For the last year and a half, Adam Wainwright has been singing the same tune after bad starts.

“My arm feels great. My body feels great. I know what adjustments I need to make. I’ll be back.” Cardinals fans have heard those lines from Uncle Charlie since his struggles began. For all of 2016, and most of this season, the idea of Wainwright returning to pre-Achilles tear form seemed preposterous.

There have been games in which Wainwright looked like he should hang it up, like June 6 against Cincinnati (otherwise known as the Scooter Gennett game). At other times, he looked a lot like the Adam Wainwright of 2012-2014, like May 27 at Colorado. That day, he went seven shutout innings at Coors Field, and only gave up three hits.

Wainwright’s ERA is 5.20 going into Monday’s start in New York. But, if you take out the 24 runs allowed in 6 1/3 innings against Miami, Cincinnati, and Baltimore, his ERA would be 3.14. That would be top-10 in the NL, as Jose de Jesus Ortiz noted in the Post-Dispatch.

Why the wild discrepancy? I looked at each start Wainwright has made this season, and divided them into two groups: quality starts and non-quality starts.

Usage Rates

The first thing I looked at was how often he throws each pitch, broken up by quality starts and non-quality starts.

There’s not much to see here. The only significant change is that Wainwright throws more four-seam fastballs in quality starts, but that’s offset by an increase in sinkers in non-quality starts. Either way, the variance isn’t enough to account for such a massive discrepancy in outcome.

Velocity

If Wainwright isn’t mixing his pitches differently, maybe he just throws them harder (or slower) on certain days. Thanks to Brooks Baseball, took the average velocity of each of his pitches in every start. Then, I calculated the quality start average velocity and the non-quality start average velocity.

Again, not what I expected. Since Wainwright is a pitcher presumably in decline due to age, I didn’t expect to see him throwing harder in his bad outings. Wainwright has only thrown his four-seamer harder in quality starts than non-quality starts, and the difference was only 0.5 miles per hour. He’s thrown every other pitch harder in non-quality starts.

At this point, after many calculations, I was beginning to get discouraged.

Changing Speeds

On Brooks Baseball, if you click on a pitchers game log, it will show usage rates, strike percentages, average velocity, and max velocity. I didn’t intend to track max velocity, but I noticed something as I went along: it seemed like the difference between Wainwright’s average velocity and max velocity was greater in quality starts.

I know that’s a lot of numbers, but bear with me. The key columns are the two right-most. In quality starts, Wainwright has more velocity variance in every pitch except the four-seamer (I excluded the change from this analysis because he doesn’t throw it often enough).

I especially want to focus on the cutter and the curve, since up to June 22 opponents were hitting .286 against the curve and slugging .512 against the cutter.

In Wainwright’s last start against the Mets, his average cutter was 82.8 miles per hour. He also ran it up to 88.5 miles per hour. On that afternoon, hitters had to deal a pitch that moves a fair amount, but could also come at them at any speed within an eight to ten mile per hour range (if the average is 82.8, there had to have been some slower than that). In that same start, he threw his curve between 71.9 miles per hour and 76.5.

Doubling Down

In his last four starts, it appears Wainwright has doubled down on changing speeds within the same pitch.

I looks like Wainwright has made an adjustment. It’s not a surprising one, as Wainwright is the type of pitcher that would alter the tempo of his delivery in order to disrupt the timing of the hitters. The league might adjust to him. However, if this is sustainable, Adam Wainwright might have found his way to continue pitching at a high level for several more years.

This article first appeared in The Redbird Daily.

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 have included anonymous descriptions of three players. The descriptions include stats that were compiled by  those players a little before the All-Star break.

I have included a link to a Google Survey (at the end of this article). No information is being collected other than your responses. (The survey also includes an optional question about your personal assessment of your baseball knowledge).

The question is: Which player would you rather have for the rest of this season?

Please keep the following facts in mind when answering the question:

1. The league average BABIP is .299.
2.  The league average K% is 21.6%
3. The league average BB% is 8.6%
4. The league average HR/H is 14.5%
5. On average in the league, 33% of the time a bat touches the ball, a hit occurs.

Player 1: “Frank”

Frank is a young hitting prospect. He has little major-league track record outside of the first half of this season, and he was considered a top prospect coming up through the minor leagues. He has been described as “freakish” in his size.

Frank strikes out nearly 30% of the time and walks nearly 17% of the time. 53% of the time his bat touches the ball a hit occurs. 30% of those hits are home runs.

Frank compiled these numbers through 81 Games and 352 PA.

Player 2: “Tom”

Tom is a young player, but he has been around long enough that he is verging on a veteran. He has been described as a “model slugger.”

