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It Must Be Something: Explaining the Nationals-Giants series

Last week, the Washington Nationals lost their opening-round playoff series against the San Francisco Giants, falling 3-2 in Game 4 in San Francisco. The series offered a lot of gripping, exciting baseball; and for one Nationals fan, at least, it was an enriching experience even with the loss. (This post is written from a Nationals fan perspective, but may be of wider interest). After a close playoff series, it is natural to try to understand what happened. I’d like to look at an idea which has surfaced in prominent places in recent days:

** The Nationals suffered from a lack of poise in the face of the heightened pressure in the playoffs; and the Giants exhibited more poise, in a manner which contributed significantly to their victory.

This idea can be found in two recent columns by the Washington Post’s Thomas Boswell (“Washington Nationals must recognize, and embrace, that October is whole new ballgame” and “Hard truth is Nationals are not yet a match for the poised, traditional powers of the NL”, both from October 8). There is similar praise of the Giants in Jayson Stark’s ESPN article “For Giants, it’s ‘ugly, but it works’” (also October 8).

I’m afraid I think reactions like this are superficial. Both teams scored nine runs over four games, so by this familiar measure they were equal. But we all share a tendency to think that the Giants must have won for a good reason: there must be something which distinguishes the two teams. Rather than being unique to inquisitive baseball fans, this desire for an explanation has deep roots far outside the sporting world; it is codified in some circles as “the principle of sufficient reason.”

Regarding the baseball playoffs, this principle is often applied as follows:

Playoff contests between evenly matched teams are often won by the team which possesses more poise. As compared to the regular season, there is more pressure in the playoffs, and what really matters is whether you respond to this with poise. In fact, poise is so important in the playoffs that it often allows a less talented team to beat a more talented team.

Several factors combine to make the poise theory an inevitable diagnosis of the Nationals-Giants series. The Nationals had a better regular season record (96 wins vs. 88 for San Francisco) and are perceived as having more talent. Also, the Giants had established a reputation as a very poised playoff team by winning two of the previous four World Series. From my side of the country, it sounds like they also picked up a reputation for outperforming their regular season record in the playoffs.

Not only that, but in 2012 the Nationals had another excellent regular season before losing to the Cardinals in a five-game first round playoff series. As you know, the Cardinals also have a reputation for being a poised playoff team. And it should not be a surprise that the 2012 Nationals-Cards series seemed to lend itself to the explanation that the Cardinals exhibited more poise.

Our series matched a post-season poise team against a regular-season performer with question marks surrounding its playoff poise. So, after the series concluded in the manner that it did, a logical next step was the appearance of the poise theory.

The problem with the poise theory is that it starts with the winner and works backwards. It cherry-picks moments that are easy to remember, at the expense of more gradual or incremental dynamics. The theory routinely assigns these moments too much significance. Often, this mindset looks at only one side of what happened at various points in the game. The analytical result is that the winner won via poise, and the loser gets no credit for exhibiting poise, or any other positive qualities.

The poise account of the Giant-Nationals series is that the Nationals were frozen by the moment and didn’t hit well, that the Giants tied game 2 when down to their last out (and won it with a poised HR in extra time 9 innings later), that the Nationals made several on-field errors in game 4, and made two questionable (or just bad) bullpen-decisions in games 2 and 4…and that the Giants played gritty, opportunistic, mistake-free baseball throughout the series.

One obvious flaw in the poise account is that the last idea is false: Madison Bumgarner’s throwing error in game 3 allowed the Nationals to score 2 runs in their 4-1 victory. In addition, this error was triggered by a two-strike bunt from Wilson Ramos, which would seem to qualify as an exhibition of playoff poise (and of a player adapting to the moment, etc.).

Why doesn’t Bumgarner’s two-run throwing error count against our attribution of poise to the Giants? One reason is because we are working backwards from the fact that the Giants ultimately won the series. Since the Giants won a close series which can only be explained in terms of poise, elements of the series which clash with this narrative are suppressed to preserve the integrity of the explanation.

The “poise” explanation of the Giants’ victory is also challenged if we admit that the Nationals exhibited poise, because then the two teams do not differ in a way that explains the Giants’ victory.

