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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The regression that I am going to run analyzes whether sabermetric statistics, more specifically WAR, have a greater impact on MVP voting than traditional statistics. This is important to the sport because MVP voting helps players garner a good reputation. It also affects how the front office of each major-league baseball team goes about acquiring specific players. In fact, the salaries of players can be affected by MVP voting, especially if that player is in the last year of his contract and is preparing to become a free agent. In turn, acquiring high-level or MVP-type players can potentially improve overall team performance, which would result in an increase in attendance, and therefore, the team would have an increase in revenue.

The data set that I have chosen to look at is the 2014 results for MVP voting for both the American and National Leagues. Also, I will look at the individual statistics for each of the players that received votes. From this relationship, the independent variables would be the player statistics (batting average, home runs, RBI, WAR) and the dependent variable would the number of votes that each player receives. This is because certain statistics are bound to affect whether one player receives more votes than another. Essentially, what I am trying to prove is that one set of statistics is a better indicator of player ability and player contribution than the other set. Bill James was one of the first to expound upon sabermetrics when he wrote a series of books known as Baseball Abstract in the 1980s. Many other baseball historians, such as Pete Palmer and John Thorn, have written books detailing and introducing the concept of sabermetric statistics. While many books have been written and studies have been done about sabermetrics, no one has really done a study about the accuracy and influence that sabermetrics can have on statisticians, writers, fans, and teams.

For this regression, I analyzed only position players (non-pitchers) to prevent confusion due to the use of different statistics which are required to analyze pitchers separately. After the running of the regression, it appears that the WAR has a greater impact on MVP voting than home runs, RBI, batting average, and stolen bases. However, the two statistics that seem to have the greatest impact on MVP voting are On-Base Percentage (OBP) and Slugging Percentage (SLG). WAR has a positive slope of 35.9 while SLG has a positive slope of 2,535.7. The coefficient of correlation (R) is 0.87 and this seems to indicate that the nature of the relationship in this regression is positive. Also, the fact that the coefficient of correlation is closer to 1 indicates that there is a significant relationship between respective statistics and their influence on MVP voting. The coefficient of determination (R^2) is 0.76. This shows that just about 76% of the MVP voting results can be attributed to the certain statistics of a specific player. For instance, in the American League, Mike Trout led the league in WAR and RBI, and was third in SLG. Since those two statistics were the most impactful, they definitely contributed to Mike Trout being named the MVP. Therefore, this relationship is positive, and some statistics have a significantly higher impact on MVP voting than others. Once again, based on the regression, SLG seems to be the most impactful statistic, and stolen bases were the least impactful.

After analyzing the results of the regression, I ran a hypothesis test to determine the population coefficient of correlation. The level of significance for this hypothesis test was 0.05. The null hypothesis was that p=0; in other words, there is no significant relationship between any statistic and MVP voting. The alternative hypothesis is that p>0, p<0 and that there is a significant relationship between certain statistics and MVP voting. The degrees of freedom for this hypothesis test was 21. The t-critical value turned out to be about 2.1. I tested each individual test statistic and discovered that there is a significant relationship between MVP voting and RBI, SLG, and WAR since the t-calc for those variables was greater than 2.1.

To further test this theory, I also did an ANOVA. I wanted to test the variation of MVP voting when compared to certain statistics at the 0.05 level of significance. The degrees of freedom1 was 7 and the degree of freedom 2 was 21. Therefore the f-critical value turned out to be 2.5. F-Calc from the ANOVA was 9.6. Since F-calc is greater than the critical value, we prove that, once again, there is a significant relationship between certain statistics and MVP voting.

Next, I did a test for the least squares regression. For the least squares regression you have to do a test for three separate things. They are normality, homoscedasticity, and independence. To test for normality, I looked at the normal probability plot. The points on this plot seemed to be curved slightly, therefore, the residuals are not normally distributed. To test for homoscedasticity, we look at the residual plots for each of the x variables. Since most of these variables neither increase nor decrease as x increases or decreases, these variables are homoscedastic. To test for independence, you would have to run another regression. This time, it would be a simple regression using the same x variables; however, each residual is the x variable for the next one. To test for independence, you would also have to do a hypothesis test. The null hypothesis would be that bi=0 and the alternative hypothesis would be that bi>0, bi<0. If bi is equal to 0 than the residuals are independent. The level of significance is 0.05 and the degrees of freedom would be 30. The t-critical value came out to be about 1.7. T-calc turned out to be greater, which means that the residual values are not independent.