Now in his eighth season, Tom has a career BABIP of .320, K% of roughly 28%, BB% of roughly 11%, and HR/H Ratio of 26%.

This season his BABIP is .299, his BB% is 10.5%, and his K% is roughly 24%. 38% of the time his bat touches the ball a hit occurs. 27% of those hits are home runs.

Tom complied these numbers through 83 Games and 352 PA.

Player 3: “Dan”

Dan is a young player, but he has a considerable track record. He has been described as one of “the most valuable properties in the game.”

Now in his sixth season, Dan has a career BABIP of .301, K% of roughly 17%, BB% of roughly 7%, and HR/H Ratio of 16%.  

This season his BABIP is .234, his BB% is 8.6%, and his K% is roughly 20%. 29% of the time his bat touches the ball a hit occurs. 24% of those hits are home runs.

Dan compiled these numbers through 82 Games and 360 PA.

Here is the survey link: https://goo.gl/forms/Fd7StZznZqQ5Brth2

I will follow up with an article a week after this is published, showing the results, revealing who the players are, and assessing what the projections expect from those players the rest of the year.

T.J. Rivera has had a remarkably unlikely path to the majors, going from an undrafted free agent to now the Mets’ starting third baseman. He has always had his doubters, and still does, but he got to the majors by consistently putting up around a .300 average in the minors with an above-average OPS despite his lack of walks and power. In 2016, a hitter-friendly park helped him enjoy a career year in Triple-A, winning the PCL batting title with a .353 average, a .909 OPS, a 142 wRC+ and a promotion to the majors for the first time in his career at the age of 27. He continued his success into the majors, where he was a key piece in the Mets’ 2016 Wild Card run. He was able to replicate the numbers he had put up during his entire minors career, batting .333/.345/.443 with a 119 wRC+ in 113 plate appearances.

Rivera’s impressive and somewhat surprising debut stint in the majors eased some of the concerns scouts had with his game, but plenty of people still had their doubts. The expectation was that Rivera would not be able to hit for a .300+ batting average in the majors like he did in the minors due to the tougher competition and better defenses. Rivera proved them wrong by hitting .333, although he was admittedly helped out by an unsustainable but certainly not outrageous .360 BABIP. Rivera posted BABIPs comfortably over .300 in the minors, so while some regression seemed to be in store for his future, it was certainly not crazy to predict that Rivera would still be able to hold a .300 average in the majors. If he had any chance of becoming a full-time starter at the highest level, he was going to need to keep that batting average in the vicinity of .300 to make up for his lack of other skills, such as patience, power, and defensive ability.

Rivera has always been known as a line-drive hitter with an aggressive approach at the plate. He likes to swing early in counts, and as a result he doesn’t walk much, but at the same time he is a contact hitter and doesn’t let his aggressive approach negatively affect his strikeouts. He doesn’t have much natural power, so for him to be successful, he just has to continue focusing on trying to hit line drives to the gaps and swinging at the right pitches.

In his first sample of major-league pitching, he was able to hit line drives at an above-average rate of 23.9%, compared to the MLB average rate of about 21%. It’s worth mentioning that this rate was higher than his typical LD% in the minors, showing that he was actually hitting more line drives vs. major-league pitching than minor-league pitching. He hit ground balls at a rate of 42.4%, which was also lower than he generally hit in the minors, and of course, preventing the amount of ground balls you hit leads to more success at the highest level, especially when you’re hitting them to the best infielders in the world. This GB% was slightly lower than the MLB average of about 45%, showing that some work could still be done on his GB% but that it wasn’t a serious problem. He also may have been helped about by a bit of luck on some of these ground balls, as he had a .360 BABIP that was sure to regress a little. Rather than hitting ground balls, the thing he needed to work on was hitting fly balls, which he did at a slightly below-average rate of 33.7%. For someone with not a lot of raw power, hitting more fly balls would be beneficial to making the most of whatever power he did have.

Overall, Rivera’s results in the majors had been a very pleasant surprise, don’t get me wrong. The key thing he showed in his 2016 debut is that he was not over-matched by major-league pitching, continuing to do the same things that made him successful in the minors. But in 113 plate appearances, he drew a grand total of three walks, which won’t quite cut it if you want to be an everyday starter. In addition to that, he was only making hard contact (according to FanGraphs) 27.2% of the time, below the MLB average of about 31%. Being the line-drive hitter that he was, he had the ability to hit the ball harder, and the thing he needed to do was to focus on hitting more fly balls and improving his launch angle by just a tick. This doesn’t mean that he needed to become a completely different hitter, but hitting the ball a little higher in the air more rather than on the ground or in a straight line would benefit him in not only his average but his isolated power, and also help him hit for a BABIP that would be less likely to regress.

