MLB’s Qualifying Offer: A King’s Ransom

With the MLB draft just past, I thought it would be appropriate to examine one of the most controversial topics surrounding the draft: the qualifying offer. Essentially, the qualifying offer intends to reward teams — presumably the small-market, low budget ones — that lose players in free agency. This reward comes in the form of an additional first-round draft pick for every player that signs with another team.

Only it isn’t that simple. Once a player reaches the end of his contract, the team can decide whether or not to offer the player a 1-year extension known as the qualifying offer. This new contract is equal to the average of the highest 125 salaries in MLB ($15.8 million in 2016). The player then chooses to either accept the qualifying offer or decline it — and thus, enter free agency with the assumption that he can earn more than a 1-year, $15.8 million contract. Once the player signs on with another team, his former team is awarded a first-round draft pick (to go along with the one(s) they already have, assuming they do) as compensation. Additionally, the player’s new team loses their first-round pick in the draft so long as it is outside the top 10 (in which case their second-round pick would be forfeited).

So, one would assume that, more often than not, a small-market team with a low payroll would benefit from this system. A budding star player reaches the end of his contract and commands a new contract worth hundreds of millions and spread over 5+ seasons. His current team does not have the financial resources to resign him, and another big-market team does. The cash-strapped team receives an additional first-round pick as compensation, while his new team willfully forfeits its first-round pick in exchange for his services over the next half-decade. And that’s that.

Not quite. I went back over the draft order for every year since 2013 (when the qualifying offer was first introduced) and summed the number of draft picks gained and lost. Results are shown below. I sorted the teams by their average payroll over the span in descending order. As you can see, the compensation is not in line with the assumption I presented above. In any way you shape it, the high-payroll teams are the ones benefiting from the current system. The 10 highest-payroll teams have received 19 additional draft picks over the four seasons — highlighted by the Cardinals who have gained four and lost none. The 10 teams with the lowest payrolls have received eight additional picks. The high payroll teams have a net draft pick gain of four, while the low payroll teams have a net loss of two.

Screen Shot 2016-05-29 at 5.27.18 PM

Now, I’m not coming up with any revolutionary solutions here — I’m not that smart and I don’t get paid enough. I am simply presenting data that supports that MLB’s current free-agent compensation system doesn’t benefit the teams that need it the most. In fact, this seems to be a story of “the rich are getting richer” — big-money teams are receiving the extra draft picks that were seemingly meant for the low-budget ones. Maybe MLB scraps the compensation system altogether, maybe they extend the time frame for when a player can accept the qualifying offer (they currently have seven days), or maybe they come up with some other solution. In any case, the current CBA ends after the 2016 season so us fans will likely know the answer before next year’s draft.


Buying or Selling Carlos Gomez

What are you to do with a former fantasy superstar who hasn’t lived up to expectations? For some, the answer’s easy; Carlos Gomez has already been dropped in over 25% of leagues on both ESPN and Yahoo.

Now that I’ve driven half my audience away with my use of a semicolon, let’s start the real analysis. Gomez certainly disappointed his owners through the first month and change of the season, sporting a minuscule .486 OPS through May 15 before being placed on the DL. For reference, out of 324 batters with at least 100 plate appearances, just two (2) have a lower OPS as of June 24. Both are on the Braves (one hit fifth in the lineup as recently as June 21, while the other has batted second 13 times this season).

So yes, one could see why owners would have lost patience with Gomez. But this was also a player who hit 66 home runs and stole 111 bases while hitting .277 between 2012 and 2014. If anyone deserved patience, it was him.

So when he hit two home runs in his first six games back from the DL, it was hard to be too surprised. Since then, he’s put together five multi-hit performances, and has brought his season line back up to at least non-Atlanta-ish numbers.

While it’s obviously a small sample size, Gomez’s 76 plate appearances in 19 games since his return have shown immense improvement over his horrendous start to the season. To demonstrate this, take a look at each of the different areas in which he’s bounced back:

Plate Discipline
2012-2014 April 5 – May 15 May 31 – June 24
BB% 6.2% 5.3% 10.5%
K% 22.8% 34.8% 30.3%
BB/K .27 .15 .35
SwStr% 13.9% 19.4% 16.7%
O-Contact% 59.5% 42.4% 45.9%
Z-Contact% 84.4% 74.4% 80.5%
O-Swing% 37.4% 32.1% 35.7%
Z-Swing% 79.3% 79.9% 65.8%

I could bring up more player comparisons and show you just how bad the Atlanta Braves are this year, but that’s not the point of this article. Instead, let’s just focus on Gomez’s numbers and how they compare to earlier in the year and during his prime years. He’s nearly doubled his walk rate while striking out more than 10% less often than before, leading to a BB/K that is no longer painful to look at. He’s missing less frequently on pitches he swings at, both in and out of the zone, and has fewer swings-and-misses as a result. The one worrisome spot here is his swing rates, where the trend is the opposite of what we’d generally expect when we see favorable results. However, his O-Swing% is still lower than it was between 2012 and 2014, and it seems as though swinging less at pitches in the zone is leading to more walks and less bad contact, so it’s not truly a terrible result.