In conclusion, the initial multiple regression that I ran showed a significant relationship between certain statistics and MVP voting. Despite the fact that the residuals were not independent, the other tests that I ran showed over and over again that the same statistics that the regression stated were impactful on MVP voting were still impactful after I ran other tests. Thus, it seems that the sabermetric statistic WAR did have more of an impact on MVP voting than most of the traditional statistics such as batting average and home runs. While sabermetric statistics are a new trend in baseball analytics, they will not replace the traditional statistics such as batting average, home runs, and runs batted in, simply because those statistics have been used since the early days of baseball. Fans and statisticians alike will continue to use both traditional and sabermetric statistics to analyze player performance.

There are many other statistics that I could’ve analyzed for this regression. In fact, pitching statistics are completely different from the statistics that I used in this regression for position players. However, the statistics that I did use proved to be effective in proving that, in fact, some statistics do have a considerably greater impact on MVP voting than some statistics that some people simply assume are not relevant or needed in order to analyze player performance and contributions. Also, for this regression, I only analyzed the offensive statistics for the position players. Defensive statistics such as defensive runs saved (DRS) and defensive WAR are also important statistics that many baseball statisticians look into when evaluating player performance. Overall, the possibilities for this regression are endless, and even though there may never be a definitive statistic that everyone agrees upon for analyzing player performance, all of the statistics that I used in this regression, as well as many others, will continue to remain relevant in the game of baseball for many years to come.

2014 American League MVP Voting Results

2014 National League MVP voting results

American League MVP Candidate statistics: (league ranks for respective statistics in parenthesis)

National League MVP candidate statistics: (league ranks for respective statistics in parenthesis)

http://www.seanlahman.com/baseball-archive/sabermetrics/sabermetric-manifesto/

www.baseball-reference.com       http://sabr.org/sabermetrics/statistics

http://bbwaa.com/14-al-mvp/                                            

http://bbwaa.com/14-nl-mvp/

Mookie Betts was incredible in 2016. As the third-best player in the Majors, he posted a 7.9 fWAR. But this year has been different. His .261/.341/.434 triple slash line is a far cry from the one he posted last season of .318/.363/.534. His 101 wRC+ tells us he’s producing runs at a rate that is barely above league average, while also revealing a lot of his value has come from his defense.

And yet, he’s still on pace for about 4.5 fWAR, which still makes him one of the game’s top assets. He continues to be awesome, but a different kind, and different enough to ask “what’s changed?”

There are some significant differences from last year to this year in Betts’ contact profile. In general, he’s swinging less. Like, a lot less. Last year he took the 20th-most pitches in the league. This year, he’s taking the fourth-most. He’s also swinging at fewer pitches in the zone, while making more contact when he goes outside it. That’s an odd combination for a player so disciplined at the plate. It suggests pitchers have adjusted to Betts and that he might have picked up on it, but that he hasn’t quite countered yet.

And though it helps us see what’s fueling a lower triple slash this year and, by matter of course, lower WAR, it doesn’t tell us how pitchers have adjusted to Betts. He’s seeing just about the same pitch mix this season as last, save for one thing. He’s getting about 22% sliders this year, or an additional 5% more than in 2016.

His wOBA against sliders is just .276 this season. That’s lower than what even his expected wOBA against sliders was last year, which he topped by 57 points. And like dominoes, this one push is impacting other pitches he’s seeing.

Changeups are also giving Betts considerable problems, and it could be because he’s been oddly less patient with them than other offerings in 2017. Despite seeing almost the same exact amount this year as last, and swinging at them at a nearly identical rate, his weighted pitch value against the offering is more dramatic than any other. He’s managing an unimpressive -0.43 mark this season. In 2016? It was at 3.67. He’s gone from waiting for changeups to show up in his wheelhouse to swinging at them freely. It’s extremely uncharacteristic for Betts, and it’s yielded just a .260 wOBA against the pitch.

Consider how the changeup is designed to induce weak contact, how it can often fade and drop away toward the lower outside corner of the zone, and how sliders drive to the same portion of the plate. Pitchers seem to have found a way to sequence their stuff against Betts to thoroughly influence the damage he can create with the bat.

This is particularly true with right-handers, against whom Betts is batting only .253 in 2017. Last year, he hit .331 against them. And because the league features about two and a half as many right-handers as southpaws, the trouble for Betts becomes emphasized that much more.