Things got off to a bit of a slow start in 2017 due to lack of playing time and a short stint in Triple-A, but as injuries have befuddled the Mets, he has received more and more playing time, and at this point has basically hit himself into a starting role at third base.

As of July 15^th, Rivera has hit .304/.350/.464. A chunk of this production has come in his last 10 games, where he’s hit nearly .500 en route to a 10-game hitting streak. Still, that batting line is “classic T.J.” At first glance it might seem like a small drop-off from last year, but if you look a little deeper, Rivera has actually improved in quite a few areas compared to last year.

First off, he has slightly decreased his soft-contact rate since last year by 2% while increasing his hard-contact rate by 4.2%. Immediately this looks like a recipe for success; hitting the ball harder more often and softer less often cannot be a bad thing.

While hitting the ball harder compared to last year, he’s also hit more fly balls, improving from a slightly below-average 33.7% last year to an above-average 40.1% this year, while also decreasing his GB% by 6.9%. So he’s hitting the ball harder, he’s hitting more fly balls, and he’s hitting fewer ground balls. These were all little things that I mentioned earlier that he could tweak to become a more polished hitter, and he has improved slowly but surely in these minor aspects of his game.

But at heart, Rivera is still the same hitter, just a better version of himself. He’s still a line-drive machine, with an LD% just a tiny bit higher this year compared to last year (24.3 vs.23.9). This shows that he has improved on hitting the ball harder and in the air while still playing his usual game. And, as it should, hitting the ball harder has caused his ISO to increase from .143 to .160, meaning that he’s taking better advantage of the power he has.

While he is still aggressive and still likes to swing early in counts, he’s also improved his walk rate slightly, from a measly 2.7% to a still below-average 4.5%, as Rivera’s plate discipline has slightly improved this year. Here’s a graph of his amount of pitches swung at outside the zone (blue), inside the zone (red), and overall (yellow).

He’s become slightly more patient and selective, swinging at more pitches in the zone and fewer pitches out of the zone. The data also shows that he’s swinging at the right pitches, as here’s a graph of his contact rate outside the zone (blue), inside the zone (red), and overall (yellow).

As you can see, he’s making contact at about the same rate on pitches in the zone, while the pitches he’s going after that are outside the zone have generally been better pitches to hit, as you can see by his increased O-Contact%. Even more importantly, he’s swinging and missing less, as last year he swung and missed an above-average 12.1% of the time while this year he’s swinging and missing at a slightly below-average rate of 10.2%. Rivera will always be a contact-first type hitter, but he’s tweaked some minor flaws in his game and is actually molding into more of an all-around hitter than people may think.

So why is his batting line appear slightly worse than last year, if he’s doing so many things better? Well, it’s really only his batting average that has declined, and that’s mostly due to a BABIP .024 lower than last year. In the minors, Rivera had always been able to keep a BABIP in the mid-.300s, so with a BABIP of .336 this year and the fact that he’s hitting the ball harder and in the air, there shouldn’t be any regression this year; in fact, his batting average is more likely to go slightly up than down. He’s improved his on-base skill and power to the point where they are still below-average skills, but they are respectable enough that his excellence in hitting for average and hitting line drives outweighs them.

So T.J. Rivera really seems like a major-league starter this year, proving that his amazingly consistent minor-league numbers and impressive MLB debut were not flukes. His defense is admittedly mediocre, as he’s accumulated -2.0 defensive runs in his career according to FanGraphs. But there really is no doubt that he can hit. This guy now has a .322/.367/.439 batting line in 3,225 professional plate appearances, so I think it’s time to stop doubting what he can do and let him play every day, because with the improvements he’s made in his game and the way he’s been able to adjust to major-league pitching, he absolutely deserves it.

The phenomenon that was Aaron Judge’s first half was indeed a sight to behold. Thirty home runs before the All-Star break? Get in line for some hardware.

As some have noticed, as impressive as Judge’s power display has been, he is still a 25-year-old rookie. Now, it used to be that holding rookie status at 25 was perfectly fine, but Trout, Harper, Correa & Co. have jacked up rookie expectations a bit. Players as good as Judge has been at 25 are increasingly often almost this good at 22 or even younger.

But that’s not the point today.

The point today is this: Aaron Judge is on track to have an unprecedented season for a 25-year-old rookie.

Judge’s season already ranks 5th in home runs and 4th in WAR since 1901 for players with rookie status at 25 years of age. Even if he comes down to earth in the second half, he could — should — easily clear first place in both measurements. He only needs six home runs and 0.8 WAR do so. Additionally, his wRC+ has 30 points of leeway for him to maintain first place in that stat as well.