Unfortunately for the poise theory, the Nationals displayed loads of this quality throughout the series – for example, via a two-strike bunt, via Jordan Zimmermann’s game 2, or via Doug Fister’s game 3. (If you are currently protesting that Ramos’ bunt was very improbable, you are just tracking the series outcome and the prior reputations of the teams).

Also, in game 4, although the Nationals certainly struggled in innings 2 and 7, including loading the bases twice, walking in a run, and throwing a wild pitch — they kept themselves in the game by limiting the total damage to 3 runs. This fact would have played very well in “poise” articles written in the scenario where the Nationals went on to win. It is now somewhat difficult for us to see poise at work in those innings. But again this is perception well shaded by the outcome. This illustrates how in baseball the attribution of poise just tracks who won a close game or series.

The poise theory cherry-picks parts of games; it also cherry-picks parts of plays. In the seventh inning of game 4, after his wild pitch, Aaron Barrett threw a ball over the catcher Ramos’ head; they were trying to walk the batter. But Ramos was able to recover the ball, Barrett covered the plate; and, in a poised, well-executed play, they threw out Buster Posey at the plate, thus preventing another run.

In game 2, with Drew Storen pitching in the 9th, Pablo Sandoval hit a ball down the left-field line which scored one run, which tied the game, and which threatened to score two. But the Nationals made two accurate throws starting from deep left field, and a good tag at the plate, to get Buster Posey (again, so to speak) at the plate.

The poise theory presumably gives Posey credit for pushing the action in close games; and here I agree. But we should also give credit to the Nationals for showing the poise, and, relatedly, the baseball fundamentals, to throw him out twice to prevent runs.

I think a normal look at poise finds it in abundance on both teams in this series. However, the baseball variant of this concept has a different logic. This variant just tracks the winner when the outcome is close.

In addition to the poise issue, there were other interesting aspects of the series.

Although the Nationals were regarded as the better team, the two clubs were not far apart with respect to many regular-season statistical measures.

Nationals batting (pitchers excluded):
.261 avg. / .330 oba / .407 slg. *** 107 wRC+, 151 HR *** 8.6% BB / 20.0% K

Giants batting (pitchers excluded):
.263 avg. / .319 oba / .401 slg. *** 107 wRC+, 128 HR *** 7.2% BB / 19.3% K

The two teams had very similar offenses, although the OBA and HR numbers represent real differences. Also, their K and BB rates cohere (to a small degree) with the idea that the Giants are more of a contact hitting team, in that they swung more (i.e., walked less) and struck out less than the Nationals. One suggestion I’ll make below is that some of the Nationals should have swung a bit more.

Turning to pitching, although the Nationals came in with a better pitching reputation, and although the Nationals have better pitching, this point is not straightforwardly validated by the full range of ERA-like measures made available by contemporary analysis:

Nationals: 3.03 ERA / 3.18 FIP / 3.43 xFIP
Giants: 3.50 ERA / 3.58 FIP / 3.59 xFIP

The pitching stats converge as we move to measures which factor out balls in play (roughly, FIP) and then factor out the home run/fly ball rate (roughly, xFIP).

FIP and xFIP bring the teams together; so do somewhat blunter measures like runs allowed per game:

Nationals: 3.43
Giants: 3.79

The teams’ xFIP’s were very close, and they were closer than I would have guessed in terms of Runs Allowed. The Nationals had a better record, but I think this was due in part to the Giants just playing the Dodgers more! These teams were closer than the lead-in fanfare communicated.

I’ll offer two observations about the Nationals’ hitting, both of which cut somewhat against the playoff poise theory. The first is that while the Nationals’ offense certainly has a high-gear mode, this is not the only face they present to the world on an ongoing basis. For instance, the non-pitchers were .252 avg. // 101 wRC+ in the first half of this season…vs. a .273 avg. // 115 wRC+ in the second half of the season.

The streakiness is due in part to a group of more or less low-average, high-power players (LaRoche, Desmond, Ramos). These players are somewhat prone to 4-0-0-0 nights anyway, and in the playoffs series the Giants appeared to have good plans for them. My subjective recollection is that there were many at-bats when these players were not close to getting a hit.