Mookie Betts is still exceptional. He’s still demonstrating elite control of the zone, as evidenced by a walk rate that equals his K rate. But there appear to be plate adjustments that will be necessary for him to make if he’s to return to being one of the game’s absolute best.

This is probably not going to be a long article but I was curious which players fit the Hoskins profile best in recent history. Carson already established the Hoskins profile as a guy who hits the ball in the air and makes contact.

For that, I searched first basemen that played from 2002 to 2017. I used 2002 because that is the year we started to have batted-ball data. It also means that it mostly covers a high-K era, although it got more extreme recently. As a cut-off, I used 1500 PAs played. 96 players fulfill those criteria.

First, I filtered for an ISO of .200 or greater. I also filtered for a BB% of greater than 9% (because Hoskins also walks), a K% of 20% or smaller, and finally a ground-ball rate of 40% or under.

That leaves a list of just eight names:

The list is a pretty good group. It averages 23 career WAR, a 127 wRC+ and a .273/.367/.503 line. The only downside there might be is that the fly-ball profile could supress BABIP some. The group has a .287 BABIP which is below the league average of .300 during that time span, especially if you consider how hard those guys hit the ball. That means that those guys do underperform their K/BB/ISO profile a little bit. For example, Konerko has a very good power/contact/discipline profile that by my math points to more of a 140+ wRC+, but his actual wRC+ is 120. That is the disadvantage of that extreme profile — you are losing some BABIP to fly outs, especially if you hit more balls in the high fly ball range, which tend to be either HRs or outs, and even more so if there is a slightly elevated pop-up rate coming in conjunction with the fly balls.

But overall that doesn’t matter that much if the K/BB/ISO profile is that good; those guys are all really good hitters even with a slightly lower BABIP. Just expect Hoskins’ hit tool to play under his contact rate a little bit due to that Bautista-like profile (who also had that lower-BABIP, pulled-fly-ball profile with great contact and walk rate).

That means Hoskins might be a .265 hitter despite above-average contact, which also makes his SLG play a little bit down on his power, but he should still get on base on a very good clip and produce excellent power. Just be a little careful when looking at his power, contact, and discipline if you want to bank him for a .300 average/.600 SLG for your fantasy team. He might pay some cost with his elevating that doesn’t come in the form of Ks, but BABIP. But nonetheless he should be very good, even if it is “just” a Konerko/Teixeira type of player and not the next Miggy like some Philly fans probably think right now.

Noted stoic Epictetus famously said, “Freedom is the only worthy goal in life. It is won by disregarding things that lie beyond our control.” If we accept this to be true, then St. Louis Cardinals prospect Sandy Alcantara might need to disregard small balls of cork wrapped in yarn and cowhide.

Alcantara was called up from AA to join the big-league club on Friday, bypassing AAA completely.

For the purposes of this article, we’re going to assume control is referring not to a pitcher’s ability to not walk batters, but by his ability to throw the ball somewhere that, by the end of the exchange, it ends up in his catcher’s mitt, be it as a ball or a strike.

By this definition, in 125.1 innings pitched for Springfield this year, Alcantara has controlled next to nothing. He has thrown 20 wild pitches and hit 15 batsmen, all with a repertoire that includes a fastball which, according to Eric Longenhagen, “sits 95-97 and will touch 101 with plus movement.”

This comes out to Alcantara being expected to either hit someone or throw the ball to the backstop once every 3.58 innings. For this study, let’s call this his “Craziness Per Inning Pitched” or CPIP. I know it would be better phrased as innings pitched per craziness, but IPPC isn’t an acronym that rolls off the tongue.

Here is a list of (as far as I can tell with my inexperienced play indexing) the lowest single-season CPIPs of all time (minimum 50 IP).

1. 2011 Daniel Cabrera: 3.4
2. 1995 Toby Barland: 4.35
3. 2000 Hector Carrasco: 4.37
4. 2000 Matt Clement: 5.26
5. 2010 A.J. Burnett: 5.32

As you can see, Alcantara, with his 3.58 CPIP would slide right in at second lowest all-time. However, the top three on my list were all used primarily as relievers, where you can get away with a little more wildness. Only four of Alcantara’s 125.1 innings have come out of the bullpen this season. Among starters, his CPIP would rank as the lowest all-time.

Now, obviously, these are all major-league seasons, and Alcantara’s was in AA, but still, a player being expected to throw a ball that ends up somewhere other than in his catcher’s mitt once every 3 1/2 innings is some special craziness at any level. You could probably even make the argument that, due to increased competition and pressure, a prospect who is suddenly vaulted two levels higher should expect to see an increase in wildness.