So, it will be a disappointment if Judge does not end up with the best 25-year-old rookie season ever.

Let’s not end the story there. I’d like to examine the full careers of some of those players who still, for now, rate ahead of Judge by wRC+ and home runs. We’ll keep things in the expansion era and stick to three: Tony Oliva in 1964, Mitchell Page in 1977, and Ron Kittle in 1983.

Tony Oliva, 1964 Minnesota Twins (32 HR | 148 wRC+ | 6.2 WAR)

Oliva never hit 30 home runs again and only once more exceeded a 148 wRC+, but he put together a terrific career for the Twins, with 41 WAR, 220 homers, a 129 wRC+. So he gives hope that even if Judge never hits for this much power again, he can still have a very fruitful career. This statement seems very modest now, but Page and Kittle weren’t so fortunate as Oliva.

Mitchell Page, 1977 Oakland Athletics (21 HR | 157 wRC+ | 6.2 WAR)

Page radiated brilliance as a rookie, competence as a sophomore, and was then roughly replacement level for the remainder of his career. I can’t tell you much about what happened to Page, but this newspaper article is an interesting one. Injuries and a dispute with infamous owner Charlie Finley may well both have played a role in Page’s decline.

Unlike Judge, Oliva, and Kittle, Page’s game was not reliant on home-run power. He hit 28 doubles, 8 triples, and stole 42 bases in 1977. But he probably had the best rookie season we’d seen from a 25-year-old until this year. Unfortunately, the rest of his career did not live up to that standard.

Ron Kittle, 1983 Chicago White Sox (35 HR | 118 wRC+ | 2.0 WAR)

Kittle currently holds the “record” for most home runs by a 25-year-old rookie, but he had a weaker rookie year than Oliva or Paige. He also hit 32 home runs the next year, 26 the year after that, and then 21. After that, he never hit more than 18 and could never again make 400 plate appearances in a season. Kittle was great in 1988-89 but only had a combined 450 PA those years, putting up 2.8 WAR and 29 homers.

Kittle ended up hitting a home run every 17 times he stepped to the plate in his career; he just didn’t step to the plate often enough, field well enough, or run the bases well enough to gain more than 5.2 WAR in 3013 PA.

It takes more than power to succeed at major-league baseball. Judge seems to have more than just power, with six steals and a potentially decent glove in right field. He’ll still have to maintain other skills — and stay healthy — to avoid Kittle’s fate. He is very likely to do so, but nothing should be taken for granted.

Conclusion

Oliva, Page, and Kittle (or Jimmie Hall, whose career ended up looking like a rich man’s Kittle or poor man’s Oliva) can’t really tell us all that much about what Aaron Judge’s future may hold.

They are only three players out of many, and we didn’t even look at 24- and 26-year-old rookies.

Kenny Lofton was also a 25-year-old rookie who performed admirably and went on to produce a fantastic career, and whose rookie year did not end up a career year. We didn’t look at Lofton because he is such a different player than Judge, but Lofton is a much better precedent for 25-year-old rookies looking to build on their success than Oliva, Page, and Kittle.

Mark Trumbo is also worth mentioning. He hit 29 home runs as a rookie and has since exceeded that mark three times, although his non-power skills have always been lacking.

This piece is getting longer than expected and it’s time to wrap up.

The careers of Oliva, Page, Kittle, and Hall do contain a couple potentially foreboding patterns. Their rookie home-run numbers remained their single-season career highs, and with the exception of Oliva in 1971 and Kittle in some parts of seasons, none of them ever improved on their wRC+ either.

Aaron Judge is his own player, and will almost certainly have a better rookie year than any of these three comparisons managed. Given that, we can also expect a better career than they managed. And, of course, it’s no shocker to suggest that a near-200 wRC+ will eventually regress.

However, perhaps it is worth wondering about the future of a 25-year-old rookie and whether to treat it the same as a, say, 22-year-old’s future.

Or perhaps it’s not. Regardless, you should ignore me anyway and enjoy Aaron Judge’s mammoth displays of power. The Yankees certainly enjoy it.

Dodgers superstar ace Clayton Kershaw has already cemented himself as the greatest starting pitcher of this generation and could go down as one of the best of all time. Despite all his tremendous regular-season success, an ongoing narrative has haunted him throughout most of his career, a well-known theory that Kershaw chokes in the postseason and can’t pitch in big games.

But in reality, this actually hasn’t been the case, and the fact that so many people consider Kershaw to be a choke artist speaks more to his amazing regular-season dominance than any struggles he’s had in the playoffs. Through 282 starts in the regular season, Kershaw has an outstanding 2.35 ERA and 0.998 WHIP, so anything worse than that in the postseason is going to feel like a disappointment.

