Archive for Player Analysis

I love pitching prospects. Not that I can back this statement up, but I believe pitchers make a more immediate impact on a fantasy roster than hitters. So, each year I stack my “Watch List” with young pitchers that might get called up in September, have a good shot of getting called up in June and potential breakout sleepers. Four years ago, one such player was Jimmy Nelson. How could a man that stands 6-6 at 245 lbs. not be on the radar? I watched with eager anticipation at all those strikeouts. That was four years ago and not much has changed. Both the Brewers and I seem to be in the same boat — waiting on Jimmy Nelson.

At one point, Nelson was the number one prospect in the Brewers’ organization. His fastball and slider were scouted as plus pitches and as such, Nelson was touted as a middle-of-the-order pitcher with potential to move up with the development of a third pitch. He was drafted in the 2^nd round, 64^th overall and is still just 26 years old. His aforementioned size gives him the frame to tax his arm with 200-plus innings each year. Plainly put, Nelson has the pedigree to be a stud and clearly the Brewers thought so too. Why then are we waiting three years into Nelson’s MLB career?

About 16 months ago, Mike Newman wrote about Nelson’s rising stock. That was prior to a year when Nelson had somewhat of a breakout campaign, going 11-13 with a 4.11 ERA and a 19.7 K%. If you recall he seemed to put things together in July to the point of striking out 32 in 33 IP with a sizzling 1.61 ERA. That’s when everyone jumped on board and expected big things in my fantasy league (10-team mix league, five keepers, deep rosters, 12 years running). July ended, however, and Nelson fizzled with the fading temperatures in 2015. His stock was mixed heading into this year (ADP 211, Yahoo!). It’s a new year now and the temps are starting to rise again. Will Nelson resurface as the potential ace he showed last July?

Last year Jimmy Nelson introduced a curveball to his arsenal, and it was good. The story on Nelson is that he always lacked confidence in his third pitch, the changeup. In the early going Nelson rarely threw that pitch. In order to get lefties out and develop into an ace Nelson needed a third pitch he was not only confident in but that could develop into a plus pitch. Maybe the curve was just what the doctor ordered. His pitch distribution looks like this.

In 2015, Nelson offered his newly-found curve 21% of the time while keeping his plus slider around (17%). 2016 seems to be a different story to this point. Nelson is throwing his fastball much more often and his off-speed pitches less, basically ditching the change all together. This has had two results: hitters are swinging less and making more contact. Z-contact% is creeping up to scary levels (93%).

Worse, so far, hitters are being patient with Nelson. It seems when Nelson goes outside the zone, hitters are laying off.

To summarize, hitters are swinging less at pitches, both inside and outside the zone, and making more contact, both inside and outside the zone, than ever before against Nelson. This is not a good sign. Dating back to Nelson’s early days, he has displayed control issues. What happens when hitters become patient against a pitcher with historic control issues? His walk rate increases.

Jimmy Nelson is progressing in the wrong direction. Hitters have adjusted to his curve and slider, they are being more patient, and they are making more contact. While Nelson’s K% has not dropped dramatically, his BB% is trending in the wrong direction. As a result his K-BB% is at an all-time high (in both the major and minor leagues).

I have something to confess. Prior to researching Jimmy Nelson I attempted to trade him in my fantasy league. To multiple teams. Multiple times. Here were my selling points: Pedigree, development of a third pitch and progression. So far this year Nelson has a 3.46 ERA, a 3-1 record, and he is still striking guys out at 17.9%. On the surface it looks like he is pitching to more contact and inducing weaker contact when he does; his 24.7% soft-contact rate is up from 19.2% last year.

One could be optimistic about this. I am not, however. His ERA is being supported by a .225 BABIP and a crazy 90% strand rate. Worse, pitching to contact is not a good strategy when fly-ball percentage is also trending in the wrong direction; up to 35% from 29% last year.

To wrap this lengthy post up I have several concerns with Jimmy Nelson. He’s always been known for having control issues and it seems he has not improved that yet. He’s developed a third pitch but is refusing to throw his plus slider and curveball more often. He’s inducing more contact but that contact is in the air. I am not searching for a way to “fix” Jimmy Nelson. His velocity seems to be consistent, perhaps just a tick down. His mechanics seem fine. There are no injuries to report. Rather, this post is about waiting on the ace that the Brewers thought they had. If that ace is going to emerge, Nelson is going to have trust in his slider and curve as he did in July of 2015. He’s going to have to find a way to induce more swings outside the zone. As it stands now, he is living dangerously inside the zone and will eventually run into major problems when those stranded runners come around to score as his BABIP rises. As deep as our fantasy league is, he still might be able to be moved. More than likely, however, he’ll remain what he has been — a middle- to back-end-of-the-rotation arm both in fantasy and real baseball.

After being taken in the first supplemental round of the 2010 MLB Draft, Taijuan Walker quickly established himself as a legitimate prospect due to his unique athleticism and his big-time fastball, which led to high strikeout totals in the low minors. He first appeared in Baseball America’s Top 100 list in 2012 at #20 as a 19-year-old, and at #18 in the 2013 list. Jonathan Mayo of MLB.com had Walker ranked as the #4(!?) overall prospect in both 2012 and 2013. But there always seemed to be questions regarding command issues and whether he would fully develop three pitches.

After a few cups of coffee in the Majors, three starts in 2013 and five starts in 2014, Walker broke camp in the starting rotation for the 2015 season. However, things were anything but successful to begin the season. In his first nine starts, the command issues that were a question while he was a prospect were alive in full force. He only made it through six innings in two of those first nine starts, and had 23 walks in 43 innings. He was running an ERA of 7.33 and an FIP of 5.48. Then, on May 29^th 2015, something clicked, as he went eight shutout innings, with two hits, no walks, and eight strikeouts. Ever since, Walker has been a very good starting pitcher, as you can see in the below table comparing before and after May 29^th 2015.

Look at that K-BB%! A 20% K-BB% puts him in some pretty elite company. Here’s the complete list of qualified SP that have a K-BB% greater than 20% since the beginning of 2015:

Not a bad group to be in! Ten guys that we think of as being aces, or near aces, and then Michael Pineda, a solid pitcher in his own right. It’s clear that limiting bases on balls has been key for Walker, and has probably been the main reason why he has improved so much. But why has he gone from walking over four batters per nine innings to around one batter per nine innings? From what I can gather, it looks like Walker tried to focus on two things: getting ahead in the count, and using his off-speed pitches more than he had been doing. In regards to the first point, as Eno Sarris wrote in June of 2015, Walker decreased the usage of his cutter, instead relying more on his fastball, which led to a significant increase in first-strike percentage. Since that start on May 29^th 2015, Walker has a 71% first-strike percentage when he throws his fastball in a 0-0 count, and has been pounding the zone with his fastball no matter what the count is. Information from Brooks Baseball:

Now for the second point, take a look at this article from the Seattle Times in early June 2015. Walker talks about how he was not comfortable with his old curveball, so he changed the grip to a similar one used by Felix Hernandez, and in addition, that he learned to throw a changeup. If we take a look at his pitch mix from before and after that May 29^th start, there is definitely a change in his arsenal. He has increased the usage of his curveball and changeup, suggesting that he has finally gained confidence in his off-speed pitches. Information from Brooks Baseball, but what they are calling a splitter I believe to be his changeup.

