NL West Edition

We’ve all been there and done that, our dynasty/keeper league(s) haven’t gone as planned. Perhaps you went for it in the offseason, ditched your prospects for grizzled productive vets and it all went south from there. No matter your story, the rebuild can be difficult in the sense of valuing the players you want. You could fall into the “shiny new toy trap” and end up with a bust or broken player (envision a Joc Pederson type in an AVG league instead of OBP). In this upcoming series, I will be highlighting players based on positions and pointing out whether I’d go for them in separate leagues (NL/AL only) or mixed.

So without further ado, here’s the first segment.

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At age 35, Albert Pujols is having somewhat of a resurgent season. Many wrote him off last year after he posted his second straight, for him, subpar season. This year, though, he has hit 30 home runs through 108 games with ZiPS projecting him to get to 40 on the season. But there remain two big differences between 2015 and prime Pujols. One, he is walking less, at 7.5% vs. his career average of 11.8%. And two, his BABIP is a minuscule .228, continuing a declining trend:

It certainly makes sense that with a loss of footspeed, BABIP would decline as well. After doing a quick mental recall, I decided to look up Mo Vaughn as another power hitter who seemingly lost it overnight. And sure enough, he experienced a big BABIP decline late in his career as well:

He still put up a .314 BABIP in his last full season, but it was a step change from the average .365 (!!!) BABIP he put up from 25-30.

So, is this a larger trend that we should be paying attention to? Or are Pujols and Vaughn just confirmation bias. Thanks to FanGraphs’ excellently downloadable data, I expanded the datatset to include every season and every player. Grouping by age reveals:

Well seemingly a lot of nothing. The BABIP for all 20 year olds in that time was .301, while the BABIP for all 39 year olds was .295. Definitely a decline, but with a p-value of 0.7 is not statistically significant. So that’s disappointing for my thesis, but encouraging for all the old folks out there! Back to the drawing board.

Pujols and Vaughn were big, hulking guys. Maybe when they lost a step, it was a step that they could less afford to lose and the impact on their BABIP of a marginal slowing down was magnified. So what if we restrict the group to only power hitters? For this, I defined power hitters as players with career ISOs over .200. The results appear to support my hypothesis better:

This is plotted on the same scale as the previous chart so we can appreciate the relative differences. For this sample, the BABIP for power hitters declined from .313 at age 22 to .296 at age 36. Interestingly enough, power hitters had higher BABIPs earlier in their careers than the general population (including the power hitters), which then dip lower than the general population later in their careers. Apparently hitting the ball hard does have some benefits.

This time, the science backs up the hypothesis! My engineering professors would be so proud. With a p-value of 0.0165, the difference in BABIP between a 36 year old power hitter and a 22 year old power hitter is statistically significant. Pujols and Vaughn were indeed the victims of a real trend.

There could be a number of factors behind this. The first one I highlighted is the loss of footspeed. Second, it could just be that as you get older you don’t hit the ball as hard. Looking at exit velocity or ISO by age would help us judge that. Finally, age and a loss of bat speed or reflexes could lead to a change in batted ball in a way that leads to less balls falling for hits. It would make sense that as his bat speed slowed, Pujols tried to hit more fly balls to recover some of the home run power. That is the next thing I will look at.

Prospects are the lifeblood of any baseball organization. They have the ability to provide large amounts of value for their team while making a fraction of what they could earn on the open market. This provides a huge competitive advantage for teams that have a superior player development system. Every organization has a different plan for their prospects and the purpose of this research was to attempt to determine which development plan yields the most production in a team’s cost controlled years for each group of players.

The Data

The first step in gathering the data was to find every hitter that debuted from 1995-2009. I stopped at 2009, because this covers most of the prospect’s cost controlled years. I chose to start in 1995, because it gave me a big sample size and I got to avoid the strike year of 1994. Next, I omitted anyone who debuted at the age of 29 or older. I did this, because players that are over 28 are usually not considered prospects and their clubs would not consider them to be future building blocks for their organization.

The final step was to eliminate anyone who did not exceed their rookie limits. I decided to omit these players, because any player that cannot amass 130 at bats in their career was probably never considered a serious prospect. If they were, at least one team would have given them more opportunities to earn a starting job.

Methodology

To determine a player’s production during his cost controlled years, I found when every player exceeded their rookie status and added the next five years of WAR to their total. If the player had previous major league experience prior to the season they lost their rookie status, I included those numbers as well. For a player’s minor league plate appearances total, I included all of their plate appearances from the start of their professional career up to and including the year they lost their rookie status.

I then broke up the data by player groups. I split up the data by players who attended college, American born players that did not attend college and international born players that did not attend college. Throughout the rest of this article, I will simply refer to these groups as college players, high school players and international players.