The main argument defending Kershaw’s postseason woes for awhile now has been lack of sample size. As Kershaw has reached the playoffs more and more this argument has weakened a little bit but is still relevant, as his 89 total postseason innings pitched is less than half of what Kershaw pitches in a typical regular season. It’s a large enough sample size that we can make some conclusions about how Kershaw has pitched in the playoffs, but not enough that we can judge his true-talent level. We have 1892.1 innings of regular-season data to judge his true-talent level.

Let’s start with the basic statistics. In 18 games (14 starts), Kershaw is 4-7 with a 4.55 ERA and a 1.16 WHIP. At first glance these numbers seem not horrific, but very underwhelming for what we’ve come to expect from Kershaw. This ERA is a mix of some very good starts and some not so good ones that evens out to a mediocre 4.55.

But as we start delving into the advanced statistics, Kershaw doesn’t look so bad. His FIP is a very good 3.13, with his xFIP about the same at 3.17. These stats take into account the things the pitcher can mostly control — strikeouts, walks and home runs — in an attempt to gauge a pitcher’s true-talent level in the sample size given, and are on the same scale as ERA. So in a sense, Kershaw has had some bad luck in the playoffs, and while the results still haven’t been as great as his regular-season results, he has still mostly pitched like himself.

But where does this FIP come from, and why is it so much lower than his ERA? FIP takes into account strikeouts, an area in which Kershaw has actually performed better in the postseason than in the regular season. In the regular season, he has averaged 9.88 K/9, while in the postseason, he has averaged 10.72 K/9. He has also kept his walks down in the playoffs, averaging 2.73 BB/9, which is only a little bit worse than his regular season 2.37. As a result, his 21.5 K-BB% in the postseason is nearly identical to his 21.2 regular season K-BB%. So the problems he’s had in the postseason haven’t had to do with walking too many hitters or not striking out any batters. In that regard, he’s still pitched like the Clayton Kershaw we know and love. So where have his issues come from?

The answer to that is a higher average on balls in play, a higher HR/FB%, and a bad bullpen coming in to relieve him. FIP also takes into account home runs, and he has allowed more home runs in the postseason, averaging 1.01 HR/9 (which is still good, just not Kershaw good) versus an outstanding 0.58 HR/9 in the regular season. It’s really not fair to criticize him too much for this since his postseason sample size is still less than half of a regular season. In fact, that 1.01 HR/9 is actually better than his 2017 regular season HR/9 so far, which is a very uncharacteristic 1.22 in a year where he’s been neck-and-neck with Max Scherzer for the Cy Young award. Kershaw has allowed more home runs in the postseason as a result of not only a slightly higher fly ball% but also a higher HR/FB%, 10.9 versus 7.7 in the regular season. While this doesn’t mean that he’s been unlucky, it does mean that his HR/FB% is likely to regress closer to his career norms. xFIP takes this into account and the number ends up being virtually the same as his FIP.

In addition to the extra home runs, Kershaw hasn’t been as lucky on balls in play as he has in his career. In the regular season, he’s held a .269 BABIP, which for most pitchers would be thought to be unsustainable, but Kershaw’s pitched for so long now that it’s become clear that he’s just that good. He hasn’t been quite as lucky in the postseason, where he’s allowed a .295 BABIP. And it’s not like Kershaw has allowed way more hard-hit balls in the playoffs than in the regular season, although he has allowed slightly more. He has a 20.1 line-drive rate in the playoffs, which is just slightly higher but very similar to his 19.8% in the regular season. Pitchers obviously try to prevent line drives, as they often result in hits, and Kershaw has prevented line drives from being hit about as well in the playoffs as in the regular season. So that’s not the problem.

Kershaw has allowed slightly more fly balls — 40.2 FB% versus 34.3% — and this, paired with the higher HR/FB%, makes for a bad combination and more home runs. He’s still allowed ground balls at a similar rate, only slightly less, at 39.7% versus 45.9%. So has Kershaw allowed more well-hit balls in the postseason than in the regular season? Yes, but only slightly, and not enough that he should be considered a choker. The only slight increase in line drives shouldn’t result in as big a gap in BABIP as it actually does, meaning that luck has not quite been on Kershaw’s side the way it has been in the regular season. He’s struck people out like regular-season Kershaw, he’s prevented walks like regular-season Kershaw, and he’s prevented balls from being well hit only slightly less than regular-season Kershaw. That, in addition to slightly more fly balls leaving the ballpark, has resulted in a really good pitcher that maybe is not quite as good as regular-season Kershaw, but still very good, and it certainly doesn’t warrant calling him a “choke artist.”