To get to the point of the title of this article, has Walker now become the best pitcher in Seattle’s rotation? The truth is that he has pitched like it since that start on 5/29/15. Using the same stats from earlier, here is how he has performed compared to Felix Hernandez over that time frame:

Looking at this table, I don’t know if I should be more excited about Walker, or more worried about the King. That being said, you can’t help but be impressed by what Walker has done over his last 24 starts. While the Mariners have the longest playoff drought in all of baseball, and have put together some pretty terrible and/or under-performing teams as of late, a bona fide ace is the one thing that they have had almost since when Felix made his debut in 2005. Walker is not currently a top-15 pitcher, and may never develop into that, but it is clear that at just 23 years old he is becoming a top-of-the-rotation type of pitcher. At a time when it appears that King Felix has entered into a decline phase, the Mariners may have found someone to front their rotation for years to come.

C.R.A.P.  It’s a fairly modern affliction that affects a great deal of people like you and me — and by ‘you and me’ I mean internet users.  It’s clear that the internet, like all of mankind’s greatest achievements, is not without drawbacks.  Never before have we been so connected, and never before have we heard the terms: Athazagoraphobia (Fear of missing out), ‘Paradox of Choice’, and ‘Intellectual Technologies’ (just Google it — because I can’t remember what it means).  The level of connectedness is so intense that on a day-to-day basis, I feel like I meet people whose personalities are plagiarized patchworks of charismatic, yet ill-informed internet voices (myself included).  And then, of course, there’s C.R.A.P., which stands for Combative Responses to Antipodal Posts.  An amusing component of C.R.A.P. is the ferocity with which contrary opinions are met with online; I have experienced 30 years of life and not once have I heard strangers communicate with each other in the manner that they do in the comments section of baseball blog posts on the internet.

To be clear, I’m not completely condemning the common vernacular found in said comments sections, because debate and conversation simply happen differently when we’re responding to a pun that’s a screen name rather than a face with eyes.  On Thursday, the 21st of April, Jeff Sullivan wrote a piece titled, The Case for Noah Syndergaard as Baseball’s Best Pitcher, and the comments section is littered with people who suffer from C.R.A.P.  In my opinion, if you actually read the article, you’d be able to tell that Jeff isn’t declaring Syndergaard the best pitcher, but based on his stuff and recent results, there’s definitely a case for it, hence the title.  Essentially, I think Jeff is saying that it’s possible Syndergaard is taking that step, and he’s open to the idea.  Jeff did a great job (as always, thank you, Jeff) as evidenced by reactions to the article.  He got us thinking and he got us discussing — some of us liked what Jeff had to say and some of us clearly weren’t receptive to the idea.  At all.  To his credit, Jeff did exactly what he’s supposed to do.

Now before we nosedive into the reasoning behind the outlandish title of this article, I want to get a few things out of the way: First and foremost, I’m sorry for throwing gasoline on an already raging fire.  Second, I think Clayton Kershaw is the best pitcher in baseball because of his sustained dominance (1.98 ERA over his last 1066.1 IP).  Certainly that doesn’t mean that pitchers can’t be better than Kershaw for a period of time, however, it’s just that while others rise and fall to his level, Kershaw remains.  And finally, I think Pedro Martinez is the best pitcher of all time.  That’s partly because I was born in 1985, and partly because I read it on the internet.  Mentioning Pedro is a good time to tie back into Jeff’s article.  To quote:

…Right now, in 2016, Syndergaard has a 23 ERA- and a 22 FIP-, through three starts…

Believe it or not, Kershaw has 37 three-start stretches with an ERA- no higher than 23. He has just seven three-start stretches with an FIP- no higher than 22. What Syndergaard is doing, Kershaw has done several times. But it’s not like this is Kershaw’s resting level. And Syndergaard is just as much about the scouting as he is about the stats.

That 23 ERA- just happens to be the number I was looking for.  During his peak (97 – 03), Pedro was preposterously good, posting a K-BB% of 26.1%, a 47 ERA-, and a 52 FIP-.  The acme of his peak came in a 22-game stretch spanning the 1999-2000 seasons when he posted an ERA- of 23 and an FIP- of 33.  His K-BB% was an unruly 34%, and he allowed just 95 hits in 168.1 IP.  Marvel at the overall line: 

August 3, 1999 – June 14, 2000

Again, that 23 ERA- is what I’m focusing on because it’s the number we saw in Mr. Sullivan’s article.  I could not find a better or equal stretch of dominance, based on ERA-, over 22 games, than Pedro’s going back to 1969…until Jake Arrieta.  Looking at only regular-season games, dating back to July 2nd of 2015, Arrieta has produced that magic 23 ERA- number we’re looking for:

July 2, 2015 – April 21, 2016

For those of you who prefer FIP I say leave your C.R.A.P. in the comments section, because as we gain more data, we learn that pitchers have some modicum of control over the quality of contact they allow, and at this point it’s probably safe to say that Jake Arrieta is a proven FIP-beater, even if he’s earned this title in less time than it takes others.  But Arrieta’s streak is now actually at 24 starts in the regular season, and two of those have been no-hitters.  His line:

June 21, 2015 – April 21, 2016

Pop the confetti!  Blow your vuvuzelas! Or Tweet!  That 22 ERA- is something we’ve never seen over such a large quantity of starts (at least going back to 1969 — and at least with my hack-job research)!

What this means in the scope of baseball’s long history isn’t nothing.  It’s a marvelous line.  Of course, it is just one number I’m looking at, and ERA-, like the internet, is not without flaws.  It’s arguable and perhaps even likely that Pedro’s line, with that 34.0% K-BB%, is more impressive (that mark was 293% better than league average — lolz).  But Arrieta has two no-hitters.  However, if we look at quality of opponents, well, Pedro’s line becomes more impressive because the teams he squared off against combined for an average wRC+ of 102, whereas Arrieta’s opponents averaged 94 wRC+.