Batting and Power
2012-2014 April 5 – May 15 May 31 – June 24
AVG .277 .182 .294
BABIP .329 .293 .405
OBP .336 .238 .368
SLG .483 .248 .471
ISO .206 .066 .176
OPS .819 .486 .839
wOBA .356 .216 .364
wRC+ 123 28 129
HR/FB% 14.6% 0.0% 33.3%

I already referenced Gomez’s OPS above, but it’s still almost unbelievable to see that his post-injury slugging percentage is nearly as high as his OPS once was. Besides that, there’s improvement across the board. His average is up over 100 points, as his OBP, SLG, ISO, OPS, and wOBA. He’s gone from being 70% worse than the average hitter to 30% better. What’s good to see her is that he’s not outpacing any of his career stats by a noticeable amount — an indication that his current run is very much sustainable. Okay, maybe not the .385 BABIP, but as you’ll see next, keeping it over .300 shouldn’t be an issue.

Batted Ball Breakdown
2012-2014 April 5 – May 15 May 31 – June 24
GB% 39.3% 47.1% 44.2%
FB% 40.6% 35.7% 20.9%
LD% 20.1% 17.1% 34.9%
Pull% 42.7% 36.4% 62.2%
Cent% 33.9% 41.6% 13.3%
Oppo% 23.5% 22.1% 24.4%
Soft% 16.7% 29.9% 31.1%
Med% 48.0% 45.5% 28.9%
Hard% 35.3% 24.7% 40.0%

Let’s take this one at a time. First, Gomez has seen a drastic increase in his line-drive percentage, unfortunately at the expense of hitting fewer fly balls. While it’d be better to see him hit fewer ground balls and get some more balls in the air, he’s certainly making this approach work for him right now. He won’t hit 30 home runs with this approach, but with the increased line drives, he should have no problem continuing to hit for extra bases.

Then comes the confusing part. He’s increased both the percentages of balls he hits to the pull side and opposite of the field, now hitting just 13.3% of his balls to center. He was definitely spraying the ball better beforehand, although the bloated Pull% will undoubtedly help him to put up some better power numbers. If the numbers stay in this region, I’d definitely expect his BABIP to regress, but it’s more likely that they regress closer to his career norms. A lot of those pulled balls will end up going to center field.

Finally, there’s the stuff that’s easy to analyze. Hit the ball harder, get better results. Gomez apparently believes in that approach as well, now hitting the ball hard over a third of the time and showing over a 50% increase from his previous rate. He needs to work on hitting the ball soft less often, which should happen if he continues to be selective and wait for his pitch.

Statcast Data
2015 April 5 – May 15 May 31 – June 24
Exit Velocity (mph) 88.5 84.8 86.4
Exit Velocity on Line Drives and Fly Balls (mph) 92.7 91.2 96.4
Fly Ball Distance (feet) 315.2 309 359

Ah, Statcast. What would we do without your infinite wealth of knowledge? The data here was obtained through Baseball Savant, and confirms that Gomez is indeed hitting the ball harder than he was before his injury. His overall average exit velocity remains low, but his velocity on line drives and fly balls is actually higher than it was last year. He can hit all the slow ground balls he wants and still be successful, provided he can keep up this increased velocity on balls in the air. Of course, he’s not going to continue hitting his fly balls over 350 feet — that’s reserved for people like Byung Ho Park (and apparently Tyler Naquin?). But he’s at 323 feet for the season now, and which should easily suffice for him to begin putting up some rejuvenated power numbers.

If you’re looking for a tl;dr, here it is: Carlos Gomez is performing much better than he was earlier in the season. He’s taking more walks, striking out less, making more contact, and hitting the ball harder and farther (further?). It’s obviously a small sample size, and he may not put up another 20/40 season, but he’s more than capable of hitting 10 home runs and stealing 15 bases the rest of the way. While it’s not elite production, it’d be better than he did last year, which would be quite an achievement after his start to the season.


A (Robbie) Ray of Hope for the D-Backs?

At this moment, the Arizona Diamondbacks, those same Diamondbacks who went into “win now mode” this offseason, currently sit in fourth place in the NL West division. A few weeks ago, Dave Cameron wrote an excellent article about what direction the D-Backs can go from here. The D-Backs’ pitching has specifically underwhelmed this year. However, one starter on their roster stands out to me, one who was not much more than an afterthought on their staff at the beginning of this year. That man is Robbie Ray.  He has a 10.4 K/9! That’s good enough for ninth in the majors among qualified starting pitchers — ahead of Madison Bumgarner, David Price, and Jake Arrieta (to name a few). He struck out eight guys in five innings his last time out. But, his ERA sits at an unimpressive 4.59. What’s up with Robbie Ray? Let’s take a look.