It can also be argued that Kershaw has been overused and over-pressured to do well. He’s been so ridiculously good in the regular season that the expectations are for him to be just as good in the playoffs and to do it practically every three or four days against the best teams in baseball. Anything less and he seem like a disappointment. People often overlook the great moments he’s had in the playoffs, like when he came out of the bullpen against the Nationals to save a tight game or when he dominated the eventual World Champion Cubs in Game 2 of the 2016 NLCS. As a result of high expectations and trust in Kershaw, he has perhaps been left in games slightly longer than he maybe should have.

An occurrence that has plagued Kershaw in the postseason a few times is going deep into games and then getting hit around before his exit from the game. He’s often left with men on base, and the relievers coming in after him haven’t exactly been kind to him, allowing nine of the 14 runners he’s left on base to score. Let’s say the bullpen comes in and dominates, stranding all 14 of those runners, and his postseason ERA drops from 4.55 all the way down to 3.64.

Also remember that in the playoffs, teams are in their full strength and effort, doing everything they possibly can to try and win. These are the best teams in baseball, the teams that had everything working well enough for 162 games to make it past all the other teams and into the playoffs. The offenses Kershaw has to face in the playoffs are going to generally be better than the average offense he might face throughout the season. It is not uncommon for great pitchers to have slightly worse results in the playoffs. Madison Bumgarner, a famous “postseason hero” for the Giants, has a postseason FIP only 0.02 better than Kershaw’s and an xFIP 0.43 worse than Kershaw’s. Luck can go in very different directions for some pitchers in small sample sizes, and this is a perfect example.

Look at Pedro Martinez. In more postseason innings pitched than Kershaw, he has a significantly worse FIP/xFIP (3.75/4.31) despite an unsustainable low BABIP of .257, lower than his regular season .279. And no one thinks of him as a postseason “choker.” Greg Maddux, another all-time great, also has a worse FIP/xFIP (3.66/4.45) than Kershaw in even more innings pitched (198). And nobody considers him a postseason choker. Roger Clemens is the same deal. 3.52 FIP, 3.91 xFIP in 199 innings pitched. These pitchers are still considered all-time greats despite having postseason numbers that are arguably worse than Kershaw’s.

This really goes to show just how good Kershaw has been in the regular season. He puts up godlike numbers and then when he puts up “only” good numbers in the playoffs, it seems like he’s bad in comparison. When you look at the aforementioned fellow all-time greats, it’s clear that Kershaw is not the first great pitcher to have a little trouble in the playoffs.

So has Kershaw been as utterly dominant in the playoffs as in the regular season? No. But has he been a choke artist who gives up eight runs every time he’s put under pressure? No, not at all. He has had some rough outings in the postseason, particularly against the Cardinals, where he hasn’t been able to dominate and take control of the game quite like normal, but he has also had plenty of good moments of great pitching and when he’s left with runners on base, his bullpen has mostly let him down. All he really needs is one great World Series run to erase this ongoing narrative once and for all. No matter what, these small hiccups in the playoffs shouldn’t diminish the legendary career that Clayton Kershaw is in the midst of.

The panel on ‘The Changing State of Sabermetrics: at the 2017 SABR convention in NYC with panelists Joel Sherman, Mark DeRosa, Vince Gennaro and Mike Petriello claimed that fewer balls are going into play and singles are actually down. They posed the question, “Are singles still a thing?”

With that in mind, we aimed to verify if these claims are true and what makes people feel that players are hitting fewer singles in today’s game.

We used data that’s current as of July 2, 2017.

NOTES:

• Data being visualized is from http://www.baseball-reference.com/leagues/NL/bat.shtml and http://www.baseball-reference.com/leagues/AL/bat.shtml on July 1, 2017.
• BABIP definition is taken from  http://www.fangraphs.com/library/pitching/babip/

Below you will see two charts illustrating the number of hits, home runs and strikeouts per game.

You can conclude three things from these graphs:

1. Over the past 10 seasons, strikeouts have been increasing dramatically — 1.94 K/Game in the AL and 1.52 per game in the NL.
2. Over the past 3 seasons, singles per game have dipped.
3. Over the past 3 seasons, HR per game have spiked higher than ever before.

In 2017, the New York Yankees have one of the best minor-league farm systems in all of baseball along with others such as the Braves, White Sox, and Astros. As a result, there are some talented players who get lost among the shuffle, and one of them is Thairo Estrada. Estrada has been splitting his time between shortstop and second base this season in Double-A Trenton, but more recently has made second base his everyday position since top prospect Jorge Mateo was called up to play shortstop. Despite getting an All-Star nod for the Eastern League this season, Estrada still does not get talked about as much as other Yankees infield prospects including Gleyber Torres, Miguel Andujar, and even Mateo. Overall, Estrada is definitely worth taking a second look at alongside these other prospects, as someone who could be a solid middle infielder in the majors one day.