Dave Cameron wrote an article about Arrieta’s ability to control the quality of contact he allows, and as we learn more about this skill, perhaps we’ll revere it a little more — never as much as strikeouts, but definitely more than we do now.  One of Jeff’s points about Syndergaard is that he undoubtedly has the arsenal and command to become the game’s top arm.  Arrieta has legit weaponry as well, but I don’t think anything we’ve ever seen from a starter matches what Syndergaard is throwing.  We know Arrieta’s story up to this point, which makes his sudden-ish ascent to a level where he can put a streak together like the one he’s on more interesting, if not more impressive.  What he does from now until the end of his career will go a long way in determining the weight this current streak holds.  If he flames out, or loses his ability to induce weak contact, it will be seen as a lucky blip; but if he rallies off another few years of 5 – 8 WARs and 50 ERA-es, then we’ll feel better about objectively putting his streak into an historical perspective.  As of right now, even despite his current run, I’m nowhere near putting Arrieta’s name in with the all-time greats (yes, the title was click-bait, spare me the C.R.A.P.), but, like Jeff in regards to how he feels about Syndergaard, but to a lesser extent, I’m open to it.  And that’s about as far as it goes for me — but I’m so contented to sit here and watch the debate unfold, violently, online.

The hypothesis: Troy Tulowitzki has a longer reaction time to pitches than he used to.  Reaction time, in this sense, refers to the overall time it takes Tulo to decide to swing and then execute the swing.  Perhaps he is only getting slower mentally, perhaps only physically, perhaps a mix of both. Regardless the source of his decline, my hypothesis is that Tulo has been slower to react since the beginning of 2015 than he has over the rest of his career. I posit that Tulo’s decline and the league’s increase in velocity have caused him to pass a “tipping point,” which has kneecapped his production.

Now for the evidence.

Here is a profile of Tulo’s swing rates from Brooks Baseball.  The data are from 2008-2014, before his decline.

Figure 1. Swings/pitch 2008 to 2014.

Throughout his career, Tulo has preferred to swing at pitches middle in and up in the zone.  Now consider where he did his damage.

Figure 2. Slugging on contact 2008 to 2014.

Again, Tulo seemed to prefer the ball up.  He was most dangerous in the top two thirds of the zone and he could cover the entire width of the plate.

Location is important because the reaction time required to hit a pitch changes depending on where it is located in the zone.  A pitch gains velocity as it moves up in the zone, or as it moves toward the hitter, while pitches are effectively slower as they move down and away. Historically, Tulo has been most dangerous on pitches in the areas of the zone that require the shortest reaction times to hit.

Now consider how productive he’s been since the beginning of 2015.

Figure 3. Slugging on contact 2015 to present.

Aside from the overall decline in the production in nearly all zones, it is noteworthy that Tulo’s most productive area has shifted from the top to the bottom of the zone.  From 2008 to 2014, Tulo’s production was highest in the top third, second-highest in the middle, and lowest in the bottom third.  That pattern has flipped, as now he’s most productive at the bottom of the zone and least productive at the top.

While these data are consistent with my reaction-time hypothesis, it’s also possible that Tulo has changed his approach to favour pitches down in the zone.

So let’s dig deeper.

Here is a profile of Tulo’s swing rates in the past year.

Figure 4. Swing/pitch 2015 to present.

If anything, Tulo has doubled down on his up and in approach, swinging at 75% – 78% of pitches up or up and in.  Tulo is swinging much more often at high pitches, and slightly less often at low pitches.  It doesn’t appear that he switched his approach to attack the bottom of the zone.

Let’s focus specifically on Tulo’s ability to make contact with the hard stuff. The two figures below show Tulo’s whiff-per-swing rates against all fastballs, the first from 2008 to 2014, the second from 2015 to present.

Figure 5. Whiffs/swing, 2008 to 2014.

Figure 6. Whiffs/swing 2015 to present.

Tulo has basically lost the ability to handle high fastballs. Historically a high-fastball killer, now Tulo can’t seem to catch up.  He swings and misses more than twice as often on fastballs in all three locations at the top of the zone. Let me spell it out: Tulo whiffs 2.57 times more often up and in, 2.77 times more middle-up, and 2.68 times more often up and away. And it gets much worse when you consider up out of the zone: He’s swung and missed 4.6 times more often at pitches on the outer third and just up out of the zone. Yikes.

While consistent with my hypothesis, swinging through high fastballs isn’t the only deficiency I’d expect if a hitter has lost some reaction-time skill.  Pitch recognition and plate discipline are also affected by a hitter’s reaction ability.

Discipline depends on a hitter’s ability to decide quickly whether a pitch is a strike or a ball. Tulo set a career high last year with an O-Swing% of 30.6%, three full points above his previous high in a season of 27.6%.  Tulo is chasing pitches outside the zone more than ever before.

Pitch recognition depends on a hitter’s ability to recognize pitch type in time to adjust his swing. Here is a chart of Tulo’s average spray angle as a function of pitch type.  Spray angle indicates the direction (left field to right field) that balls are hit on average.  Thus, the more positive the average spray angle the greater the tendency to pull that pitch type.  As you can see, Tulo has historically hit breaking balls and off speed pitches with the same spray angle, suggesting that he was able to recognize and wait back equally well for both pitch types.

Figure 7. Average spray angle by pitch type, 2008 to present (short seasons in ’12, 14, and ’16).

In 2015 and onward, Tulo has been pulling offspeed pitches much more than breaking balls. The result (which I won’t bother to show you graphically), has been an abundance of roll-over ground balls against offspeed pitches.

Breaking balls are easier to recognize out of a pitcher’s hand than offspeed pitches. So while Tulo is still able to use the earliest information to make an adjustment, he seems unable to make use of later trajectory and spin information that would allow him to recognize and adjust to offspeed pitches.

Maybe this is because his response speed to the later information has slowed, or maybe it’s because Tulo is committing to his swing too early to make the adjustment.  I would guess the latter.

So in summary, the reaction-time hypothesis is supported by evidence suggesting Tulo is most vulnerable when the required reaction time is shortest, he is less able to recognize pitch location in time to lay off, and he is no longer able to adjust to offspeed pitches as well as breaking balls.

A POSSIBLE SOLUTION

I’m a Jays fan and a Tulo fan so I won’t be ending this post with a “Tulo’s washed up” conclusion.  I watch this guy almost every day.  He’s still got the athleticism, the power, the hand-eye, and the swing. That said, the data have me convinced that he needs to make an adjustment.  The first thing I’d try is almost embarrassing to suggest, but I’ll suggest it anyway.  Tulo should swing a lighter bat.

Hear me out. Tulo just turned over the wrong side of the aging curve – especially for a shortstop – and meanwhile the league is throwing faster than ever.  He used to have success with an approach that requires superhuman abilities, and now that he is slightly less superhuman, that approach isn’t working.  Perhaps changing the swing weight of his bat, shaving off an ounce, could allow him to catch up to the pitches he’s not getting to and return him to some semblance of his previous form.