Next, I partitioned the data by minor league plate appearances. I decided to split the plate appearances into groups of 500. I chose this amount of plate appearances, because it is a nice proxy for a full season of production and it splits the data into a fairly even distribution of players among the groups.

Overall Performance

I’ll start by giving a simple overview of total player production over their cost controlled years. The table below shows the median WAR for each grouping. I decided to use median instead of average throughout this article, because the WAR measurement is right skewed instead of normally distributed.

Median WAR for All Players

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College Observations

As you can see in the table above, college players need the least amount of plate appearances to produce a high level of WAR, but there is a sharp decline in production when a college player amasses over 2500 plate appearances. It makes sense that this player group is the quickest to develop, because they have had several more years of amateur competition to help hone their skills for professional baseball. This should create a smoother transition period for these players and reduce the amount of plate appearances needed to become a valued member of the major league club.

High School Observations

Unlike their college counterparts, American high school players take an extra 500 plate appearances before they reach their peak value of 15.4 WAR. However, high school players also have a wider range of success than either college or international players. High school players also produce more than the other two groups of players. This result may seem counter-intuitive, since it is commonly accepted that high school players are riskier prospects than college players. It is important to remember that this process does not account for all of the high school prospects that never receive an at bat in the majors. We therefore create a selection bias where we only look at the players that were good enough to make it to the majors in the first place. This means that if a high school player is good enough to make it to the majors; he’s probably going to be a productive major leaguer.

International Observations

The international player group offers the least amount of production. I believe there are several factors that contribute to this result. One of the main factors could be that many of these players have not played as much organized baseball as their counterparts. I also think that there could potentially be a language barrier issue that makes it more difficult for an organization to teach foreign players as opposed to their English speaking teammates. Of course that conclusion is just pure speculation on my part, but I believe that it is a reasonable assumption to make.

Total Player Summary

As the table above shows, the longer a prospect is in the minor leagues, the less chance they have of making an impact in the major leagues. This makes sense, because if a prospect is outperforming everyone in the minor leagues, they will be called up much sooner to help the major league club than everyone else. This leads me to believe that this table may not be the most informative for every minor leaguer. Perhaps, if we segment the data between Baseball America’s top 100 prospects and every other prospect, we will get a more accurate depiction of minor league development. It is essential to remember that the more we split the data, the less accurate our individual values may be. Therefore, we should not take the numerical value of WAR for each grouping too seriously. It is more important to take an overall view of the values in the tables below before drawing any conclusions about player development.

Median WAR for Top 100 Prospects

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Top 100 Prospects Summary

Yet again, we see that college players develop the quickest and that high school players take a little longer to develop. College players also have a quick drop in production after 1000 plate appearances, but they still yield the highest production of the three groups. International prospects are a bit of a mystery here. There does not seem to be a pattern in their production. I assume this is because there are major differences in baseball development between South American prospects, Japanese prospects and Canadian prospects, and any other nation’s prospects you can think of. In the future I may revisit this issue, but for now I’ll have to make do with what I have.

Median WAR for Non-Top 100 Prospects

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Non-Top 100 Prospects Summary

As expected, we see a dramatic drop in overall WAR across the board. This means that Baseball America is usually correct when identifying the most impactful future major league players. Kudos to you Baseball America. We also observe that these groups of players develop a bit more slowly than their more heralded prospects. These college players continue to peak early, but they are still 500 plate appearances in development behind the top prospects. High school players take even longer to develop now with a peak of 2.8 WAR in the 2001-2500 plate appearances group as opposed to 15.4 WAR in the 1001-1500 plate appearances group for the top high school prospects. International players are much more consistent in this table than the previous one. Unfortunately, they also have the worst total median WAR of 0.1.

Conclusions

So let’s do a quick recap. Usually the less time a player spends in the minors, the more productive they will be in the majors. High school prospects offer the most production, while international prospects offer the least production and college prospects fall somewhere in-between. We also observed that college prospects develop the quickest, high school prospects develop a little slower and international prospects are a bit of a mixed bag. I attributed this to simply combining all foreign born players into one group instead of by nation or continent.  I hope this article has been informative and that it provides some guidance on when teams should consider calling up their most prized assets.

To a casual baseball fan, Stephen Strasburg’s numbers are not pretty. The owner of a 4.76 ERA and a 1.38 WHIP, Strasburg is clearly having the worst season of his career. But how bad has he been, really? Not as bad as you think. Take a look at these 2015 stats:

Player A: 3.48 xFIP, 22.8 K%, 5.5 BB%
Player B: 3.31 xFIP, 24.1 K%, 5.3 BB%
Player C: 3.18 xFIP, 24.9 K%, 6.0 BB%

Player A is none other than Johny Cueto, recently traded to the Kansas City Royals. 12th in ERA among qualified pitchers, Cueto is widely considered among the best, and perhaps deservedly so with five straight years of a sub-3 ERA. While he has consistently outperformed the above metrics, they are still indicative of general pitcher performance and should not be overlooked when comparing the quality of different pitchers.