But what about the Nats’ better hitters? I am thinking of Rendon and Werth in particular, and again the Giants appeared to have a plan. Here I do have a concrete suggestion about what was going on. Werth and Rendon each had 20 plate appearances in the series, and they both had 10 appearances where they took the first pitch as a called strike. This may be a surprise to you, but I doubt it’s a surprise to the Giants. Werth and Rendon are both deliberate hitters, and I think the Giants resolved to take advantage of this, and to keeping throwing early strikes until Werth and Rendon made them pay.

Of course, Rendon batted .368 for the series, and Werth batted .056. However, Rendon’s hits were all singles, from a 21 HR / 39 2B hitter. The Giants gained an edge here – in a specific, tangible way – and Rendon and Werth didn’t make the requisite adjustment. But this is one piece of a story which could easily have been different. For example, Rendon hit a very deep fly ball in extra-innings game 2, which might have made it to the wall or farther in different wind conditions. Werth had similar misfortune on deep fly balls, the most memorable of which was Hunter Pence’s excellent catch late in Game 4.

The Giants deserve credit for executing a good approach against the Nationals’ hitters. On the other side, the Giants did not exactly light up the Nationals’ pitching. After game 2, the Giants did not score a run off a hit. So I suspect that the Nationals’ pitchers executed similar strategies as well. These layers of the competition are more remote to those of us who observe the game from the outside; but they are probably more significant than psychological differences between the teams.

What about Bryce Harper?

Bryce Harper did more than exhibit poise in this series. Bryce Harper displayed the superlative animal dynamism which our games can extract from us and showcase, the best they can offer. More than any other player, Harper elevated a series marked largely by deadlock and attrition. A series like that does require poise, which both teams showed. A series like that is exciting, but not transcendent. Poets celebrate poise when a contest offers little other inspiration.

OK, what are the proper takeaways?

Boswell writes

If you send the winning run home on a wild pitch (Aaron Barrett); if you can’t field a two-hop grounder back to the mound (Gio Gonzalez); if three players look at each other and none of them picks up a sacrifice bunt attempt (Gonzalez, Anthony Rendon, Ramos); if you can’t throw a strike with the bases loaded and walk home a run (Gonzalez); if you get confused and throw home when no Giant is actually running toward the plate (LaRoche), squandering an out, then you have no business staying at baseball’s October party.

Amen! But why not issue a similar edict against the Giants, who, again, did not score a run off a hit in the last two games? Out of context, that doesn’t sound like a terribly promising formula either.

Boswell also draws an analogy to golf: “Right now, the Nationals are like professional golfers who win a bunch of weekly Tour events but falter under the pressure in major championships.” His remark connects us with a long-running discussion in golf about competitors with various records in the majors (the Masters, the US Open, the British Open, and the PGA Championship) and in regular events. This discussion of golf players is characterized by an all-too-familiar blend of mythology, pop psychology, and information gaps. Nonetheless, I think there are instructive parallels between the majors and the baseball playoffs, which help us understand the recent Nationals-Giants series, and perhaps offer some lessons for the Nationals looking ahead.

Boswell’s peroration about disqualifying mistakes is wrong. Golfers win major tournaments despite serious, embarrassing, incriminating blow-ups. At Carnoustie’s 18th hole on Sunday of the 2007 British Open, Padraig Harrington twice hit his ball into a narrow, winding waterway, but ended up winning a playoff against Sergio Garcia. I am fine with the idea that you have no business trying to win a major if you find the water twice on the 18th hole. But this plausible moral stance is falsified by events. Similarly, in 1999, on the same final hole at Carnoustie, Jean van de Velde elaborated an even greater disaster; he blew a three-shot lead, but still qualified for a playoff.

The significance of an error depends on where you are in the competition and on what your opponents are doing. In a high-pressure situation, they may not be doing very much. At Carnoustie in 2007, the golf course and the moment got the better of everyone, in that the top three finishers (Harrington included) were a combined six over par for the last two holes. At Carnoustie in 1999, the course had been winning all week, in that no one finished under par for the tournament. In fact, van de Velde’s blow-up brought him back to a three-way tie for the lead at 6 over par. Looking at a different golf course, in the 2006 US Open, won by Geoff Ogilvy, the top four finishers all suffered serious damage on the final day, with Phil Mickelson and Colin Montgomerie taking double bogeys on the final hole.