With the Cardinals promoting fellow pitching prospect Jack Flaherty as well, it does seem likely that Alcantara will be pitching in relief for the Cardinals, but Cabrera’s record is still within reach if he can just allow himself to control a little less.

Is your name Christian Yelich? If not, please stop hitting ground balls. Right now. Please. Thank you.

Christian Yelich is the only MLB player to log 2400 PAs over the course of 2014-2017, hit 55% or more ground balls and log a wOBA of .340 or higher in a single-season. And he’s done it in all four seasons.

How does he do it? He combines a league-average line-drive rate (22%) with a .270 batting average on ground balls and a 10%+ walk rate.

Sure, Jean Segura (3yr+ GB 55.9%) did it last year, but he dropped his GB rate to 53% and had a HR/FB excursion up in the 13%+ range that year.

You might point out that during the same year, Jonathan Villar managed a .356 wOBA, but he needed an even-better-than-Yelich .316 average on ground balls with a 20% HR/FB ratio and an 11%+ walk rate. We’re talking about the definition of outlier seasons.

After a quick back-and-forth with another FanGraphs reader/commenter, John Autin, in the recently published Justin Turner piece by Travis Sawchik I started wondering what sort of wOBA does each type of player carry based on the percentage of ground balls that player hits on average. But for starters, I had to understand how many players carried ground-ball rates in what ranges.

More than half of the qualified player seasons in the last four years have come from players who averaged 40-50% GB. Of those, 65 (16%) resulted in players contributing less than a .290 wOBA. FanGraphs’ own wOBA rule of thumb page considers these seasons “awful.” This includes seasons you might remember such as “Albert Pujols’ season in progress (2017),” “Every Billy Hamilton season ever,” and “most seasons from Alcides Escobar.”

To provide a little more context, let’s view these player seasons on a 100% graph. Players who have averaged greater than 40% ground-ball rates have a 4-in-10 or better chance of producing a below-average season by wOBA standards (.310-.319 bin and lower).

The “Great” (.370+) seasons lodged in the 50% bin are from Eric Hosmer (2017), DJ LeMahieu (2016) and Ryan Braun (2016). Braun needed an outlier HR/FB (~29%) season, LeMahieu is one of the ten deadliest line-drive hitters in all of baseball, and Eric Hosmer, well, he’s straddling the line 5/6th of the way through the season. There just aren’t that many great hitters carrying a GB rate between 50-55%. You’re going to either need to hit a TON of line drives to make up for all those ground balls, or pound three out of ten FBs for a HR. Otherwise you’re looking at a very average offensive season a quarter of the time, and well below average another 50% of the time.

What I’ve learned is that 30-40% GBs is the sweet spot, and only a quarter of MLB player seasons from 2014 have been recorded by players in this bin. Freddie Freeman, the king of line drives, has lived in the 30-35% GB range over this time period. He’s joined by players like Lucas Duda (putting up three above-average seasons), Kris Bryant, Matt Carpenter and Brandon Belt.

Interestingly enough, Ian Kinsler might want to rethink his approach. Along with a high infield fly rate, he’s just not doing enough damage with the HR to put up high wOBAs. The exception being his 2016 and 2011 seasons. Being that he’s an above-average line-drive hitter, he could benefit from shifting his focus a little more that way as he ages through his last few seasons. Or I suppose he could benefit from a more hitter-friendly home park as he enters free agency this year.

Now that we have the table set, I’d like to share a short list of players that are putting up terrific wOBAs, but could benefit from putting even more balls in the air. Of course there’s Christian Yelich, but let’s let him do what he’s doing. And while we’re at it, we won’t recommend any changes for Joey Votto.

• Adam Jones (.335 wOBA, 45% GB)
• George Springer (.370 wOBA, 47% GB)
• Yasiel Puig (.365 wOBA, 49% GB)
• Yasmany Grandal (.350 wOBA 44% GB)
• Xander Bogaerts (.340 wOBA 47% GB)
• Jose Abreu (.370 wOBA 46% GB)
• Domingo Santana (.360 wOBA 47% GB)

One thing I’ve noticed, and this isn’t a new revelation to me, is that Cuban players like Puig, Grandal, and Abreu all hit a very high number of ground balls, even while enjoying quite a bit of success. But if they ever decide to make the anti-ground-ball leap, they may find an MVP trophy or two. Ditto for George Springer. Let’s get him ripping air balls and see how high he can fly.