Estrada’s line of work speaks for itself this season. While the minor leagues do not have as much access to advanced stats, having seen Estrada play every day this season has given me a unique perspective into the facets of his game. Estrada has proven he can make adjustments, as evidenced by his strikeout percentage dropping roughly 4% from last season. As a result, his BABIP has skyrocketed to .344, and he has a slash line of .320/.375/.418. I attribute his lower slugging percentage as well as his low home-run total of 4 to the dimensions of the ballpark in Trenton. Not only is it 330 feet down each line, but the ballpark sits on the banks of the Delaware River, which as a result creates high winds that knock down potential home runs. If Estrada played in Yankee Stadium every day, he has the potential to hit 20 home runs, as evidenced by Brett Gardner, who in his two years in Trenton (2006-2007) hit as many home runs as I did (0).

Estrada also has a knack for base-running. This may come as a surprise to some given that he has only stolen three bases and been caught stealing nine times. However, on balls hit into the gap or down the line, Estrada has the ability to take the extra base, which has resulted in his wRC+ being 121 this season. Additionally, his spray chart shows that he has the ability to hit the ball to all fields, which makes it tougher for defenses to scout him, and gives him more opportunities for hits. There may not be many stats on Estrada’s defense, but after struggling somewhat at shortstop, he has become far more comfortable at second base, and has not made an error in 19 games.

If Estrada can continue this performance, we might see him in the majors soon, and he could potentially create a great middle-infield combo with Jorge Mateo if Torres’ recover from Tommy John surgery doesn’t go according to plan. So far through 14 games in Trenton, Mateo has a slash line of .396/.508/.755 and a BABIP of .486. The high OBP is a result of Mateo walking in 15.2% of his plate appearances. If Estrada does not play for the Yankees, then the Yankees should be smart enough to utilize his value and include him in a trade package for a big-name player (Sonny Gray, anyone?).

If you take a look at the leaderboards on FanGraphs for all triple-A pitchers this year, you’ll find a surprising pitcher in the lead in FIP who is above two Rays pitchers, MVP of the Futures Game Brett Honeywell and Yonny Chirinos, along with surprising pitcher Buck Farmer. It’s Andrew Albers, with a 2.58 FIP in triple-A in 77.1 IP, 20 appearances, and 11 starts, with a less impressive 3.61 ERA, along with a sterling 2.77 xFIP.

What’s driving this 2.58 FIP? A strikeout rate of 9.54 per 9, with a measly 1.40 walks per 9 and .58 homers per 9, which is shockingly low, even for him. The home runs will likely increase as he isn’t getting too many ground balls; 46.2% is all right, but not elite. He is also getting a ton of infield pop-ups, with a shockingly high 21.9%. He has had very high infield pop-up numbers in the minors before, which make it easier to do as well as he had, although some negative regression should be expected.

Why his ERA is too high: He generally runs a high BABIP as it has usually been above .330 in the minors since 2015. This year his BABIP is a ridiculous .372 which is inflating his numbers above where can can truly perform at. It should regress to normal levels, maybe even a .320 BABIP perhaps, since minor-league defenses are worse than big-league defenses are (even the A’s pitiful defense).

His strikeout and walk rates are exceeding previous levels; last year in triple-A his walk rate was a good but not great 2.17 per 9, while his strikeout rate was a disappointing 6.08 per 9. I think he’ll likely negatively regress in his K/9 to around 7.5 per 9, walks to around 1.9/9.

But, there’s a chance that Albers could just be a second coming of Jamie Moyer, which could be useful for a big-league team looking for a cheap player to be their fifth starter, since he wouldn’t cost much on a minimum MLB contract or in prospects, and for all intents and purposes is a poor man’s Jason Vargas, who has been surprisingly good this year and is a Comeback Player of the Year candidate. It seems like Albers has made a serious adjustment in performance. Quite an interesting buy-low opportunity for a playoff hopeful that is tight on prospects (Angels, Royals), or tight on cash (Brewers, Rays, Twins, Royals). The Braves should have an extra selling chip that they didn’t know about before. Granted, they might get a lottery-ticket prospect for him, but the Braves are rebuilding, so they need prospects to try out at the big-league level eventually since a lot will flame out. Another pitcher who is similar to Albers is Wade LeBlanc, who I feel should be a starting pitcher for the Pirates, especially considering their rotation issues. But it seems like the thought of him starting is scarier to them than being in a saw trap.