Take a look at the two schematics below (conceptual, not to scale). The full line from Release to Contact represents the timeline of the pitch.  The lines for “Breaking ball,” “Offspeed,” and “Location,” represent the moments when the hitter finally has enough information to process these respective features of the pitch.  Hitters recognize pitch type before location and breaking balls before changeups.  The coloured bars represent the time required to execute the cognitive and physical aspects of the swing.  The decision to swing must be completed by the beginning of the blue bar (response selection), in order for the brain to have enough time to make the necessary commands (response selection) and execute the swing (movement time).

My hypothesis suggests that the length of one or both of the coloured bars has increased for Tulo, while the length of the entire timeline has shortened for him (and everyone else).  I propose that both factors have pushed the blue bar to the wrong side of the deadlines for offspeed and location, causing Tulo to swing at more balls and fail to recognize changeups in time to adjust. The longer reaction time leaves Tulo vulnerable against hard stuff up and in, yet that’s exactly where Tulo made his money throughout the rest of his career. The “Tulo Now” schematic represents things since 2015, while the “Tulo Lighter Bat” figure depicts my proposed solution.

I’m not sure if anything can be done about a longer response selection time, but my hope is that a lighter bat could reduce Tulo’s movement time enough to get him back to the right side of those offspeed and location deadlines.  If Tulo can’t shorten his overall response time, he’s not going to be able to approach the game the same way he has for the rest of his career.  He’ll need to start looking down, looking away, and spitting on high fastballs.  Basically, he’d need to give up on what made him great.

I know trying a new bat might be a hard sell for a guy who won’t give up his 100-year-old beaver tail of a mitt, but I think changing bats might be easier than changing everything else. Including a swing that still looks fantastic.

As a former No. 1 overall draft pick, No. 1 overall prospect, three-time batting champion, and 2009 American League M.V.P., Joe Mauer seemed destined to dawn a Twins cap in his inevitable Hall of Fame induction. He claimed the title Mr. Minnesota, and the Twins payed him as such when they inked him to an 8-year, $184M contract starting in the 2011 season. However, Mauer’s sudden drop in production following his full-time conversion to first base left many Minnesotans cursing his name and clamoring for the vintage Joe Mauer. As a small market franchise attempting a rebuild, Minnesota desperately needs Mauer to live up to his contract if they plan to contend with their rising young core. While 2016 has started off miserably for the Twins – their division odds have already sunk from 7.6% to 1.5% – a resurgent Mauer provides one bright spot in an otherwise bleak outlook. While the usual sample size caveats apply here, Mauer’s improvements appear more than superficial.

Through the first couple weeks, Mauer has crushed the ball to the tune of a 173 wRC+, and has already surpassed his 2015 fWAR. He has raised his BB% to 12.8, the highest it’s been since 2012, cut his K% down to 8.5, lowest since 2008, and upped his isolated power to .154, its highest mark since his M.V.P. campaign in 2009. While Mauer most certainly cannot maintain his current .371 BABIP, underlying signals suggest that he may have broken out of his two-year slump and regained his All-Star form.

One indicator: his resurgence in batted-ball prowess. So far this season, Mauer’s Hard% is up greater than 10 points over the past couple seasons and has risen back to his previously dominant levels. Similarly, Mauer is pulling the ball more than ever, and is going to the opposite field less than ever before. Perhaps this is a sign of Mauer adjusting to an aging body – as his bat speed diminishes, he might swing earlier to try and get ahead of the ball. Another encouraging sign: his line-drive rate has risen to 33.3%, the highest he’s ever had it, while his fly-ball rate has diminished to 19.4% the lowest he’s ever been at. Considering how much his home park, Target Field, suppresses left-handed power, this seems a wise adjustment to make. On the downside, Mauer’s HR/FB rate and IFH% reside above his expected rates, providing obvious areas for his power and BABIP to regress. However, the overall batted-ball picture remains encouraging.

In addition to batted balls, Mauer is displaying an overall different approach at the plate. His O-Swing% is back to its previous low form while his Z-Swing% and overall Swing%, have sunk to their lowest levels in his career. After Baseball America rated him as having the best strike-zone discipline in the American League in 2012, his chase rates spiked tremendously in 2013 and had remained there since. Now Mauer seems to have regained that lauded discipline. Furthermore, his Zone% has actually dropped each of the past three seasons; this combination of less pitches in the zone and fewer chases out of it explains his rising walk rate. Additionally, Mauer has significantly raised both his O-Contact % and Z-Contact%. Overall, it appears Mauer has become more selective on which pitches he feels he can barrel up, hence the rising contact and line-drive rates.

Now if Mauer truly has made critical adjustments to improve his game, then we should expect to see pitchers alter their approach as well. Baseball is nothing if not a game of adjustments. According to Brooks Baseball, Mauer’s current relative mix of hard, breaking, and off-speed pitches seen remains the same as ever, suggesting that no major adjustments have been made yet. However, if his bat truly is slowing down and these are his adjustments, we should expect to see pitchers start attacking him with fastballs up and in. Currently, Mauer sees roughly 1/3 of his pitches off the plate low and away. Realizing that he won’t chase those anymore, pitchers will presumably begin attacking him in the zone more often. Whether Mauer can turn on these pitches and continue lining the ball the right will determine whether or not these results stick.

In the big picture, small-sample variance likely explains most of Mauer’s current success. However, Mauer does appear to at least be attempting to adjust his approach, hence we should not entirely disregard these results. Up to this point, Mauer has shown significantly more selectivity in which pitches he swings at, particularly in the zone, letting him barrel up the ones he feels he can hit with conviction. As pitchers adjust to his adjustments, we will see whether Mauer has truly made a triumphant return. The Twins desperately hope Mauer can maintain a modicum of these results, as he will earn $23M a year through 2018. Unlikely to go out and make a major free-agent splash, Minnesota needs Mauer to provide value commensurate to his contract if they plan to capitalize on their youth movement. Once (if) Sano, Buxton, Berrios and company develop, the Twins could have a devastating roster led by Mauer. Until then, in a season marred by underperformance and disappointment, the return of Minnesota’s favorite son could provide a potential beacon of hope.

Stat Line:  6 IP, 0 R, 3 H, 6 SO, 2 BB

In the New York Mets’ 2-1 victory over the Miami Marlins, Logan Verrett showed why he would be in the starting rotation for 29 of 30 Major League teams.  Verrett attacks opposing lineups differently than the Mets’ big three power pitchers, looking to induce poor contact early in at-bats rather than inducing a high whiff/miss and strikeout rates.

Logan Verrett continues showing more than scouts prepared us for, exhibiting an above-average breaking ball while keeping four pitches low in the strike zone.