Let’s start with his four-seam fastball. Its velocity has risen each season since he first came up in 2014. He’s topped out at 97.6 this year — great for a lefty. He averages 93.6 on the heater, which is harder than all other qualified lefties this season. Its swinging-strike rate has gone from 7.1% last year to 8.3% this year — a very high SwStr% for a fastball. The pitch even has a bit of arm-side run and added backspin, giving it a “rising” appearance. He throws his fastball 59.6% of the time (third-highest in the majors), and for good reason.

His slider is solid. Hitters are managing a meager .570 OPS against it. It has an 18.4% SwStr%, up 0.3% from last year. Here is a wonderful gif of Ray striking Andrew McCutchen with the slider. And him striking out McCutchen again. Not to mention, the pitch is generating a whopping 68% groundball rate this season.

So both the fastball and slider are solid pitches. But here is where Ray runs into some trouble: his two-seamer is mediocre and his changeup is awful.

He throws the two-seamer hard, and consequentially, it has less movement than average. It has slightly more movement than his four-seamer, but otherwise, it’s just a slower version of the four-seamer with much less “rise”. Last year, it did generate a solid 54% GB%, but this year, that number has dropped to 45%. Hitters are mashing it to the tune of a .962 OPS this season, though last year they only managed a .729 OPS in a similar sample size. That being said, the SwStr% of the pitch has jumped from 6.1% last year to 7.1% this year, probably because his improved fastball and slider help to set it up better.

The changeup is awful: hitters currently have a 1.437 OPS against it this year. But, last year, hitters only had a .662 OPS in a similar sample size. He has trouble commanding this pitch, especially: he throws it for a strike only 53% of the time. However, there is some good news: the SwStr% has almost doubled, going from 4.6% to 8.5%.

Having examined Ray’s repertoire, I have a couple of predictive theories. Firstly, his HR/FB ratio is an exceedingly high 16.7%. This is well above the league average and his career rate of 10.9%. According to park factors on ESPN and FanGraphs, Chase Field is at least in the top five in terms of worst parks for pitchers, so that could explain some of this. He also over-performed with a 7.3% HR/FB rate last year, and maybe this is just regression coming in. Either way, I think that this rate should certainly improve through the rest of the season, settling in closer to his career average rather than 16.7%. Unsurprisingly, the changeup is the main culprit here; it has a 100% (!) HR/FB rate. This should almost certainly regress, which would bring his “OPS against” on the changeup back down.

Something else of note is that the changeup and two-seam fastball are weapons primarily deployed against batters of the opposite handedness, as they would move away from the batter. Since these are Ray’s two poorest pitches, it makes sense that he struggles to get right-handed batters out. They have a .875 OPS against him, compared to the meager .590 OPS that lefties manage. The changeup and/or two-seamer need to improve for Ray to start getting right-handers out. These two pitches have been hit hard, and have thus helped to make Ray’s BABIP climb up to .350. The BABIP against his changeup is .476, and against his two-seamer it’s .421.

One last thing that should not be discarded is that Ray’s walk rate has risen this year. Poor command of his pitches has resulted in him leaving a few meatballs over the plate. The fact that he only throws his changeup for a strike 53% of the time is specifically a major detriment to his control; the rest of his pitches are at least at 60% or higher.

So, Ray’s HR/FB rate should at least regress a bit, and I think that he can get his ERA under 4 for this reason alone. Roll with the Steamer projections for the rest of his season over ZiPS, but keep in mind neither projection system knows everything of Ray’s velocity increase and improved SwStr%, so it’s entirely possible that he can do even better, maybe even sustaining a 10 K/9, especially if he can improve his command and work on his changeup and two-seam. To sum it all up, the SwStr% has improved on all of Ray’s pitches, and there’s room for improvement yet; he’s only 24 years old.


Jake Fishman On His Draft Process, Gaining Velocity, and Spin vs. Location

The MLB draft was about two weeks ago and the Blue Jays selected a lefty out of Division 3 Union College in the 30th round. At first blush, a pick like this sounds like when a team selects a notable name like football star Russell Wilson for some good publicity. The selection might lead you to believe that Jake Fishman is a little crafty lefty who tosses batting-practice fastballs.

Well, not exactly. Jake Fishman was the top pitching prospect in all of Division 3 heading into the year, and he finished his 2016 collegiate season with a 0.41 ERA and 85 strikeouts in 66 innings, while regularly running his fastball up into the 90s. The 6’3 lefty was heading to play in the Cape Cod League this summer before the Blue Jays plucked him, signed him, and started him down a whirlwind that hopefully ends in big-league success.

