike, as the pitch is seen more than three times more often when he is behind in the count rather than ahead, regardless of batter handedness.

After he gets back into counts with his changeup, he turns to the cutter-slider to put away hitters.

The frequency at which he uses his slider, at any point in an at bat, is what simple analysis says correlates to his overall success.

If just throwing his slider more was the reason for his recent success, Bundy’s xFIP in particular wouldn’t be half a run lower in his most recent set of games.

Jeff Sullivan of FanGraphs mentions that Bundy has gone up in the zone to lefties more often in August, but the effect that approach has on his other pitchers stands out the most. Combing through Bundy’s approach to left-handers and right-handers, you’ll notice an uptick in slider usage, but perhaps the most impressive change is his new ability to strike out left-handers. While his strikeout rate versus right-handers has stayed around the 24-28% mark for most of the season — reaching a high of near 30% in his most recent starts — lefties’ ability to solve the righty have dwindled.

Meddling around 12% for the first four months of the season, in Bundy’s most recent seven starts, that left-hander strikeout rate has more than doubled to 26%. This was the missing piece that allowed him to post a 28% strikeout rate over than span. His ability to pitch up in the zone to lefties allowed for the other pitches in his arsenal to flourish, and as a result, Bundy has become more confident with his cutter-slider, evidenced by its usage. The key is not only using the cutter-slider more, but combining that usage with an approach that makes the pitch more effective, particularly to left-handed bats. Overall trends in Bundy’s game have allowed individual pitches to become more effective, and with his innate ability to deceive hitters post-tunnel point, Baltimore is seeing the potential start to blossom.

In Dylan Bundy, the Orioles have something their fan base has longed for; a 24-year-old arm with an enviable arsenal and the ability to tunnel his pitches in a way that makes each independent part more deadly. There have been growing pains, but his tools have become skills at the major-league level, and it’s hard for me to doubt his intermittent dominance isn’t a sign of greater polishing. Although it would be naive to say his cutter usage is directly tied to good starts, Bundy’s Labor Day meltdown is highlighted by reliance on his fastball and his lowest cutter-slider usage since the beginning of July — sub 20%. Whether the downtick in cutter-slider usage on Monday was because because of comfort with the pitch, or a want to focus elsewhere, at least the Orioles know where Bundy’s strengths are when he spins a great outing.

Use your offspeed, Bundy, and may the baseball gods grant you health like no other. Those are the primary factors to make the step from possessing great skills to being an elite arm.

A version of this post can be found at BigThreeSports.com

Lance Brozdowski can be found on Twitter as well, @LanceBrozdow

There are a multitude of ways that we can judge pitchers. Most people look at earned run average to gauge whether a pitcher has been successful, while many old school announcers will still cite a pitcher’s win-loss record. ERA is a nice, easy way of looking at how a pitcher has performed at limiting runs, but it doesn’t come close to telling the whole story. In the early 2000s, Voros McCracken created the idea of Defense Independent Pitching Stats or DIPS, which credited the pitcher only with what he could actually control. Fielding Independent Pitching was born from this theory and only took into account a pitcher’s strikeouts, walks and home runs allowed. It turns out that a pitcher’s home run rate is not terribly consistent, thus xFIP was created by Dave Studeman to normalize the home run aspect of the FIP equation by using the league home run per fly ball rate and the pitcher’s fly ball rate.

In 2015, a new metric was developed by Jonathan Judge, Harry Pavlidis and Dan Turkenkopf called Deserved Run Average or DRA. This new stat attempts to take into account every aspect that the pitcher has control over and control for everything that he does not, thus crediting the pitcher only for the runs that he actually deserves. DRA, however, is still dependent on the result of each batted ball. If the batter hits a ball deep in the gap and it rolls to the wall, the pitcher is charged with a double, but if the center fielder lays out and makes a remarkable catch, the pitcher is credited with an out. When evaluating pitchers, why should it matter whether they have a Gold Glove caliber defender behind them or not? It shouldn’t, and that’s where Expected Run Average comes in.

Expected Run Average or XRA gives pitchers credit for what they actually can control. FIP attempts to do this as well but assumes that pitchers have no control over batted balls. While the pitcher does not control how the fielders interact with the live ball, he does have an impact on the type of contact that he allows. XRA is based on a modified DIPS theory that the pitcher controls three things: whether he strikes the batter out, whether he walks the batter and the exit velocity, launch angle combination off the bat. After the ball leaves the batter’s bat, the play is out of the pitcher’s hands and should no longer have any effect on his statistics. The goal is to figure out a way to measure, independently of the defense and park, how each pitcher performs on balls in play. Since 2015, StatCast has tracked the exit velocity and launch angle of every batted ball in the majors. Each batted ball has a hit probability based on the velocity off of the bat and its trajectory. The probability for extra bases can also be determined. These batted ball probabilities have been linearly weighted for each event including strikeouts and walks to give each player’s xwOBA, which can be found on Baseball Savant. This is the perfect way to look specifically at how well a pitcher has performed on a per plate appearance basis.