Player B actually has the fifth lowest ERA among qualified pitchers and was also traded at the deadline. He’s been one of the most reliable pitchers over the past five years and has been an ace on every staff for which he’s pitched. Player B is David Price.

Player C is obviously Stephen Strasburg, and as you can see, his peripheral stats stack up against the best in the game. In addition to these 2 players, Strasburg also compares positively to others like Sonny Gray and Scott Kazmir, both of whom have better ERAs but a worse xFIP, K%, and BB%.  Strasburg is pitching like an ace, and xFIP shows that, so why have his results been so poor?

Well, first of all, there’s his .345 BABIP. Not only is this high compared to the league average (.296), it’s well above his career mark of .302. Considering he’s not giving up any more line drives or hard contact than usual, his BABIP should fall back to around the .300 mark and bring his ERA down with it.

Not only is his BABIP at an all-time high, his LOB% is at an all-time low. Currently at 65.3%, it figures to inch back up to his career 73.2% mark, or at least to the league average of 72.4%. Considering his strikeouts have not dropped off, there’s no reason for his drop on LOB%, and it can simply be chalked up to bad luck, something that he’s had plenty of this year.

Looking at these stats, there’s nothing that suggests Strasburg is anything but unlucky. However, as Jeff Sullivan pointed out here, Strasburg’s problem could stem from the injury he suffered in the spring. He had apparently adjusted his mechanics to compensate for the discomfort, and even though it appears as though he has fixed this, it’s possible that when pitching from the stretch and in higher leverage situations, he returns to this altered motion by default. When looking at the difference in Strasburg’s stats between pitching from the windup and the stretch, this is what we see:

Evidently, this claim has some ground. Strasburg is clearly having some problems with runners on base, particularly in striking batters out. Before we deal with the strikeout numbers, let’s take a look to make sure that he’s not just getting killed during the at bats that don’t end in strikeouts.

Strasburg is actually generating more ground balls and weaker contact with runners on base. His infield hit percentage is triple what it is when the bases are empty, something that can be attributed to luck. With such weak contact, it’s safe to say this isn’t the problem. So it must be the strikeouts. If we take a look at his whiff rates, the results are intriguing:

OK, so there’s definitely a problem here. With runners on base, he’s only whiffing batters at half the rate he’s done previously in his career, as well as half the rate that he does with the bases empty. So what’s the issue? Well, it’s not his pitch velocity:

He could be playing (Saturday). I’m not sure yet. I want to see how it plays today, but I wanted to be upfront with him and just let him know it’s not just a day off.

— Joe Maddon

And with those words on Friday, August 7th, the Castro Regime fell in Chicago. Starlin Castro has earned the pine, posting an abysmal .268 on-base, around 50 points worse than the MLB average. Power has been even more of a problem; Castro’s ISO of .068 is sixth worst in MLB among qualifying hitters. It is also the worst of Castro’s professional career. Maybe he contributes with speed? Nope, not since 2012, when Castro stole 25 in 38 tries. He’s had only 23 ineffective attempts since then. His defense, long and loudly criticized, hasn’t been all bad; the metrics differ on him, but add them all up (metaphorically, anyway) and he seems to grade out about average.

Castro is striking out only a bit more this year than he has in his career (16.8% vs. 15.7%), but he’s making weaker contact. His infield fly percentage is at a career high of 12.9%, a full 5% higher than his career average. It was high last year, too, but he made up for it with a line-drive rate of over 22%. The line drives are gone this year, with Castro hitting a career low of 15.8%, which is, like his ISO, sixth worst among qualifiers.

Castro isn’t obviously being pitched differently this year. He’s seeing a few more strikes, but that’s probably an effect of his power outage rather than a cause. It doesn’t seem that pitchers have found some sort of secret recipe to deprive him of hits. Rather, it appears that fastballs are simply overwhelming him. According to his PITCHf/x data, Castro’s done pretty well against most offspeed pitches, but he has a league worst -2.70 runs above average/100 against four-seamers, and he’s 4th worst against two-seamers (-2.74). There are some decent hitters who have struggled with one of those pitches this year, but no one has been as bad as Castro at both.

Castro has been known to travel with a rough crowd, and more recently there’s been some ADD speculation. The Cubs organization is hinting that conditioning is a problem, which would explain the loss of power and his inability to hit the fastball. Perhaps, but Castro is 10th overall in total plate appearances since 2012. Whatever his problems may be, durability hasn’t been one of them.