The Nationals should work on their play inside the diamond, but they shouldn’t beat themselves up about it. Everyone is likely to screw up in the furnace of playoff pressure, including the Giants…who yielded two runs on one bunt.

Let’s say that an attrition contest is one in which even the winner takes a beating. Although this model is prominent in major golf, it is not universal. (I’m sure it isn’t in baseball either. But I have a better grasp of recent golf). Some players get a lead early and are never seriously threatened. Many of Tiger Woods’ victories fit this pattern. A recent, more mortal example is Martin Kaymer’s 8-shot victory in the 2014 US Open.

Another interesting major winner is Charl Schwartzel, who birdied the final 4 holes at the 2011 Masters, to resolve a highly fluid final-day horse race in which 8 different players had at least a tie for the lead at different times during the day. Five past or future major winners finished behind Schwartzel in the top 10, as well as Rory McIlroy, who lost a two-stroke lead, shot an 80 for the day, and finished out of the top 10. (McIlroy won the next major in 2011 and has since won three more majors). Schwartzel elevated his play above his competitors at the climax of one of the world’s great sporting events. In this setting, against this group, poise is out as an explanatory variable. Schwartzel won with the sort of imperious dynamism which I have already praised as the most admirable character trait athletic competition reveals to us.

I think the Nationals can win an attrition playoff series, because they almost did. (Just ask the Giants in a candid moment). But playoff success for them is likely to go by a different path. A team which can post a second-half 115 wRC+ (pitchers excluded) without a healthy Ryan Zimmerman and Bryce Harper, while posting a team 2.96 ERA over the same period, may not need to change the way it plays. It may need to embrace the way it plays.

Less poetically, I’m optimistic about what the team can do with a full season of Zimmerman and Harper, Harper, Harper :-).

Tanner Roark’s Z-Swing%, and Related Observations

Although the Nationals had a disappointing 2013 season overall, Tanner Roark (RHP) was one of their more pleasant surprises. The Nats brought him up in August, as injuries and performance problems created openings for several pitchers in their minor league system.

While Taylor Jordan also performed well, I think it’s fair to say that Roark had the most impressive and intriguing debut for the big-league team. Roark accumulated excellent “traditional” stats, and he did so at least in part by exploiting an unusual but highly effective talent: making batters not swing at good pitches. This post explores Roark’s story, and opens up the question of how his distinctive forte, zone-swing rate, contributes to effective pitching.

To recap, Roark finished 7-1 with a 1.51 ERA over 53 2/3 innings. He allowed only 1 home run in total, or 0.17 home runs per 9 innings; and the league batted .197 against him (– “batting average against” or “BAA”). The Nationals’ ace, Stephen Strasburg, allowed 0.79 home runs per 9 innings, with a BAA of .205. Roark was comparable in BAA to Strasburg, and much, much better at preventing home runs.

Of course, Strasburg reached his figures in 183 innings of pitching as compared to Roark’s 53 innings of pitching. This is what is sometimes described as a smaller sample. But we should not discount Roark’s performance too quickly. His 53 innings involved five starts and nine relief appearances, and a total of 12 appearances with at least two innings pitched. This is considerably more than, say, one start and no relief appearances. Roark played for the Nationals for the last two months of the season. His stint in the majors last year was substantial enough, I think, to merit serious interest.

Roark’s 2013 performance was surprising in part because of his pedigree. In 2012 Roark was 6-17 as a starter in Triple-A, pitching for the Nationals. His 2012 ERA in Triple-A was 4.39 (although his FIP [Fielding Independent Pitching rating] of 3.85 was better). Providing more background, Adam Kilgore wrote in September 2013 that

Roark has never been regarded as a star or a significant prospect. In 2008, the Rangers drafted him in the 25th round. The Nationals acquired him and another minor league pitcher for Cristian Guzman at the 2010 trade deadline. Last winter, the Nationals left Roark unprotected from the Rule 5 draft for the second straight year. They invited him to major league spring training this year, and shipped him out in the first round of cuts.

(Washington Post, Nationals Journal, 9/17/2013;

Roark’s 2013 performance was also surprising because, with a fastball averaging 92.6 mph, he had good but not overwhelming velocity.