Once xwOBA is found, then XRA can be calculated. The first objective is to find the pitcher’s weighted runs below average. To do this, I used the weighted runs above average formula from FanGraphs except I made it negative since fewer runs are better for pitchers.

wRBA = – ((xwOBA – League wOBA) / wOBA Scale) * TBF

For example, Max Scherzer has had a .228 xwOBA so far this season and has faced 487 batters. After finding the league wOBA and wOBA scale numbers at FanGraphs I can plug these numbers into the formula.

– ((.228 – .321) / 1.185) * 487 = 38.22

Max Scherzer has been 38.22 runs better than average so far this season, but now I need to figure out what the average pitcher would do while facing the same number of batters. To find this I need the league runs per plate appearance rate and multiply that number by the number of batters that Scherzer has faced.

League R/PA * TBF = Average Pitcher Runs
.122 * 487 = 59.41

So a league average pitcher would have been expected to surrender 59.41 runs facing the number of batters that Scherzer has so far this season. Now that we know how the average pitcher should have performed we can find the expected number of runs that Scherzer should have surrendered so far this season by subtracting his wRBA of 38.22 from the average pitcher’s runs.

Average Pitcher Runs – Weighted Runs Below Average = Expected Runs
59.41 – 38.22 = 21.19

Based on Scherzer’s xwOBA, he should have only given up 21.19 to this point in the season. If this sounds incredible it’s because this is the lowest mark of any starting pitcher though the first half of the season. Finally, XRA is found by using the RA/9 formula by multiplying the expected number of runs allowed by 9 and then dividing by innings pitched.

(9 * Expected Runs) / Innings Pitched = XRA
(9 * 21.19) / 128.33 = 1.49

Max Scherzer’s XRA of 1.49 is easily the lowest of any starter through the first half. The second best starter has been Chris Sale who has a 2.15 XRA. Of course these names are not surprising as they each started the All Star Game and are both currently the front runners for their leagues’ respective cy young award.

Here is a list of the top ten qualified pitchers:

And the bottom ten:

Full First Half XRA List

It is interesting to see that three members of the Giants rotation rank in the bottom seven in all of baseball. In fact, AT&T Park is such a pitcher-friendly park that once you park adjust these numbers, Moore, Cain and Cueto become the three worst pitchers in baseball. It’s not surprising then why the Giants are having such a disappointing season.

One measure of a good stat is whether or not it matches your perception. Therefore, while it is interesting to see Dan Straily as one of the best pitchers in baseball and Johnny Cueto as one of the worst, it is much more assuring to see Max Scherzer, Chris Sale and Clayton Kershaw as some of the very best in the sport. The numbers for relievers also reveal how dominant Kenley Jansen and Craig Kimbrel have been. This is all good evidence that XRA is doing what it is supposed to do, accurately displaying how good pitchers have actually been, independent of all other factors.

Another important characteristic of a good stat is how well it correlates from year to year. While ERA is the most simple and popular way to look at pitchers, it is not very consistent. XRA is much more consistent than ERA and FIP and also compares favorably with xFIP. However, it is not as consistent as DRA. DRA controls for so many aspects of the game that it should be expected to be the most consistent. However, being the most predictive or most consistent stat is not necessarily the goal of XRA. The real goal is to show how well the pitcher actually did, and XRA seems to do this remarkably. While not being as consistent as a stat like DRA, the level of consistency is extremely encouraging and puts it right in line with the other run estimators.

XRA is a stat that takes luck, defense, and ballpark dimensions out of the equation. When evaluating a pitcher, he shouldn’t be penalized for giving up a 350-foot pop fly for a home run in Cincinnati while being rewarded for that same pop fly being caught for an easy out in Miami. With XRA, no longer will people have to quibble about BABIP, since it is results-independent and removes all luck from consideration. A ground ball with eyes will now be treated the same whether it squirts through for a single or is tracked down for an out. Pitching ability will no longer need to be measured with an eye on the level of the defense. It takes a good offense, a good pitching staff and a good defense to make a great team, and with XRA we can finally separate all of these important factions.

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.)