And it’s worth remembering that Castro plays the most difficult position in what is arguably the most difficult team sport. He’s still only 25 years old, and by the standards of young shortstops, Castro has done quite well so far. He’s 29th in career bWAR (8.1) in the divisional era for shortstops through age 25. There are some great players in the top 50, and some not-great players, but there’s only one real disaster: Bobby Crosby at #40. (Ok, Rafael Ramirez at #39 was pretty bad too.) So Castro could have a Crosby-Ramirez future, in which he rapidly descends into mediocrity and irrelevance. But the vast majority of players with achievements similar to his at age 25 did not.

This suggests that either patience or a change of scenery could help Castro, as Grant Brisbee suggested in refuting the ADD speculation in the post linked above. Patience would not, however, seem to be the right move for the Cubs at the moment. Theo Epstein correctly eschewed the splashy megamove at the trade deadline: the wildcard game isn’t worth surrendering prospects. But it makes sense to to take less costly steps to improve this roster for the stretch run, and Castro is easily the biggest hole on the 25-man roster, with arguable exception of the 5th starter slot, now filled (for the moment, at least) by Dan Haren. The Cubs have been more than patient with Castro, and the performance hasn’t been there. Maybe they can give him more at-bats if they fall out of contention, but right now the team’s immediate future matters more than Castro’s.

That said, maybe the Cubs could spend a few minutes rethinking their approach to Castro. He’s has had three different managers in the last three years, each using a different approach with him. Dale Sveum’s tough love didn’t work, and Maddon’s zany zen isn’t working either. It was Rick Renteria’s more personal approach that seemed to get the most out of Castro. The karmic wheel spins in unpredictable ways, and Castro’s collapse may simply be the earthly price the Cubs are paying for Renteria’s defenestration, but it also suggests Castro can be reached, because someone was able to do it. Maddon is intelligent enough to realize this, and flexible enough to recognize that the shtick that works for most players doesn’t work for all. If Castro’s benching is coupled with some creative efforts to get him re-engaged, the Cubs may still be able to get value out of the player.

Diets, workouts, Ritalin, and perceptive coaching will be for naught if Castro is in fact the second coming of Rafael Ramirez. At some point his relatively reasonable contract will begin to look like an albatross, and the Cubs will cut him loose or trade him for minimal return. It would be helpful if players came equipped with little red crystals in their palms that glowed when the player reached his ceiling, but that won’t happen until at least the next renegotiation of the CBA.  So yes, it is possible that Castro has plateaued, and neither he nor the Cubs have figured that out yet.

But the Cubs have a little time. They can jury-rig their infield until they’re ready to press Javier Baez (or even Arismendy Alcantara) into service. They can see how the rest of the season develops, and how Castro progresses as they attempt to rebuild him in place, much like they’re doing with Wrigley Field.  As many have observed, his trade value can’t get much lower, so it doesn’t hurt the Cubs to take a little more time to see what they have. Burning a valuable roster spot on an unproductive player is dangerous, but the biggie-sized September roster is nigh.

If I had to bet, I’d bet that Castro will be moved in the offseason in exchange for someone else’s disappointment (Jed Gyorko, anyone?). But it’s not impossible that, in the top of the 12th inning of Game 7 of the 2015 World Series, Castro comes in from the end of the bench to hit the game-winning homer.  On what started as a day off.

I wish I knew why Jung-ho Kang and Ben Paulsen seem to get so little respect. It’s baffling. Regardless, people should be talking about these guys and their production — both have very legit numbers, yet few seem to have noticed. More to my point: fantasy baseball players should pick them up from the waiver wire ASAP. I mean, right this second.

Kang, recall, is the stud the Pirates signed from Korea. An unknown for the better part of the season, Kang is making his presence felt in the middle of the Pirates lineup, having just earned honors this July for NL Rookie of the Month. Kang, with dual SS/3B eligibility, is owned in just 57.9% of ESPN leagues and is slashing a highly productive .291/.365/.446 and, based on what he did in Korea, his .809 OPS could prove to be low in the long run.

Kang went through a bit of a power drought in June, but he caught fire in July. He’s now hitting .291 with 8 HR and 35 RBI. Consider that in the last week of July, Kang recorded multiple hits in five out of eight games with 6 R, 2 HR, and 3 RBI in that stretch. In his next game, on August 1, he hit his 8th home run of the season, a ball that traveled 412 feet. In 2014, Kang launched 40 home runs in 120 games in Korea, while also hitting .297. The kid can flat-out rake. With Jordy Mercer on the shelf (and not very good when healthy), Kang continues to occupy the 4–6 holes in Clint Hurdle’s lineup.

As many hitters have said before: As the summer heats up, so do they. I suspect we’re going to see Kang launch many more home runs before season’s end. If nothing else, even if the power is merely moderate, the fact that he hits for average, steals a few bases, and slots in the middle of a very potent Bucs lineup makes him worthy of a pickup in leagues of any size.