Repertoire

Verrett’s breaking ball (slider and curveball) is a viable MLB strikeout pitch, inducing a strong 16.6% whiff/miss rate (swing and miss rate).  His breaking ball, particularly his slider, shows sharp, late, downward movement and has enough velocity to deceive the hitter into thinking the pitch is a four-seam fastball.  The reason behind defining it as a breaking ball is because it’s tough to decipher the difference between his slider and curveball.

Verrett’s four-seam fastball sits 90 to 93 mph while his two-seam fastball, also referred to as a sinker, dials in at 88 to 92 mph.  At times, Verrett’s two-seam fastball/sinker seemed to move 6 to 10 inches with sharp 10-to-5 downward movement (think of 10 to 5 on a clock).  Although he didn’t show consistent fastball command on the corners of home plate, Verrett kept his pitches between ankle and thigh high.

Staying low in the strike zone with two pitches having sharp downward movement makes it nearly impossible for opposing hitters to lift the baseball for hard hits and extra base hits.

Verrett’s Four Keys to Success

Verrett has to focus on four aspects of pitching to be successful with a fastball/sinker primarily sitting 88 to 92 mph:

1. Command fastball low in the strike zone because any misses in the strike zone will be hit hard.
2. Rely more on a two-seam fastball/sinker with downward movement rather than straighter four-seam fastballs further reducing hard contact and naturally helping keep the ball down.
3. Throw many off-speed pitches (45%-50% of total pitches) making his fastballs appear harder than reality.
4. Throw at least 70% to 75% first-pitch strikes otherwise Verrett will be forced to throw predictable fastballs to climb back even in counts.

Verrett commanded his fastball thigh-high or below on 46% of fastballs but excluding the five intentionally thrown high four-seam fastballs the percentage moves to a respectable 52%.  However, Verrett only threw 34% two-seam fastballs/sinkers, another reason his “fastball low in the strike zone” percentage wasn’t higher.  Verrett threw 52% off-speed pitches at an outstanding 70% strike rate.  Lastly, Verrett threw 77% first-pitch strikes.  Three out of four isn’t bad for his first spot start of the 2016 season.

Cause for Concern

Verrett showed a stronger out pitch than scouts reported but didn’t exhibit fastball command on each corner of home plate needed for a pitcher throwing in the low 90s.  In fact, he threw 27 of his 85 pitches (31%) on the inner half of home plate or inside to hitters but only eight of those were commanded well on the inside corner.  Understandably, Verrett lives on the outside corner but must learn to throw inside with a purpose and control.  Lacking control and a presence on the inside corner allows MLB hitters to feel comfortable in the batter’s box and gives them the ability to look for predictable outside pitches.  When an MLB hitter is able to predict or feel comfortable guessing a certain pitch type or pitch location, the more aggressive and confident their swings become.  This makes Verrett vulnerable to higher home run, hard contact and walk rates.

I wrote the article below before the news that Hector Olivera had been arrested on suspicion of domestic assault.  Obviously, if true, those allegations are horrible, and take precedent over any analysis as a player. 

As you may know, the Atlanta Braves have entered a full-scale rebuild.  Nearly every player of note from the 2014 Braves has been shipped out of town: Justin Upton, Jason Heyward, Evan Gattis, Andrelton Simmons, Melvin Upton, Craig Kimbrel, Alex Wood, etc.  Most of the transactions the team has made can be characterized as typical for a rebuilding club — exchange short-term assets for long-term assets with a focus on youth.  You can argue the emphasis on stockpiling pitching is unique, but the general idea of the Braves rebuild fits the standard template.  That is, with the exception of one transaction.

Just before the 2015 MLB Trade Deadline, the Braves sent 24-year-old left-hander Alex Wood and organizational top infield prospect Jose Peraza to the Los Angeles Dodgers for 30-year-old Cuban rookie third baseman Hector Olivera.  The teams exchanged other pieces in the deal (including a 2016 draft pick headed to Atlanta), but the backbone of the trade was Wood and Peraza for Olivera.  In making the deal, the Braves bucked the conventional rebuild philosophy (particularly theirs) in sending out young, cheap, controllable assets while acquiring a more expensive player who was already 30 years old.  It was a bold move that made Olivera and his development hugely important in making the tear-down to build-up strategy a success.  So, eight plus months later, what do the Braves have in Hector Olivera?

The short answer is no one knows.  There simply is not enough of a sample to have any confidence projecting Olivera.  When the Braves acquired him, Olivera was nursing a hamstring injury, so he began his Braves career with a rehab stint in the middle of August.  After a combined six games between the Braves’ rookie and Single-A affiliates, Olivera played another 10 games at Triple-A before making his major-league debut September 1.  He finished 2015 with 87 plate appearances and has added 21 more thus far in 2016 for a grand total of 108 major league PAs.  While 108 plate appearances is not much to go on, this is FanGraphs, so we can do better than shrugging and throwing our hands in the air until the sample grows.

Plate-discipline numbers are some of the first to stabilize after a player is called up.  During his time in MLB, Olivera has walked less than average (BB% of 5.6%) while also striking out less than average (K% of 15.7%) and making contact at a rate just above league average (Contact% of 81%).  A low walk rate combined with a low strikeout rate and near average contact rate means he must be swinging the bat.  Sure enough, that is what is shown on his player page.

Olivera swings at over 4.0% more pitches than the MLB average player.  That alone would not be concerning, except the reason that his Swing% is elevated is mainly because he is swinging at pitches outside of the strike zone, as evidenced by an O-Swing% 6.6% above the league average.  These are the hardest pitches to get the barrel of the bat on, and Olivera’s batted-ball numbers show the effects of swinging at balls outside the zone.

Despite showing the ability to hit the ball hard with a maximum exit velocity of 110 according to Baseball Savant (approximately 86th percentile thus far in 2016), Olivera has posted ISO and BABIP figures well below the MLB average.  His struggles to make consistent solid contact show up throughout his profile with a low LD%, high IFFB% (a BABIP killer), and low HR/FB ratio.  Perhaps the best summary of Olivera’s MLB batted-ball authority is found within his soft/medium/hard contact percentages.  His medium contact rate is nearly identical to the league average, but Olivera’s hard contact percentage is well below league average with the entire difference and more being accounted for in his soft contact percentage.  Essentially, Olivera’s offensive output has been sunk by a poor approach.  He has swung at too many pitches outside the strike zone, leading to weak contact and therefore poor production on balls in play. 

I haven’t yet touched on his fielding and baserunning numbers.  The Braves were not confident in his ability to stick at third base, so they moved him to left field this past offseason.  Obviously that does not suggest much confidence in his fielding ability, but it remains to be seen how he will perform as an outfielder.  The early returns are not promising as both DRS and UZR have him rated negatively (-2 and -3.7 respectively) in an admittedly microscopic sample of 43 innings.  As for his baserunning, BsR numbers of an exactly average 0.0 leave little reason to expect him to contribute or hurt much on the base paths.  It seems safe to say the bat will be what determines Olivera’s future success. 