And maybe there are a couple of careers to save as well, a la Yonder Alonso or Justin Turner? Here are the low-flying 2017 players who could use the #turneradjustment

• Kole Calhoun (.311 wOBA, 42% GB 3yr+ Avg, 44% 2017)
• Danny Valencia (.313 wOBA, 47% GB 3yr+ Avg, 47% 2017)
• Kendrys Morales (.316 wOBA, 47% GB 3yr+ Avg, 51% 2017)

Looking team by team, at the approaches employed by their players who gathered at least 400 PAs minimum in any given year, and also have accumulated 1000 PAs over the last four years, we can pick out some trends as well. I was a little surprised to see the Mets at the top of the list, but the A’s, Tigers, Reds and Blue Jays didn’t surprise me as “put it in the air” types of teams. You’ve got some of the poster children for the air-ball revolution on those teams such as: Donaldson, J.D. Martinez, Jose Bautista, and Yonder Alonso. Those teams also feature some of the game’s deadliest line-drive hitters in: Nicholas Castellanos, Joey Votto, Miguel Cabrera, and Daniel Murphy (from his Mets years).

On the flip side, we see the Marlins, led by aforementioned ground-ball expert Christian Yelich, pound-it-into-the-ground Dee Gordon, and Ichiro Suzuki, as well as a team-wide approach by Ozuna, Realmuto, Hechavarria, and Martin Prado to hit ground balls and line drives. Prado is the only one other than Yelich to do it well.

The White Sox were led by Adam Eaton (54% GB), Avisail Garcia (52%), Alexei Ramirez (49%), Yolmer Sanchez (48%), Melky Cabrera (47%), and Jose Abreu (46%). Tim Anderson is the latest, though he doesn’t factor into the analysis yet, to pound out 52% ground balls like it’s his job and turn in awful wOBA seasons (.315 and .274 in progress).

Carson had an interesting article about finding contact hitters who can elevate. That makes a lot of sense, especially if the ball is really juiced, because that new environment means that more FBs are going out even though they are not totally crushed. A couple months ago I already correlated power and contact together with walks, and had pretty decent correlations with performance. Power and contact together is definitely a good thing. However, when it comes to low-minors players, often the power is not present yet, so it can make sense to look at the batted-ball profile instead when evaluating potential for growth.

Now, that is not a hard rule, and you could actually say that a strong ground-ball hitter like Daniel Murphy when he was young has actually more potential for growth than a weak FB hitter when he actually learns to elevate, and he and others have shown that it is possible to make that change even in the late 20s, but we also know that sustainable swing changes are quite hard to attain (there are the Murphys and Donaldsons but also guys like Jason Heyward who tinker with the swing every year and make it worse because muscle memory gets confused), and it is probably a safer bet that a young minor leaguer (17-19-year-olds especially) can add some muscle and make some of the FBs go over the wall.

Instead of FBs, however, I have tried a new stat. Instead of FB% I have used a stat I called “effective off the ground percentage.” I used off the ground percentage because line drives are just as good as FBs (actually better) and everything off the ground is good unless it is a pop-up. Basically it is 100 minus GB% minus PU% (IFFB*FB/100). I think that is important because pop-ups are a terrible result and we do know that extreme FB hitters like Schimpf, Story, or Odor tend to have elevated pop-up rates. Overall, there is a small but not super significant positive correlation between FB% and IFFB% (0.3 Pearsson), but at the extreme top end of launch angle, the pop-ups do get higher.

That means, obviously, a hitter who can get the ball off the ground while avoiding pop-ups (like Trout or Votto) is a big asset. Still, the overall correlation of wRC+ and effective off the ground percentage is not huge, although it is better than just FB% (0.23, vs 0.17 Pearsson).

The effect gets stronger at the extreme ends; for example, the top-20 in effective off the ground percentage is at a 117 wRC+ and the bottom 20 just at 99. However, of course power still plays a big role, as do strikeouts. Launch angle does help, but there are limits to that; it is not a magic pill. The most important things are still the big three — power, contact, and plate discipline. But a bad batted-ball profile can make the other peripherals play down. There is an effect of diminishing returns. Getting balls in the air is good, but it is mostly an issue when it gets extreme. If you have 6-degree LA/50% grounders, that is bad, but once you get past average (10 degrees, 45% grounders) there is not that much of a gain by further increasing LA.