Ben Paulsen. What’s not to love about a guy who: 1) plays half his games at Coors Field; 2) made minor league pitching look like little league; 3) hits for both power and average; and 4) absolutely kills right-handed pitching? Answer: Nothing. His numbers aren’t dissimilar from those of Kang (in fact, they’re nearly identical), with a .300 average, 8 HR, and 34 RBI. His average is a bit buoyed by a .363 BABIP, though ZiPS projects a .333 BABIP the rest of the way. The only knocks against Paulsen are playing time and his ugly platoon splits, which are obviously related. But as with guys I’ve discussed before, who cares if he’s not an everyday starter; he’d just tank your average anyway. Instead, bench him against the few lefties he’s allowed to face, and you won’t be disappointed.

FanGraphs had this to say about him before the season started; it’s like these guys are clairvoyant or something. But they’re also very much wrong in the when they say that Paulsen’s game is made for just NL-only leagues. It’s much better than that (keep reading). Per FanGraphs:

The Quick Opinion: If Morneau starts the year on the disabled list as he recovers from knee surgery, Paulsen could be a sneaky short-term option in NL-only leagues, but that’s about it.

Paulsen, actually, is now effectively an everyday starter in the mercurial Walt Weiss’ lineup, thanks to the demotion of Wilin “Baby Bull” Rosario. Justin Morneau’s concussion symptoms are persisting, and he may have played his final game in the big leagues. Thus, the gig is Paulsen’s to lose, and with Corey Dickerson on the DL again, Paulsen has also been playing some corner outfield when called upon.

And when the 27-year old Paulsen is called upon, the numbers are a thing of beauty — against RHP, anyway, who he’s torturing to the tune of a .308/.361/.535 triple slash. Paulsen’s OPS of .896 isn’t just ‘productive,’ it’s downright fantastic. Frankly, it’s more than a little weird that just 19.7% of ESPN players own him. I’m happy to say I’m one of them, though I missed out on Kang, much to my dismay (and totally because of my stupidity).

There will be more blogs to follow, with similar themes in mind: finding value where there seemingly is none. There always is, you just have to look hard enough.

The last time Matt Shoemaker allowed more than two runs in an outing was June 19. Since then, he’s pitched 37 1/3 innings, allowing just seven earned runs. He has 35 strikeouts compared to just 11 walks, leading to a 2.88 FIP. He’s been even better when just isolating the numbers in his three starts since the All-Star break, with 27/6 K/BB and a 1.36 FIP, although, to be fair, that is an incredibly small sample. For comparison’s sake, his FIP through June 19 was 4.70.

So has there been a change in Shoemaker’s game, or has his streak been a fluke? Well, I wouldn’t be writing this if it was the latter, as I’m sure you could’ve guessed (although if you weren’t able to guess who the article was about after the first paragraph, perhaps I’m overestimating you). There’s been a significant change in the way Shoemaker has approached batters. Take a look at his pitch type chart through June 19, courtesy of Baseball Savant:

And then take a look at the data since then:

Through June 19, Shoemaker threw his fastball (four-seam and two-seam) 51.6% of the time. Since then, it’s been 56.9% of the time. Comparing these two proportions with a two-tailed Z test yields a p-value of .034, significant at the .05 level, showing that there has indeed been in a difference in the amount of fastballs he’s thrown.

Of course, throwing more fastballs doesn’t translate to a drop in FIP of over 3 points. That is, unless, those fastballs are of higher quality. And, class, what’s the most important aspect of a fastball? Hopefully you were at least able to guess this one: the velocity. Which, naturally, is the next thing I looked at.

Again, I used Baseball Savant’s PITCHf/x data. Narrowing the results to just fastballs, here are the velocities of Shoemaker’s pitches this year:

At the beginning of the season, Shoemaker’s average fastball velocity hovered right above 88 mph. Since then, it’s steadily risen, and there’s a clear jump about two-thirds of the way into the season (note that this time would be remarkably near June 19). After the jump, his average velocity has hung closer to the 92 mph range, further away from Jered Weaver status. FanGraphs data shows the same thing:

Note, this data also shows Shoemaker’s average velocity from 2014, when he had a 3.04 ERA and a 3.19 SIERA. This image confirms the steady increase in velocity of Shoemaker’s fastball, as it has recently resided at or even above its value from last year’s productive season. There have been clear results from this change, especially in the form of whiff rate, and predictably, strikeouts. Through June 19, Shoemaker’s whiff rate sat at a mediocre 10.5%.

Since the All-Star break, this is what that breakdown looks like:

You might notice that his whiff rate sits at 13.7%, which would be top-5 among starters if he managed it for an entire season. Now, I’m not naive enough to think that number is where is true value lies after just 3 games, but he’s certainly improved off his 10.2% mark he had earlier in the season.