Fortunately, the potential in that bat is obvious given the hype surrounding him and ultimately the contract he received coming out of Cuba.  He has also shown the ability to hit the ball hard on occasion at the major-league level, but particularly given the Braves decision to move him from third base to left field, Olivera will need to learn to make much more consistent hard contact to post acceptable offensive numbers.  For the Braves, there is plenty left to see to determine if this trade was a wise investment, but the early returns are not promising. 

Most FanGraphs readers know that even the fastest-stabilizing statistics take almost a quarter of a season to mean anything. With the availability of PITCHf/x data, we can look at individual pitch data, which can give us hundreds of data points for an individual pitcher just from one start. Instead of waiting until near the All-Star break to see if Aaron Sanchez has really made a leap forward or if the league has adjusted to Dallas Keuchel, we can use statistics that stabilize quickly (both “approach” stats and “results” stats) to guide these decisions.

The “results” stats that I used are:

• Zone Contact%
• Zone Whiff%
• Zone Take%
• Out-of-Zone Contact%
• Out-of-Zone Whiff%
• Out-of-Zone Take%
• First Pitch Strike%

First, I used a regression model to create a formula that used only these statistics to produce an expected ERA (or SIERA, actually, as I wanted to filter out any BABIP and HR/FB luck).

The formula ended up as: -3.11 + (12.48 * Z-Con%) + (3.08 * Z-Take%) + (11.96 * O-Con%) – (14.19 * O-Whiff%) + (13.06 * O-Take%) – (3.46 * F-Strike%)

Using 2015 data (and only pitchers who threw more than 1,500 pitches), I get an r-squared of 0.68. I’m going to call this statistic “PD-SIERA” since it uses only plate-discipline data to produce an expected SIERA.

The PD-SIERA leaders for 2015 were:

1. Clayton Kershaw, 2.47
2. Chris Sale, 2.75
3. Max Scherzer, 2.78
4. Carlos Carrasco, 2.78
5. Chris Archer, 2.92

The r-squared is good enough, and those names pass the sniff test, so I’m pretty comfortable that this produces a good approximation of pitcher performance.

I will use this to calculate a Results Change% = (year2_PD-SIERA – year1_PD_SIERA)/(year1_PD_SIERA). For example, Drew Smyly had a 3.73 PD-SIERA in 2014 (year2) and a 2.33 PD-SIERA in April of 2015 (year1). The calculation would then be: (3.73 – 2.33) / (3.73) = +37.5%

[This number can be positive or negative to indicate a positive or negative change in results]

Now, just looking at the plate discipline statistics isn’t enough. We need to see if there was a reason for a pitcher to have a better or worse PD-SIERA than he had the previous year. PITCHf/x to the rescue again, as we can look at what I will call “approach” stats: a pitcher’s pitch mix and velocity. Since these are things almost completely under the pitcher’s control, they should stabilize quickly.

In order to calculate a pitcher’s “Approach Change%,” I calculate the change in his pitch mix + the percentage of velocity change from the previous year. An example of the calculation is below:

• Drew Smyly, 2014 (full): 89.9 mph, 51.9% FB, 15.9 % CT, 28.5% CB, 3.8% CH
• Drew Smyly, 2015 (April):  90.2 mph, 46.4% FB, 30.1% CT, 23.5% CB, 0.0% CH

Velocity change = (year1_velo – year2_velo)/(year2_velo) = (90.2-89.9)/89.9 = 0.3%

[If this value ended up negative, we would use the absolute value, as we are only interested in the amount of change, not positive/negative change]

Pitch Mix change = -5.5% FB, +14.2% CT, -5.0% CB, -3.8% CH = (take the absolute value of all of these changes and then divide by two) = (28.5%) / 2 = 14.3%

[Dividing by two makes sure that each percentage change is only counted once – a +1% increase in FB% combined with a 1% decrease in CH% equals only a 1% chance in pitch mix]

Approach Change% = Velocity change + Pitch mix change = 14.3% + 0.3% = 14.6%

In order to see if this formula would work for 2016, we can look backwards to see how it would have done predicting 2015 breakouts/blow-ups.

Looking at the data from 2014 (full season) to 2015 (April only), we can multiply Approach Change% * Results Change% to see if we can identify early-season breakout/blow-up candidates. The three highest rated “breakout” candidates in April 2015 were:

1. Drew Smyly: 14.6% Approach Change%, +37.5% Results Change%… Improved SIERA from 3.69 (2014) to 3.25 (2015)
2. Chris Archer: 13.7% Approach Change%, +36.1% Results Change%… Improved SIERA from 3.80 (2014) to 3.08 (2015)
3. Dillon Gee: 13.4% Approach Change%, +36.6% Results Change%… SIERA increased slightly from 4.30 to 4.41 (groin injury in May, lost his rotation spot, and ended up in the minors for most of the second half)

Not bad – two of the clear top three breakout candidates actually improved their SIERA by over 10% from 2014. How about the bottom of the list? We have a clear top four:

1. Homer Bailey: 14.2% Approach Change%, -34.7% Results Change%… SIERA jumped from 3.60 to 5.65 (injured after two starts)
2. Jake Peavy: 21.9% Approach Change%, -14.9 Results Change%… SIERA increased slightly from 4.11 to 4.33
3. Tyler Matzek: 23.9% Approach Change%, -13.6% Results Change%… SIERA jumped from 4.08 to 6.45 (injured after five starts)
4. Wade Miley: 10.2% Approach Change%, -31.5% Results Change%… SIERA jumped from 3.67 to 4.24

Bailey and Matzek were both headed for season-ending injury (maybe this formula is a good predictor of an aching arm?), Miley went from above-average to below-average, and Peavy got a bit worse.

To show why we need both the Approach and Results Change%, consider these two pitchers:

• James Shields: 5.5% Approach Change%, +26.5% Results Change%… SIERA increased slightly from 3.59 to 3.72
• Edinson Volquez: 5.2% Approach Change%, +23.5% Results Change%… SIERA increased slightly from 4.20 to 4.35

Both pitchers had significantly better results in April of 2015 than they did in 2014, but their approach barely changed at all. As the change in results was not backed by any change in approach, they both ended up being essentially the same pitcher for the remainder of 2015 as they had been in 2014.