It’s an idea that teams like the ones above should use to get underrated players cheap, while teams that have players like that should sell them for more value than they invested in the player. His best comp is of a right-handed pitcher who is with the Blue Jays: Marco Estrada. They have similar velocities, similar lack of performance till they got older, and get lots of pop-ups. Essentially, he is a left-handed version of Marco Estrada, and Marco Estrada received $26 million over two years after the 2015 season — quite an interesting thought. Especially considering his unimpressive stats in the majors so far. Let’s see if anyone will be willing to give him a chance as a swingman, as he could be an amazing fit on the Nationals; way better than Jacob Turner, and he could start in place of Joe Ross if he performs the way he has so far.

All stats from FanGraphs as of 7-13-2017. I do not own any stats or pages used to help me write this article.

To say that Kevin Siegrist has really struggled in 2017 would be an understatement. After allowing 15 earned runs in 31 appearances through June 22, he was placed on the DL with a cervical spine sprain. With an ERA near 5, Cardinals fans have been left wondering what happened to the player who led the league in appearances (81) and finished third in holds (28) in 2015.

At first glance, Siegrist has an obvious issue — a very clear and very serious velocity problem. Take a look at this graph.

The velocity of his fastball has decreased every year since 2013. It hovered around 95.8 mph at one point, but more recently it’s dropped well below 93 mph. That’s a significant decrease, as the steep slope indicates. And for the first time, Siegrist, who is a reliever, has a fastball velocity well below a league average that includes starting pitchers.

If you have ever looked at aging curves, for hitters or pitchers, then you know that skills decline with age. Certainly, pitching velocity is no exception to this rule. Still, Siegrist is an extreme case.

Velocity very clearly declines with age and Siegrist has fallen right in line with this trend. For the first two or three years of his career, his changes in velocity pretty closely matched the aging curve. However, for the last two years, there has been a marked decrease.

In case you haven’t gotten the point, here’s one more graphic that shows Siegrist’s velocity problem.

This slope looks more like something I would ski down than data you want to see from a pitcher’s velocity. Clearly, Siegrist had an excellent stretch in 2015 and he produced the numbers to back that up. Other than that, we see a pretty consistent decline.

So, is that it for Kevin Siegrist? A slow decline into oblivion? I don’t think so. I actually expect him to far surpass expectations in the second half of the year.

What if I told you, Siegrist has actually improved this year? He’s not telegraphing his pitches. He has improved his tunneling. (For extra reading, here are primers on tunneling from The Hardball Times, Baseball Prospectus, and FanGraphs.)

Essentially, tunneling is the ability of a pitcher to repeat his delivery with similar, if not identical, release points. If a pitcher is able to do this, a batter has less time to recognize the pitch and a lower chance of getting a hit. If a pitcher’s release points are completely different, say for his fastball and changeup, a hitter can more easily distinguish between the two and put a better swing on the ball.

These are Siegrist’s release points from 2015 (his most successful year).

And here are the release points from the first half of 2017.

Let’s keep in mind we’re talking about inches here, not feet. Still, the differences between these two years are significant. The release points from 2015 are more spread out than the data from 2017. Siegrist has improved his ability to replicate pitch deliveries. Unfortunately, due to his decreased velocity, this hasn’t resulted in any type of noticeable success.

In 2015, the changeup and the slider release points overlapped nicely, but the fastball release points stick out like a sore thumb. In 2017, with the addition of a cutter, there is much more overlap among the pitches. If he can keep this up, it should translate to long-term success.

Moving away from release points, pitch virtualization data confirms the same hypothesis: that Kevin Siegrist has improved his ability to replicate his delivery.

This is the data from 2015. To the average viewer, and even probably to you and me, this doesn’t look too bad. At the 55-foot mark, the pitches have pretty similar locations. Even at the 30-foot mark, it’s probably pretty difficult to distinguish between five of his six pitches.

If we compare it to the 2017 data, we see a considerable difference.

It’s pretty clear, right? At 55 feet, the release points aren’t “pretty similar,” to use my own wording, they’re practically identical. And the trajectories remain extremely close to one another until about the 20-foot mark, when they break. 20 feet at 93 miles per hour (an all-time low velocity for Siegrist) gives the batter about a tenth of a second to decide what to do.

There is no denying that Kevin Siegrist has a velocity problem that he would do well to fix. And if the first half of 2017 is any indication, it needs to happen fast. It is unfortunate that he has not been able to reap the benefits of an improved delivery. The consistency in release points that Siegrist has shown during an abysmal 2017 is encouraging and should provide a source of hope going into the second half of the season.