I’m not suggesting Shoemaker is the next coming of Clayton Kershaw. I’m not even sure if he’s the best pitcher on his own staff. But one thing is for sure: Matt Shoemaker is throwing the ball harder than he has in the past, and it’s working. And while it may not continue at this level, there’s no reason it should stop.

Note: Norris has now signed with the Padres.

—

Hey, remember Bud Norris? The guy who was an opening day starter for the 2013 Astros (although that team lost 111 games, so that might not be something to brag about). He then was traded for prospect Josh Hader (who was just traded for Carlos Gomez), and a replacement level player in L.J. Hoes and a compensatory 1^st round pick. The draft pick turned out to be Virginia’s Derek Fischer who has hit 19 dingers for the Astros single-A club in 2015. He won 19 of his first 35 starts with the Orioles. This O’s pitcher got released on August 8^th after clearing waivers. He is now free to sign with any team willing to take on his services. Norris has been a huge disappointment in 2015 — actually huge disappointment would be an understatement. The Orioles signed Norris to a one-year, $8.8 million contract last winter to avoid an arbitration hearing. He was slated to solidify the middle/back end of the O’s rotation. A solid veteran who over his first five full years in the league averaged a WAR right around 2. He has never been flashy but always solid, until 2015. 2015 is the year of the Bud Norris Apocalypse. Norris sported an ERA of 7.06, and a Win-Loss record of 2-9. So is Norris this bad, or is he a victim of bad luck, and is picking him up for a pro-rated portion of the league minimum worth it?

What changed in 2015 versus the rest of Norris’ career that saw him deliver an average ERA of 4.20 over parts of six seasons? There’s a few factors that snakebite Norris in 2015. The first is Norris had a brutal increase in his FB/HR rate. For his whole career (2015 included), 11.4% of the fly balls hit against Norris went over the wall. This year that number ballooned to 17.7%. That is over a 55% jump. Why the huge jump in FB/HR rate? Well, it is not that his fastball velocity dipped, in fact his fastball velocity is over .6 mph faster than his career average of 92.9 mph. Norris is throwing the same rate of strikes vs. his career rate (63%). He has not been throwing in the middle of the plate any more than usual either. In fact, on pitches in the middle third of the strike zone he has thrown 0.7% less pitches than his career average.

Perhaps the reason behind the change in FB/HR rate is luck, but Norris is also throwing 7% more fastballs than the career average. Batters may have been sitting on his fastball more than usual and were teeing off. My thinking is that when a pitcher does not have a huge drop in velocity or major change in strikes thrown, the huge increase in FB/HR rate must be something of a fluke. Norris also got snakebitten by an awful LOB% of 59.5%. His career rate is 72%. Maybe this is just a product of being unlucky. But Norris has been miserable in situations with men on base; with runners in scoring position, batters were hitting .313. No pitcher on earth is going to have a good ERA when batters are hitting over .300 with RISP.

To recap, it seems that Norris may have been much more unlucky this year than other years in his career. He has not been good by any means, but he is not as bad as the 7.06 ERA he has this season. The xFIP and SIERA projections give Bud an estimated ERA of 4.55 and 4.48 much closer to his career mark of 4.20. It seems that Norris has been plagued this season by an inability to pitch with RISP and an awful FB/HR rate. I highly doubt anyone is going to confuse Norris for a top-tier starter, but he should still be a serviceable back of the rotation option.

Signing Bud Norris at this point in the season has practically no risk. If Norris signed for the league minimum, it would be pro-rated to roughly $150,000. Norris could serve as a $150,000 insurance policy in the event that a starting pitcher goes down. He could get picked up and put in the bullpen in a long-relief role with the capability of making a spot start. Having a viable long-relief man is huge during the late months of the season as teams try to save their bullpens. He could easily be picked up by a team like Minnesota who is 4 games back of the wild card. They could use back of the rotation help with the injury to Tommy Milone. The Giants could use rotation help with the recent injury to Mike Leake. And unless Kansas City feels comfortable running Jeremy Guthrie out to the mound every 5th day, Norris could be a good fit. Even a team like St. Louis or Tampa could use him for a spot start to give some rest to fairly young starting rotation. There could potentially be multiple landing spots for Bud. While Norris is not a flashy option by any means, he is a veteran who could easily be a band-aid for a team with a banged up rotation or just simply looking for someone to eat innings.

*Stats acquired from FanGraphs.com and Baseball-Reference.com.

The importance of getting ahead of hitters is stressed to pitchers from the first time they play in a non-coach-pitch league.  It’s not what happens on the pitch immediately following a first pitch strike, it’s because the numbers for the rest of the at bat sway dramatically in the pitcher’s favor.