Going back to FIP and similar topics, another reason why Roark’s 2013 performance was surprising was because of some relationships between his statistics. For instance, although his 2012 Triple-A ERA (4.39) was higher than his 2012 Triple-A FIP (3.85), this relationship reversed itself last year in the majors, with Roark posting a 1.51 ERA and a 2.41 FIP. In addition, his xFIP (“expected Fielding Independent Pitching”) was 3.14, significantly higher than the FIP.

“ERA < FIP < xFIP” spreads of this size are not unheard of, but they are rare, especially when your ERA is less than 2.00. In fact, ERA < FIP < xFIP distributions of this type suggest that you are identical to Clayton Kershaw (1.83 ERA / 2.39 FIP / 2.88 xFIP) and that you have just signed a contract worth 215 million dollars!

These observations about Tanner Roark’s performance and pedigree raise several questions:

How did he perform so well in 2013?

What is going on with his ERA<FIP<xFIP distribution?

What can we say about his future performance?

Taking a quick initial look at the ERA<FIP<xFIP distribution, a “negative” delta between ERA and FIP is often attributable to the pitcher having a low Batting Average on Balls in Play (BABIP). Roark’s BABIP was indeed very low, at .243. (Kershaw’s was .251).

Also, although this might sound odd, Roark’s extremely low HR rate (0.17 per 9 innings) pushed his ERA below his FIP, even though home runs are a fielding-independent matter. Roark was fine (league average or better) on the other FIP elements — walks, K’s, HBP’s. But combining these normal-range statistics with his homer rate produces a compromise number and some information loss.

Turning to xFIP, this calculation substitutes out the pitcher’s own homer rate for the league average homer rate. As we might expect, the league average homer-rate was much higher than Roark’s, and this explains the FIP < xFIP delta, while also contributing to the delta between his ERA and his xFIP.

These observations tend to intimate that some of Roark’s statistics are not likely to repeat themselves. Before turning to the “future performance” question identified above, I want to look more at the first question of trying to understand Roark’s 2013 success. There are aspects of Roark’s pitching last year which suggest that his strong performance numbers were not an accident, and that his apparent prowess is not simply overmagnified by the small prism of his innings total.

The first statistic of interest is that Roark was seriously good at throwing pitches in the strike zone which batters did not swing at. This is the Z-Swing% statistic recorded on FanGraphs and other places. Roark’s Z-Swing rate in 2013 was 54.8% (per Baseball Info Solutions [BIS]), or 55.9% per PITCHf/x. This means that batters only swung at Roark’s pitches in the strike zone about 55% of the time.

(BIS and PITCHf/x converge around 55% for Roark’s Z-Swing%. These systems actually diverge, or report different percentages, for some other stats which are not independent of Z-Swing%. Although this is interesting, the differences do not materially affect our evaluative questions. I will cite the BIS plate discipline statistics throughout and compare them to PITCHf/x at various points below).

The complement of Z-Swing% is what I will call “Z-pass” — the phenomenon of non-swings on pitches in the strike zone. Tanner Roark’s Z-pass rate last year was 45% — batters passed on about 45% of his pitches in the strike zone.

This was a very high Z-pass rate. In fact,

  • It was the highest Z-pass rate on the Washington Nationals, by about 5 percentage points, among Nationals pitchers with at least 50 innings.
  • It also was more or less the highest Z-pass rate in all of major league baseball, again among pitchers with at least 50 innings. Roark came in first in Z-pass rate according to BIS. According to PITCHf/x, Roark was tied for sixth-best in Z-pass rate, behind Sonny Gray with a 47% Z-pass rate.

A high Z-pass rate is indicative of several good pitching qualities. Z-passes are good because they mean that batters are laying off a higher number of pitches which damage their cause and advance the pitcher’s cause. A high Z-pass rate indicates that the pitcher is accumulating strikes while maintaining an atypically lower risk of allowing a hit. (This is true if the pitcher is hitting the strike zone at a reasonable rate. More on this below). Tactically speaking, the Z-pass is the best outcome on the swing v. strike zone matrix below.

In Zone

Out of Zone




No Swing



Swings on pitches in the zone and out of the zone can lead to hits, and worse. By contrast, if we assume that non-swings in the zone lead to strikes, the Z-pass simply constitutes a good outcome for the pitcher.