I’ve run the numbers for the first week of 2016, but will wait until we get about a month’s worth of data before releasing the actual numbers. For those that would like a sneak peak (caution: most of these are using ONE game’s worth of data!):

Breakout candidates: Alfredo Simon, Wade Miley, Jose Fernandez, Jacob deGrom, Noah Syndergaard, Aaron Sanchez

Blow-up candidates: Dallas Keuchel, Stephen Strasburg, Jerad Eickhoff, Chris Sale, Taijuan Walker, Masahiro Tanaka, James Shields

Positional adjustments are a tricky subject to model. It’s obvious that an average shortstop should get more credit for defense than an average first baseman, but there are a wide variety of methods to calculate this credit. Some methods use purely offense to calculate the adjustments, while others have used players changing positions as proxy for how difficult each area is.

We’ll use a simplified version of the defense-based adjustments (which I’ll propose a change for later) for Part 1. This model looks at all players who have played two positions (weighted by the harmonic mean of innings played between the two). Then, it produces a number for how much better an average player performed at a certain position than another. After doing this for all 21 pairs of positions, we combine the comparisons into one scale, weighted by which changes happen the most often.

Example: the table below shows how all outfielders in 1961 performed when changing positions within the outfield (using Total Zone per 1300 innings):

• LF/CF: 14.5 runs/1300 better at LF, 4028 innings
• LF/RF: 10.4 runs/1300 better at LF, 9487 innings
• CF/RF: 7.4 runs/1300 better at RF, 6025 innings

After weighting each transition by the number of innings, we get an estimate that the LF adjustment should be -8.3, RF should be 1.0, and CF should be 7.3. (We’re assuming that players being better at a position means that that position is easier.)

I performed this calculation for all seven field positions (1B, 2B, SS, 3B, LF, CF, RF) for all years between 1961 and 2001. While using only seasons from the same year does away with any aging issues, the big problem with this analysis is that it doesn’t adjust for experience, as very few managers, ever, send full-time first basemen to play the outfield. This experience issue will be addressed in Part 2, but for now we just have to keep it in mind.

Finally, while I could have expanded this to 2015, the difference between UZR/DRS and TZ is so massive that using both would have created a lot of error in the graphs below.

The graphs (using loess regression to smooth the yearly data):

With yearly data:

With error bars:

Less smooth version:

Less smooth version with points:

A lot of positions have 4-run error bars, so it would be wise to take some jumps and drops with a grain of salt. However, it is interesting to note that corner outfielders (especially left fielders) appear to get much better at defense since the 1960s, while the right side of the infield has seemed to drop in quality. Also, for whatever reason, center field had a huge dip during the 1970’s.

During Part 2, I’ll analyze these graphs in depth, and propose adjustments to this simple model.

A preview of Brandon Belt, Giants first baseman

Ever since Brandon Belt tore apart the Eastern League in 2010, hitting .337/.413/.623 over 201 plate appearances in a very pitcher-friendly league, Giants fans have been hyped up on his potential major-league career. When his name first began to circulate, fans and journalists liked to mention Belt’s raw power. 

That’s a dangerous word for Giants fans: power. You say that word, and all of a sudden we enter fever dream hallucinations of riding Barry Bonds home runs like Concords, waving at our houses as we pass over them, never to land. We’ve been pining for a 40+ home-run hitter since Bonds set the league on fire in 2004. No, that’s not hyperbolic enough. Barry Bonds incinerated baseball history in 2004. Relatively impossible standards for any mortal player, wouldn’t you agree?

So why Belt? How did Belt become the Giants’ next offensive savior, when he doesn’t even play Bonds’ position?

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BELT AS BONDS

The Giants never had a history of developing hitters well. Will Clark was the one true homegrown star that bridged the Mays and McCovey era to the present one. The post-Bonds years were a concoction of otherworldly young pitching, and Brian Bocock: starting opening-day shortstop. Bengie Molina led the 2008 Giants in home runs….with 16.

We were given a Panda in 2009, swinging at everything for a .330/.387/.556 slash. 23-year-old Pablo Sandoval firmly grasped the hearts of Giants fans, but he wasn’t really heralded for his power. To this day, no Giant has hit 30 or more home runs in a single season since Bonds in 2004.

Then came 2011. In Brandon Belt’s second major-league game, he hit a three-run homer to dead center field at Dodger Stadium against Chad Billingsley. Certainly no easy task, but the way Belt just whipped his bat through the strike zone made it look almost routine. “That’s the guy,” thought the Giants fan. “That’s the team’s new 30-home-run machine.” It was that instantaneous.

But it wasn’t that easy. Belt, like most rookies, struggled to keep pace with major-league-caliber pitching: a 23-year-old kid could be forgiven for facing Clayton Kershaw like he was swinging a fishing rod. Belt bounced from Triple-A to San Francisco, from the bench to the disabled list. Every once in a while he flashed his incredible home-run potential, re-igniting the “Savior Belt” narrative. He just needed more time.

In late 2012 Brandon Belt finally, if unspectacularly, wrested the starting first-base job from Brett Pill, another hitter with serious power. Belt locked himself in during a lost 2013 season, perhaps at last realizing his potential. He came out with dingers blazing in 2014, and was then hit in the wrist with a Paul Maholm fastball. Upon returning, he received a concussion from his own teammate. It was a lost season for Belt, even though he did get to be a postseason hero for one night.

In 2015, he finally put it together. Slashing .280/.356/.478, Belt had his best overall season. He had arrived.

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So why do people still call into KNBR 680, and bother the poor hosts with poorly-conceived trade proposals that usually involve purging Belt? Is it because he hasn’t unleashed the stupendous slugging ability that we fantasized for him, an unrealistic threshold that is becoming harder for any San Francisco hitter to reach?

In this era of pitching-dominated baseball, in one of the most dramatically home-run-reducing ballpark in the United States, very few left-handed Giants are capable of hitting 30 home runs. Giants hitters, Belt very much included, succeed by hitting .300, maintaining a terrific eye at the plate, hitting to all fields, and playing solid (and sometimes sterling) defense. Park factors have always pegged AT&T Park, with its Grand Canyon outfield gaps, as a doubles and triples park. Therefore, it benefits the team to fill their lineup with contact-first hitters with…you guessed it…doubles and triples power. This is how the Giants have won. This is how the Giants will continue to win.

That said, how do we value Belt? He’ll be 28 for most of 2016, so he’s likely in his prime, or close to it. Via Baseball Prospectus, Belt was worth 4.7 Wins Above Replacement Player in 2015, and 4.4 WARP in 2013, losing 2014 largely to injury. Belt is a plus base-runner, and a very adept fielder (DRS: 8, UZR: 9 in 2015). But how do we know if these numbers are good?

Perhaps we need some context. There are two first basemen in particular whom Belt resembles, both representing existing and theoretical stages of Belt’s development. The first is Joey Votto of the Cincinnati Reds, and the second is Freddie Freeman of the Atlanta Braves. Let’s show a quick comparison of the three players, in 2015.