These are league averages, but for the most part they apply to individual hitters as well.  Paul Goldschmidt is not a “league average” hitter, in fact, he is at least in the conversation when discussing the best hitter in baseball right now (2015) – and I only say at least because I’m too afraid of the backlash I might receive if I declared him the best.  But regardless if a pitcher is facing an average hitter or an elite hitter, the law of getting ahead applies –  even if the numbers for Goldschmidt do look a bit different from the table of above.

Paul Goldschimdt is just so strong, and so adept at making hard contact to all parts of the field that, even at his worst, he’s still so much better than other professional hitters.  The results clearly show that he’s a lesser version of himself throughout the duration of an at-bat that starts with a first-pitch strike, but here’s the thing: getting a first-pitch strike on Goldschmidt isn’t easy.  Not only is he discerning, but he is so devastatingly destructive when he sees something he likes.  Pitchers have gotten a first pitch strike against Goldschmidt 56.7% this season (league average is 61.1%).  In 471 PA, Paul Goldschmidt has only swung 126 times at first pitches, or 26.8%.  It could be said that Paul Goldschmidt “goes to bat with a plan”.  But it’s not like pitchers’ game plans will stand idle while Goldschmidt continues to pummel them; they will make adjustments, and one adjustment they have made, because the pay-off is so dramatic, lies in figuring out how to get ahead of him.

First, let’s consider two samples from Goldschmidt’s 2015 – through July 3^rd of this year Paul Goldschmidt put up MVP numbers:

April 6 – July 3:

Since then, however, he has hit like someone who just might be mortal:

July 4 – August 4:

So what course of action have pitchers taken to get ahead of him in the count?  The answer lies in the conveniently bolded numbers featured in the CB% column of the table below.

Numbers represent the usage of pitches in all first-pitch situations to Paul Goldschmidt.

Obviously there’s been an uptick of a larger percentage in split fingers for first pitches, but a hell of a lot more pitchers throw curveballs than splitters, so that value is not really important.  What is important is that 119.5% increase in first-pitch curveballs, because Paul Goldschmidt SPITS at first pitch curveballs.  He saw twenty-eight, 1^st pitch curveballs in the sample size concluding July 3^rd and swung at a grand total of 1 of them.  Since then, in a month, he’s seen 20, first-pitch curveballs and has swung at exactly 0 of them.

Goldschmidt is looking for something hard-ish (fastball/slider/change-up; league average change up velo is 83.3 compared to 77.7 for curveballs and 84.2 for sliders) that he can drive on the first pitch, and knows he can lay off curveballs to sacrifice a first-pitch strike and still be an above-average hitter.  For the record, it’s not like Goldschmidt is bad against curveballs; he owns a 3.31 wCB/C in 2015 (3.79 through July 3^rd, and 2.16 after), it’s just that he’s committed to his plan.  Pitchers – or analysts – have noticed his disregard for curveballs as first pitches, and the pitchers – not the analysts – have twirled curveballs in to Goldschmidt on the first pitch at a much higher rate over the last month – again, that number is 119.5% more often.  While the strike percentage of these curveballs has only been 45%, that’s still up from the 28% of curveballs for first-pitch strikes through July 3^rd.

Conjecture alert:  Perhaps expecting more first-pitch curveballs, Paul Goldschmidt has readied himself to not swing at the first pitch, as he has swung at just 25.3% of non-curveball first pitches since July 4^th, compared to 32.9% through July 3^rd.  Pitchers have been able to sneak their first pitch strike percentage up against Goldy from 55.9% to 59.5% in this past month – that’s a 6.4% increase.  So it seems as though the best way to beat Paul Goldschmidt is to try to find some way to make him swing the bat less, because when he does, bad things happen to baseballs.  For clarification, I’m talking about throwing him more first pitch curveballs, not walking him every time up.

Paul Goldschmidt is so good that he will probably adjust to this new approach fairly quickly.  I said earlier, “he knows he can lay off curveballs to sacrifice a first-pitch strike and still be an above-average hitter” – Paul Goldschmidt’s aim is not to be a player who is an above-average hitter – he’s a force at the plate and he will adjust.  Health permitting, Goldschmidt will likely finish the season with at least a .300 AVG, 100 R scored, 30 HR, 100 RBI, and 20 SB – a line we haven’t seen from a first baseman since Jeff Bagwell did it in 1999.

So as Goldschmidt adjusts to this new attack from pitchers, maybe the real number to take away from this research is that Goldschmidt is partying like it’s 1999.