I don’t believe in that “steeper swings lead to more Ks” thing, but higher LA can have a cost of BABIP and sometimes pop-ups. So I’m not sure a Hoskins / Jay Bruce / Cody Bellinger FB profile is that much better than a normal 40% FB profile. In the end, there is a threshold when LA can’t be further increased.

The FB revolution is mostly helping the guys who had extreme grounder profiles; in the end, it is probably best to have a slightly above-average LA of like 12 degrees, and have an off the ground percentage of 60+%, but extreme FB profiles probably only make sense for extreme power guys.

Carson’s article had Rhys Hoskins in it, but also Willians Astudillo, who probably won’t become a star. I think it is good to look for prospects who don’t hit on the ground too much, but I’m OK if my prospect hits like 45% grounders since many prospects tend to improve that a little in the majors, and I don’t think looking for extreme off the ground profiles brings that much of an extra advantage.

However, when a guy hits a ton of grounders, it is a red flag, especially if it comes with K issues. If you can’t make contact better, make your contact count with hard-hit fly balls. Moncada has that problem somewhat, and needs to improve that.

However, what is also bad is pop-ups with no power. J.P. Crawford, for example, has good off the ground rates (almost 60%) but also insane pop-up rates. He is starting to develop some pop, but unless it gets better, he probably might be a low-BABIP guy. He probably might be better off with a more conservative batted-ball profile of like 45% grounders and a little less pop-ups, so that his BABIP gets better. His off the ground rate is 60% but his effective off the ground rate is actually slightly under 50%, which means he is not getting the benefit of staying off the ground, but is paying the costs.

Of course, his plate discipline and contact profile would still work with average power, but the batted-ball profile definitely is not ideal.

AL Comeback Player of the Year: There’s a case for many players who could potentially receive this award. For me personally, I would have to pick either Mike Moustakas, who has seen a resurgence after being plagued by injuries last season, or Ervin Santana, who has been the ace of the Twins’ staff and may help carry them to a playoff appearance.

NL Comeback Player of the Year: From a pitching standpoint, Zack Greinke would be a good choice, as he has pitched like the $206-million ace that Arizona thought he might be. Others such as Ryan Zimmerman and Michael Conforto should also be up for consideration.

AL Manager of the Year: This one is a bit tougher, because there are so many managers who have their teams performing beyond expectations for this season. If I could only pick one at the moment, it would be Mike Scioscia. Even with Mike Trout missing significant time due to injury and the rest of the roster mostly depleted of talent, it’s incredible to see that the Angels are just a couple games out of a Wild Card spot.

NL Manager of the Year: While Bud Black has the Rockies performing at their peak, I believe Torey Lovullo has to be the front-runner for this award, considering where the Diamondbacks were last season and how he has been able to unleash the maximum potential out of some players that the baseball community had previously written off, while overcoming injury woes that haunted the team last season.

AL Rookie of the Year: Aaron Judge. I know that he hasn’t been able to buy a hit since the All-Star break, but he has still out-performed other rookies above and beyond, and still has a good chance to break Mark McGwire’s record for most home runs by a rookie (48).

NL Rookie of the Year: Cody Bellinger. Just like with Judge, Cody Bellinger burst onto the scene and was crushing baseballs at an outrageous pace, much like Gary Sanchez did in 2016. Bellinger has out-performed other NL rookies, so this award should be his for the taking.

AL Cy Young: Chris Sale. So far, the Red Sox have been more than satisfied by the results of the trade they made last offseason. Their intimidating left-hander has been shutting down lineups just as Dave Dombrowski had hoped. An argument could also be made for Corey Kluber, but because he missed some time this season due to injury, I believe Sale should have no problem getting his first Cy Young, especially if he wins the pitching triple crown.

NL Cy Young: Despite both of these pitchers suffering from injuries, it would be hard to give the Cy Young to someone other than Clayton Kershaw or Max Scherzer. It’s hard to decide between the two of them at the moment, but the choice will probably be much more clear after the conclusion of the season.

AL MVP: If you had asked me this question before the All-Star break, I would have definitely picked Aaron Judge. However, due to his recent struggles, I would have to give this award to Jose Altuve. Altuve stands at the moment with an amazing .358 average while also leading in stolen bases. Altuve is often under-appreciated due to his small stature, but he has led the big leagues in hits since his arrival, and this season is his best opportunity to win a well-deserved MVP, especially since Trout also missed significant time with a thumb injury.