How often did Roark throw strikes? In 2013 Roark hit the strike zone 47.7% (BIS) of the time. This was about 3 percentage points ahead of major league average (44.9%). 3 percentage points comes out to about one standard deviation above average. (PITCHf/x reports a higher league-wide strike-zone rate — 49.4% — and a higher strike-zone rate for Roark as well, at 53.8%. PITCHf/x appears to have a larger strike zone than BIS).

It therefore appears Roark was exploiting his elite Z-pass rate often enough for it to be useful, and indeed for him to have an advantage over hitters. Roark accumulated strikes at a good rate; and, by strongly suppressing swings at pitches in the zone, he lowered the risk of allowing a hit. It appears this dynamic was a main factor in Roark’s success in 2013. That’s part of the answer to our “How did he perform so well” question.

Another factor which stands out from Roark’s strike-zone data is that he threw first-pitch strikes 70.6% of the time. This tied for third in major-league pitchers with at least 50 innings in 2013. Consistently gaining an initial advantage over hitters, and doing so at an elite rate, was another main factor in Roark’s success.

Other discussions of Roark have cited his command, his aggression, and an improved mental approach. Going back to Adam Kilgore, he writes:

Roark’s ascension began last season, when he told himself he would not allow his temper to control him on the mound. He would not the things out of his control – fluky hits, errors, whatever – distract him. He would throw strikes. He would be confident. He would attack, above all else.

“I feel that last year is when I had my, I guess, mental turnaround,” Roark said. “That was the biggest thing for me.”

(Washington Post, Nationals Journal, 9/17/2013;

We can certainly see command at work in Roark’s low homer rate, and his low walk rate (5.4%). We can see both command and aggression at work in his first-pitch strike rate. Roark’s league-leading Z-pass rate substantiates the command/aggression understanding of his performance, and also adds to this understanding.

A pitcher who suppresses swings on pitches within the zone is presumably hitting unattractive parts of the zone, but he may also be throwing in-zone pitches which do not present to hitters as strikes. This sounds like a pitcher on whom it is difficult to make good contact. This is a third idea, beyond Z-pass rate and first-pitch strike rate. One way, however, to be averse to good contact is to be a high Z-pass pitcher.

Being a high Z-pass pitcher does not entail being a high strikeout pitcher. Roark’s strikeout rate was only one percent below major-league average (again, among pitchers with 50 innings and up). Of course, on other measures, like ERA, Roark was much better than league average. I think that connecting Z-pass rate with suppression of good contact can help us understand why.

Z-passes represent hittable pitches – pitches in the zone – which were not hittable enough to induce a swing. Poetically speaking, Z-passes involve real visual ambiguity: since they end up in the strike zone, they can’t look that bad; but they do not look good enough to induce a swing.

How well does this characterization actually apply to Roark’s pitches? On this question, we have the following from the Atlanta Braves:

“He wasn’t missing with any pitches over the plate, it seemed like,” said Braves catcher Gerald Laird. “When he was going away, he was throwing that little two-seamer back door, when he was coming in he was running that two-seamer in on your hands, and he had that little slider working.

“Tonight it seemed like he was hitting his spots and wasn’t making any mistakes. I know (Freddie Freeman) was saying he was starting it at him and running it back over. When he’s doing that it’s hard to pull the trigger.”


Of course, these descriptions of visual ambiguity — or of evidence which shifts within a fraction of a second — presumably apply to all or most of a high Z-pass pitcher’s offerings, not just to his pitches in the strike zone which do not elicit a swing. The image that emerges is of a player whose whole volume of pitches is tough to react to in a manner that creates good contact.

Roark was actually pretty good at inhibiting contact of any kind, especially on pitches within the strike zone. However, a look at his contact numbers does not immediately confirm this interesting and important point. As we see in the table below (from BIS by way of FanGraphs, again looking at 50+ IP), many of Roark’s contact rates were actually above league average, sometimes by more than one standard deviation.




