In “Hardball Retrospective: Evaluating Scouting and Development Outcomes for the Modern-Era Franchises”, I placed every ballplayer in the modern era (from 1901-present) on their original team. Therefore, Nolan Ryan is listed on the Mets roster for the duration of his career while the Expos / Nationals declare Gary Carter and the Marlins claim Josh Beckett. I calculated revised standings for every season based entirely on the performance of each team’s “original” players. I discuss every team’s “original” players and seasons at length along with organizational performance with respect to the Amateur Draft (or First-Year Player Draft), amateur free agent signings and other methods of player acquisition.  Season standings, WAR and Win Shares totals for the “original” teams are compared against the “actual” team results to assess each franchise’s scouting, development and general management skills.

Expanding on my research for the book, the following series of articles will reveal the finest single-season rosters for every Major League organization based on overall rankings in OWAR and OWS along with the general managers and scouting directors that constructed the teams. “Hardball Retrospective” is available in digital format on Amazon, Barnes and Noble, GooglePlay, iTunes and KoboBooks. The paperback edition is available on Amazon, Barnes and Noble and CreateSpace. Additional information and a discussion forum are offered at TuataraSoftware.com.

Don Daglow (Intellivision World Series Major League Baseball, Earl Weaver Baseball, Tony LaRussa Baseball) contributed the foreword for Hardball Retrospective. The foreword and preview of my book are accessible here.

Terminology

OWAR – Wins Above Replacement for players on “original” teams

OWS – Win Shares for players on “original” teams

OPW% – Pythagorean Won-Loss record for the “original” teams

Assessment

The 1983 St. Louis Cardinals     OWAR: 54.8     OWS: 310     OPW%: .517

GM Bing Devine acquired 73.1% (30/41) of the ballplayers on the 1983 Cardinals roster. Based on the revised standings the “Original” 1983 Cardinals edged the Expos by a single contest while pacing the National League in OWAR and OWS for the second consecutive season.

Jose Cruz (.318/14/92) topped the Senior Circuit with 189 base knocks and registered 30 Win Shares. Terry Kennedy (.284/17/98) and Ted “Simba” Simmons (.308/13/108) shared responsibilities behind the dish. First baseman Keith “Mex” Hernandez earned his sixth straight Gold Glove Award. Larry Herndon (.302/20/92) posted career-bests in batting average, hits, doubles and RBI.

Simmons ranked tenth among catchers according to Bill James in “The New Bill James Historical Baseball Abstract.” In total, eight ballplayers from the 1983 Cardinals roster registered in the “NBJHBA” top 100 rankings including Steve Carlton (15^th-P), Keith Hernandez (16^th-1B), Jose Cruz (29^th-LF), Andy Van Slyke (32^nd-CF), Tom Herr (40^th-2B), Garry Templeton (42^nd-SS) and Terry Kennedy (52^nd-C).

The Redbirds’ rotation featured John Denny (19-6, 2.37), the league-leader in victories and 1983 NL Cy Young Award winner. Steve “Lefty” Carlton tallied 15 wins while striking out a League-leading 275 batsmen. Jerry Reuss contributed a 2.94 ERA along with a 12-11 record. Luis DeLeon saved 13 contests and furnished an ERA of 2.68 with a 1.045 WHIP.

The “Original” 1983 St. Louis Cardinals roster

Honorable Mention

The “Original” 1982 Cardinals           OWAR: 54.7     OWS: 318     OPW%: .552

The majority of the Cardinals teams from 1977-1985 consistently achieved OWAR scores above 40 and/or OWS scores above 300. Due to the roster similarities I have selected the 1992 roster for additional comment.

The “Original” 1992 Cardinals           OWAR: 47.8     OWS: 286     OPW%: .563

Andy Van Slyke (.324/14/89) led the National League with 45 doubles and 199 base knocks while accruing a team-high 35 Win Shares. Van Slyke collected his fifth consecutive Gold Glove Award and placed fourth in the NL MVP balloting. In his second full season Ray Lankford (.293/20/86) nabbed 42 bags and established a career-high with 40 doubles. Terry Pendleton replicated the output from his MVP campaign in ’91, posting a .311 BA with 21 blasts and 105 ribbies. He delivered a League-leading 199 safeties, made his lone All-Star appearance and earned runner-up status in the MVP vote. Lance “One Dog” Johnson swiped 41 bases and topped the circuit with 12 triples. Mike Perez (9-3, 1.84) and Todd Worrell (5-3, 2.11) anchored the bullpen corps.

On Deck

The “Original” 1992 Padres

References and Resources

Baseball America – Executive Database

Baseball-Reference

James, Bill. The New Bill James Historical Baseball Abstract. New York, NY.: The Free Press, 2001. Print.

James, Bill, with Jim Henzler. Win Shares. Morton Grove, Ill.: STATS, 2002. Print.

Retrosheet – Transactions Database

Seamheads – Baseball Gauge

Sean Lahman Baseball Archive