NL MVP: The answer out of many people’s mouths at the moment would be Giancarlo Stanton. However, despite the torrid pace at which he is hitting home runs, I believe someone like Nolan Arenado or Paul Goldschmidt is more deserving. I was also considering Bryce Harper before his injury, which could potentially sideline him for the season. If not for Kris Bryant, Nolan Arenado would have won the MVP last season, and now that both him and Goldschmidt have put their teams in positions to make deep playoff runs, it’s time in 2017 that all of these overlooked players finally get their well-deserved recognition.

Starting pitching constitutes the most persistently difficult roster-management problem in baseball. The laws of supply and demand make starters exceedingly expensive, while the laws of biomechanics make starters exceedingly unreliable. When Terry Francona had uberreliever Andrew Miller throw 151 innings (or something) during the 2016 postseason, people began to say “why not do that all the time?” And with MLB offenses scoring 4.67 runs per game, a level not seen since the tail end of Vitamin B-12 Era in 2007, the entire concept of starting pitching has come under withering scrutiny. The answer to “why not use relievers all the time” used to be “because it wouldn’t work, you remarkably silly person.” But now, with starters routinely getting shelled, it’s becoming clearer that the current default approach isn’t necessarily working either.

The internets are positively chock full of people anticipating the post-starter world (see, e.g., here and here). Cubs broadcaster Len Kasper, who has given starting pitching a lot of thought over the years, recently suggested removing the five-inning minimum as a condition for a win, in order to encourage managers to be more creative with starter usage (and, perhaps, to discourage Jon Lester from flattening Joe Maddon when he gets yanked after 4 2/3). The arguments for moving beyond traditional pitcher usage are creative and intriguing.

This future may seem exciting, but it still appears to be a long way off. While starter innings have certainly ebbed since the days of Big Ed Walsh, who led the charted universe with 422 IP in 1907, the number of innings per start has stabilized somewhat in recent years. And there is little evidence that shortening starters’ outings necessarily enhances run suppression.

Since 2007, innings/start has varied from a high of 6.0 in 2010 and 2011, to a low of 5.6, last season and this. From 2007 – 2009 the average was 5.8. Since 2011, innings per start, and the average number of pitches per start, have been generally declining, but run scoring has been increasing since 2014. The correlation between runs and the other variables seems weak, and to the extent a relationship exists at all, it appears to be an inverse one: from 2007 to the present, innings per start declined from the previous year when, and only when, run scoring rose (2012, 2015, and 2016). If a conclusion can be drawn from this limited and noisy data, it’s that starter innings fall more as the result of hitter success than clever managerial design. (This year is so far an exception — runs are up over last year but innings per start and average starter pitch count have remained the same.)

Many readers are surely now reaching for their 2015 Kansas City Royals World Series key chains, and The Fighting Yosts were indeed third in the American League in run suppression that year with a below-average innings per start of 5.6. The famous trio of Wade Davis, Ryan Madson, and Kelvin Herrera (and the less famous Franklin Morales) led a unit that amassed 5.0 WAR, good for a four-way tie for third in the majors. This was a significant achievement, but just as importantly, one hard to maintain. Just three teams have amassed 15.0 bullpen WAR over the last three full seasons: the Royals, Orioles, and Yankees. Of those teams, only the Orioles were in the top 10 in bullpen innings over the same period. Conversely, many of the teams that led the way in bullpen innings didn’t get stellar results: seven of the top 10 teams in bullpen usage failed to get even 10 WAR out of their bullpens over the three-year span.

This isn’t to say a pen-first strategy can’t work, but that it hasn’t worked so far in a sufficiently repeatable manner to dislodge traditional starting pitching. And a lot of that probably has to do with the relative quality of relievers. Many, if not most, are failed starters. They either lack the stamina to go deep into games or they never developed an adequate third pitch. A move to the pen mitigates those shortcomings, but does not eliminate them. An injury-prone starter may still be injury-prone coming out of the pen, and the absence of the third pitch will really hurt on those days, and there will be some, when the first two just aren’t working. And then there’s the statistical problem — it’s simply more difficult to get a good numerical read of a reliever because there are fewer innings by which to judge him. However unreliable starters are, relievers are for the most part even unreliable-er.