MLB (50+ IP)










std dev










Before turning to contact rates, you will have noticed that this table also gives us a look at how Roark’s Z-swing rate compared to the rest of baseball. According to BIS, Roark was 3 standard deviations above average on a positive pitching statistic which is completely independent of fielding. He was two standard deviations (56% Z-Swing%, as opposed to 63% league average) ahead according to PITCHf/x — this is still pretty good for a former 25th-round pick! Some other observations:

  • O-contact. Here Roark was much higher than average, but this may not be a bad thing, since contact outside the zone is less likely to be productive for the hitter.
  • Z-contact. Roark again was higher than average. But this somewhat unsettling number should not be digested outside of its relevant context, which is helpfully provided by Roark’s Z-swing rate. Looking at Z-contact multiplied by Z-swing yields the interesting result that Roark allowed contact on 51 percent of his strike zone pitches, as opposed to a league average of 57 percent, with a standard deviation of 3 percent.

(PITCHf/x condenses this gap, in much the same way that it condenses the gap between Roark and MLB on Z-pass. PITCHf/x reports Roark at 52.2% contact on all pitches within the zone, and MLB at 54.6%. Thus, if we switch from BIS to PITCHf/x, Roark’s contact rate goes up, and MLB’s goes down.

However, as noted above, PITCHf/x appears to be working with a larger strike zone than BIS (MLB-average Zone% of 49.3 vs. MLB-average Zone% of 44.9). This point complicates Roark’s apparent movement back towards league average. In brief, the fact that Roark’s swing rates go up — while the MLB average goes down — on larger renditions of the strike zone may be a testament to his effectiveness, rather than a knock against it.

  • SwStr (swinging strikes/total pitches). Since Roark did a good job suppressing contact within the zone, Roark’s low swinging-strike number does not seem to be an especially important piece in his overall puzzle.

The standard contact rates reported by BIS and PITCHf/x do not do a good job of communicating how well a pitcher actually prevents contact, because these contact rates only look at swings. Since you can suppress contact by suppressing swings, multiplying the contact rate by the swing rate provides a better view of how a pitcher is actually doing along this dimension. Despite a “zone-contact” rate which was higher than league average, Roark was very good to excellent at suppressing contact within the strike zone.

We are exploring a clue provided by Roark’s excellent Z-pass rate that Roark was good at inhibiting solid contact. This clue was supported by our look at Roark’s contact rates, which indicate that he was pretty good at suppressing contact flat out. The idea that Roark’s pitches were visually ambiguous enough to limit good contact receives further confirmation from his batted-ball statistics. In addition, looking at these statistics (2013, 50+ IP) will bring us around nicely to the question of how well Roark might sustain his performance in future seasons.
















MLB (50+ IP)








Std dev








Roark’s ground-ball, fly-ball, and infield-fly rates combine to indicate a strong bias against good contact. Roark had a somewhat high line drive rate, and, admittedly, line drives are a form of good contact. For instance, I suspect it’s unusual to have a somewhat high line-drive rate and a markedly low BABIP. Roark’s line-drive rate provides one specific indication that his BABIP is due to increase. However, a low line-drive rate is not entirely at odds with the idea that a pitcher is suppressing good contact — especially if we are thinking about home runs. Since most line drives are not home runs, a slight tendency towards line drives is a small but genuine homer-prevention measure.

In this way, Roark’s line drive rate coheres with his ground-ball, fly-ball, and infield-fly rate statistics. All of these rates, and especially their combination, suggest a low-homer pitcher. Why didn’t Roark give up a lot of home runs? Well, he got a lot of grounders and infield flies, while limiting his fly balls overall, and he gave up a somewhat high proportion of line drives. It is very plausible to suppose that Roark’s extremely low HR/FB rate overshoots the anti-homer bias suggested by his other batted-ball rates. Equally, however, the other rates tell a clear enough story that a low homer rate is not at all a surprise. Roark was very good at inhibiting good contact.

How will he do in the future? A nice way to frame this question is in terms of Roark’s ERA, FIP, and xFIP numbers mentioned earlier. And, leading up to that, I think it’s helpful to assess the respective importance of two things: (1): the overall coherence of Roark’s 2013 statistics; and (2) the sample sizes in which they were achieved.