All three players had great seasons last year, and all three players are similar in different ways. Belt, like Freeman, is young enough to improve. Belt, like Votto, had his best season in 2015, yet remains criminally underrated. Votto and Freeman both survived team rebuilds, and both represent their team’s best player. Both have had to be superstars, whereas Belt has become a role player. All three are left-handed.

But there’s more to both players than their statistics on the surface; all three players have unquestioned power, and power hitters are expected to command the strike zone. One quick glance at Barry Bonds’ Baseball-Reference page reveals his unbelievable plate discipline, usually getting one good pitch to hit per game. Sluggers command the zone, just as they command respect.

This table shows the percent of pitches outside the strike zone at which each player swung (o-swing%), the percentage of pitches inside the strike zone at which each player swung (z-swing%), the percentage of total swings that resulted in contact (contact%), and the percentage of strike swings that resulted in contact (z-contact%). The final column shows the percentage of balls put into play that were hit hard. We are using data collected through PITCHf/x, displayed on FanGraphs.

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BELT AS VOTTO

Joey Votto, being the best and longest-tenured hitter on this list, doesn’t swing much. He swings at only 19% of balls, 11% better than league average. Perhaps more importantly, Votto is very selective about swinging at certain strikes. Many pitches in the strike zone cut the corners, with nasty movement running down, away, or into a hitter. If a hitter were to attempt a swing at one of these pitches, he would make weak contact, and likely make an out. It’s a blatantly obvious, but crucial reminder: hitters get three strikes, and they don’t have to swing at all of them.

Votto has a spectacular eye; he will only swing at the best strikes he gets. His eye and stubbornly consistent plate discipline have earned him an MVP award, and have helped established himself as one of the smartest hitters in the game.

Votto, much like Belt, has drawn criticism for his approach. He has endured the ire of many impatient Reds fans due to his deliberate approach to hitting. Fans know Votto has special power, and they don’t want to watch him walk 20% of the time. The old-guard sentiment still lives strong, and contends that Votto is wasting his offensive capabilities by just getting on base, leaving the damage to the hitters behind him in the lineup. Votto should be the one doing the damage. But the value of getting on base is undeniable these days, and Votto is too smart to swing when he doesn’t want to.

So Votto sets the ceiling pretty high for Belt. Both hitters use the entire field very well, but they each play in vastly different hitting environments. Belt makes the hard contact necessary to intimidate opposing pitchers, but he may never hit enough home runs at AT&T Park to command the respect that Votto does. Belt also swings and misses a lot (league-average contact rate in 2015 was 80%), and needs to lower his strikeout rate, lest opposing pitchers taunt him with junk.

Belt has improved his offensive prowess every year since 2012, and if he improves further in 2016, he could draw more comparisons to Votto than he does to the next guy.

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BELT AS FREEMAN

The closest current comparison to Belt is Atlanta Braves first baseman Freddie Freeman. Both players are relatively young, and love to swing. Neither makes as much contact as Votto does, but both hit a higher percentage of balls harder. Both are very solid defenders, and capable baserunners.

Whereas Votto personifies Belt’s future potential, Freeman represents Belt’s present and past. While the similarities are there, one glaring difference exists in Belt’s favor.

Freeman had easily his best season in 2013, and has posted progressively weaker seasons in the two years since. Belt, on the other hand, has gradually improved. Belt, like Freeman, had a terrific 2013 season, boosted by a ridiculous second-half surge. In 2014, Belt was well on his way to career highs in home runs, OPS and RBIs, until he was repeatedly and mercilessly struck by baseballs, from Dodgers and Giants alike. Broken wrists and concussions kept Belt from playing a full season.

Then 2015 came, and Belt started to resemble the hitter Freeman had been in 2013. After several years of doubt, it was becoming clear that Belt was trending up. He was still improving. There was no reason to suspect any deviation from the trend, and Belt would continue the dedicated upward march toward the summit of his own potential.

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DOCTOR BELTED AND MISTER SLIDE

Except we’re getting ahead of ourselves again. Part of the reason fans are constantly disappointed by Belt is the incessant, hyperbolic expectation that surrounds him, and the unfair duality with which he becomes associated. He’ll go 3-4 with three singles, and we’re wondering where his power went. Then he’ll go 1-5 with a long home run and four strikeouts, and we’ll throw our hands in the air and complain that he’s too reliant on his power. Why can’t he be more consistent? We can’t allow a middle ground for Belt, because he doesn’t present one: Belt truly is an all-or-nothing hitter.

This doesn’t appear to be the case when Belt’s season statistics are viewed as a whole; he puts up solidly above-average offensive numbers. When Belt plays a full season, he’ll hit 18-24 home runs per year, and posts a batting average between .270 and .290. Sound familiar? We know better, because we’ve watched him play. We know that Belt is one of the streakiest hitters in the major leagues: Does THAT sound familiar?

In 2015, he didn’t hit his first home run until May 15, six weeks into the season. In the two weeks following, he proceeded to hit seven. Belt managed only three through June and July combined, then hit seven again in the month of August, two of those in the same game. He finished with only one in September.

It wouldn’t be so difficult to evaluate him if he spread his 18 home runs equally, one every nine games. If he hit .284 in every month, we would know exactly what Belt’s true value was. But every year, we go through the same cycle:

“What’s wrong with Belt? Are his injuries still bothering him? You know concussions are persistent little things right? Wait, he’s back baby! Damn, Belt for the All-Star Game? Nope, there’s ol’ slumpy again. Why does he always look so sad? Should we trade him to Miami for…wait who’s the Marlins first baseman again? What the hell is a Justin Bour? Yeah okay, sure. Why not. Wait there he is again! Two home runs to right-center at AT&T against a tough lefty, impressive! Can’t believe I ever doubted you Belty. Aaaand he’s gone again. Wonder what Brett Pill is up to these days…”

Every. Damn. Season.

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BELT AS BELT

It’s increasingly clear to us at this point what type of player Brandon Belt is becoming. He’s a streaky, high-power guy who hits to all fields, strikes out a good amount, plays a mean first base, and will occasionally slump his shoulders. And that’s fine. Because he’s good enough to start, and he fits in perfectly with the rest of the Giants lineup.

Belt doesn’t need to hit like Joey Votto; the Giants already have Buster Posey. Belt doesn’t need to hit like Freddie Freeman; the Giants already have Hunter Pence. With Brandon Crawford’s continued ascent, as well as the dramatic emergence of Joe Panik and Matt Duffy, all Belt really has to do is remain healthy and hit as well as he can.

Even if Belt never blossoms into the next great Giants slugger, even if Belt repeats his 2015 season ad infinitum, during which he was a well above-average baseballer, he’s making the team better by simply showing up.

Perhaps it’s time we leave Brandon Belt alone. He’s doing just fine.

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