Change is happening. Managers are becoming slightly more averse to having their starters face hitters a third time. It happened in roughly 3,000 fewer plate appearances in 2016 than it did in 2007, a small but noticeable change. Tandem starts are perhaps becoming more common out of the nominal fifth-starter slot, even if these are officially unacknowledged. The Cubs survived the Eddie Butler Intermediate Period earlier this year by having Mike Montgomery come in and throw three innings after Butler’s usually early exit. MLB teams averaged 106 relief appearances of more than one inning last season, the highest in recent years.

That said, at the end of the day, talent probably wins a lot more baseball games than creative pitcher usage. There may be a vast storehouse of as yet unlocked wins lying around the bullpen amidst the ball bags, spent seed husks, and vaguely creepy masks. It seems more likely, however, that any improvement in pitcher deployment would bring marginal improvements in team performance rather than revolutionary changes. The remarkable resistance to sustained experimentation with pitching usage may stem from hidebound traditionalism or the timidity of the herd. But that explanation carries less force than it once did, given that there are today few front offices that can safely be characterized as hidebound or herdlike. It’s at least equally possible that teams have not taken hammers to pitching orthodoxy because they have concluded that this would be a waste of perfectly good hammers. Teams searching for more wins appear to be spending most of their time looking elsewhere.

This is not a paean to The Good Old Days, but rather a suggestion that shifting more innings to the bullpen may be more about moving risk than reducing it. The real hidden treasure buried somewhere in the pitching portion of the roster lies in unlocking the secrets of durable elbows and shoulders, and then being able to identify those in players still too young to legally drink. This would expand the supply of sustainable run-suppression talent, making pitchers a more predictable investment. This in turn could finally lead baseball away from its fascination with 14-man staffs, allowing for better-balanced rosters, more interesting game play, and fewer four-pitcher innings, since managers would be able to trust the men they are sending out to the mound, rather than placing all their faith in platoon splits. Heck, it might even lead to peace on the Korean peninsula and whiter, brighter teeth, too.

One way to deal with a presently unsolvable problem is to de-emphasize it. The Mets tried to build around young starting pitching and failed. The Astros didn’t, and didn’t. Their approach has been to invest modest resources in a more or less traditionally-deployed rotation while building around a MOAB offense and a high-quality, if not an extraordinarily high-quantity, bullpen. Expect more teams to follow this path until the buried treasure is unearthed.

This year, the NL MVP will be a highly-contested race among players such as Cody Bellinger, Nolan Arenado, Kris Bryant, Justin Turner, Paul Goldschmidt, and the superior all-around player, Joey Votto. If the season ended today (as of August 14, 2017), Votto, an average defender who has the best combination of power and OBP at the plate, should win the NL MVP this year.

According to Baseball Reference, Joey Votto boasts the highest-ranking OBP — of .446 — in the National League, along with having the third-most home runs, with 31. He ranks sixth in slugging at .600, second in OPS+ at 169, and second in runs created with 114. He ranks first in batting runs and batting wins with 48 and 4.5, respectively. Votto may not be the biggest slugger in the league, but there is no other player who hits for as much power while also getting out as infrequently and getting on base as frequently. In fact, he is the only current NL player with a .400 OBP and at least 30 HR. Compared to all other players with at least 20 home runs, nobody has been on base more times without reaching on error than Joey Votto.

Among players with 60 or fewer strikeouts, he ranks first in home runs, second in SLG, first in runs produced, first in WAR, and first in win probability added. Among players with 300 or fewer outs made, Votto is second in home runs, second in OPS+, and second in total bases.

Stanton and Bellinger, the only players in the NL with more home runs than Votto, have a combined 104 strikeouts more than Votto.

According to FanGraphs, Joey ranks first in wOBA (.431), second in wRC+ (165), and first in wRC (111). His 11.5 K% is the sixth-lowest in the league among qualified hitters, and his 47.9 wRAA (weighted runs above average) ranks first, along with his 18.5 BB%. His .287 ISO is fifth in the National League.

Joey has 3.7 Wins Above Average, which ranks third among all players in the National League. His 5.3 WAR in second among all position players, his 4.8 oWAR is second, and his 4.0 WPA is third.

At 33 years old, Joey Votto is having a career year, and if the season were to end now, he should have an MVP season. Hitters who get on base as often and strike out as rarely as Votto while also hitting for as much power are increasingly rare. I think he has a decent shot of winning this year; however, the ludicrous belief that the MVP should be on a playoff team is still rather prevalent, unfortunately. The Reds are not a good team this year, but this does not detract anything from what Votto has done this year. Hopefully, voters will recognize the value that he has brought to the Reds, and the exceptional way in which he has done it.