In terms of coherence, Roark’s statistics tell a consistent story:

  • Looking at Z-pass, Roark was very good at limiting swings on good pitches
  • Looking at Z-swing * Zone%, Roark was very good at limiting contact within the zone
  • Looking at his batted ball rates, Roark was very good at limiting good contact

I could be wrong about this, but I do not see relationships among Roark’s 2013 statistics which point to trouble looking ahead. These statistics tell a consistent story of effectiveness. You can focus on his low swinging-strike rate if you like, but this rate was consistent with Roark being at least one standard deviation (two sd’s according to BIS) better than average on limiting contact within the zone.

In addition, there are pockets within Roark’s portfolio where some stats are very good and others are even better, like the HR/FB rate relative to Roarks other batted-ball statistics. However, this type of overshooting is a good problem to have. To the extent that the non-harmonic components of Roark’s statistical portfolio are extremely good statistics, this relates to the issue of our expectations for future years. A version of Tanner Roark based on 2013, but without the extra anti-homer overshooting, would still be above MLB-average.

As noted above, Roark only pitched 53 innings, and that’s a much lower total than what a starting pitcher would typically accumulate over a full year. Although we intuitively regard this as a small sample, it does not follow that Roark’s performance is without predictive value. As is often pointed out on the pages of FanGraphs, statistics stabilize, or acquire predictive value, at different thresholds ( Generally speaking, fielding-independent stats stabilize more quickly for pitchers than fielding dependent stats; this is a helpful point in assessing the forward relevance of Roark’s 53 innings.

Some of Roark’s relevant statistics are above their stabilization thresholds. Roark allowed 153 balls in play (BIP), which puts him above the stabilization points for groundball rate and flyball rate:

70 BIP: GB rate

70 BIP: FB rate

Roark faced 204 batters, which is above the stabilization points for walks and strikeouts:

70 BF: Strikeout rate

170 BF: Walk rate

However, Roark was league-average in K’s and was “only” one standard deviation above average in walks; these numbers are not as good as Roark’s plate discipline statistics like Z-pass and suppression of contact within the zone. So it’s not clear whether Roark reached the stabilization points for key parts of his performance.

But this is more or less where I will have to leave it. Figuring out the stabilization point for Z-pass is beyond the scope of the present study. Indeed, my post has probably pushed us to near overload regarding things that we ever wanted to know about Tanner Roark! By the same token, it’s not clear that learning more about Roark’s statistical profile would shift our opinion much about his prospects for future performance. This is what I think we have to consider:

In an intuitively small sample size, Roark put up a consistent portfolio of excellent fielding-independent stats: on limiting zone-swings, limiting contact in the zone, and limiting good contact. Very broadly, the size of a sample has to be balanced with the consistency of the evidence within it. Just imagine watching a one-round boxing match in which one competitor knocks the other one down three times. This is a small sample which tells a very compelling story about the respective abilities of the boxers. Roark’s sample size is larger, of course, and his performance was not as dominant. Nonetheless, his limited 2013 season is packed with a lot of positive indicators.

Here are a few final comments about what Roark might do in the future, framed in terms of his ERA, FIP, and xFIP:








MLB average (50+IP)




standard deviation




As we discussed above, the delta between Roark’s ERA and FIP is primarily a matter of his low BABIP and his very low homer rate. Although Roark’s BABIP will probably go up, there are signs he may be better than average at suppressing hits: he showed a tendency to induce ground balls and infield flies; the latter especially inhibit BABIP.

Roark’s very low homer rate pulls down both his ERA and his FIP. Although his .17 homers per 9 innings will almost certainly go up, there are signs he may be better than average at suppressing home runs…signs which are distinct, that is, from his one homer allowed in 53 2/3 major league innings!! Roark’s tendencies toward ground balls, infield flies, and line drives are all anti-homer measures. These tendencies flow, by hypothesis, from his ability to inhibit good contact by throwing visually ambiguous pitches.

The most eligible view by far is that Roark will regress towards league average in future years. But accepting this view should not deprive us of optimism. Roark could go back at least one standard deviation on each of the ERA-like measures and still be at league average or better than league average. That’s a good position for any pitcher. It’s a great position, albeit a paradoxical one, for a pitcher who is currently slated to compete for no better than the 5th spot in the Washington Nationals’ 2014 starting rotation!! Suffice to say I think that Roark ought to receive full consideration for the opportunities available to him.