Over the last few days, Jake has been kind enough to exchange emails with me. We covered his draft process, adjusting to pro ball, some of his theories on pitching, and tardigrades. I’ll be rooting for Jake, even as a proud Vassar Baseball alum. He’s a nice guy, a good story, and clearly a hard worker. Enjoy the interview.

 

SM: I saw that you just signed, so Congrats! Vassar coach Jon Martin is probably happy with that decision. How did that process work? Can you walk me through the decision making that lead to signing and foregoing your senior year? Union College is a good school with a good reputation.

Jake:  Thank you! The draft process is definitely hectic. For me, it was difficult to understand because I come from a family with no professional athletes and I went to a school where nobody has been drafted for baseball. Everything was new for us. So when scouts started to come around, my family and I started reaching out to anybody we could talk to that had gone through the process to get info on it. Eventually as the season progressed, a lot more teams reached out and watched me pitch. This went on until my season ended and we accumulated a hand full of teams that we could tell were more interested than the rest. I was invited to a few pre-draft workouts so I drove out and pitched for a couple teams before the draft.

When we finally reached the draft, we were waiting to hear (from) anybody. At the beginning of day 3 we got two phone calls from the Reds and the Blue Jays. I could have gone as early as the 10th round, but rounds 10-20 flew by very quickly and we hadn’t heard anything. I knew from the start that you can’t trust what the scouts tell you, but after round 20 hit I started to get really nervous.

The Blue Jays reached out again and said I was still on their draft board and they were thinking of taking me, while the Reds told us I would be a very late pick if they were to take me, and then they would watch me pitch in the Cape League to see how I did. Finally, when I was at the point of thinking I wasn’t going to get taken, the Blue Jays took me in the 30th round. It was the best feeling in the world.

Even though I went in the 30th round, they gave me a very reasonable offer for a kid like me. I expressed to the Blue Jays how important school was to me, and they offered to pay for my entire senior year of school. Tuition for next year is $65,000. If they didn’t offer to pay for school, I wouldn’t have signed. That was my biggest requirement. Before the draft, I spoke with my Dad so we could agree on a number. If push came to shove, I would accept a $50k signing bonus and all of school.

In the end, I was beyond happy with the offer they gave me because I had a lot of friends who are phenomenal players that didn’t get selected in the draft. I also think for the best opportunity to make it to the major leagues, I should start my career as soon as possible. As a deceptive lefty, there’s a chance I can move up the ranks fast, so if I have a great year in the minor leagues, they may look at me and say “let’s challenge this kid” and I would move up fast. And of course the Blue Jays were encouraging about getting me back to school in the fall to work towards finishing my degree. They might send me to a fall instructional league, but if they don’t then the timing works out perfectly with Union’s trimesters for me to get a fall term in before spring training starts.

 

SM: Okay that all seems to make a surprising amount of sense. I know that’s a nerve-racking process. I had a friend who actually went undrafted following his senior year after thinking he’d be picked up, and then wound up signing with the Yankees and has worked his way to high-A and is pitching well there, so draft position really isn’t all that important.  My buddy Max actually wrote about Yankees’ farmhand Matt Marsh here and I did a follow up about the success he’s enjoying so far in 2016

Anyway, your approach to the draft seems to align with the analytic approach I gleaned from your blog on pitching mechanics. You seem to have some strong opinions on pitching that have definitely helped you improve velo. So I guess two questions:

1) How’d you go from 84-86 as a freshman to 92 as a junior? A whole lot of us never make that jump.

2) You’re going to have a whole lot of new coaches and new perspectives. The Liberty League and [Union Head Coach] Paul Mounds are used to your kind of “heady” player. How are you going to handle it if the Jays make some adjustments to your mechanics or repertoire that don’t really make sense to you?

I tend to take an analytical approach with most things (except when I’m on the mound). But you’re definitely right about me having some strong opinions about pitching. I think that if somebody finds something that works for them, they should stick with it.

1) The big jump I made was from freshman to sophomore season in velocity. I put on 20 pounds and my strength shot through the roof. I’d always been a pretty fast kid, but I was scrawny. When I put on the weight I got bigger, stronger, faster and the velo followed.

I was around 88-90 my sophomore year (as long as it was warm), but I was a little shaky on the mound. It felt almost as if I had hit another big growth spurt and I didn’t have pinpoint control of my body. It took me until the summer, where I pitched for the Brockton Rox (of the collegiate summer league FCBL), to figure out my mechanics again. From then I’ve maintained my weight and kept my control. It’s been smooth sailing ever since then and I picked up a mph or two just from adding strength over this year.

2) It’s funny to me that you bring that up. The past three years, Coach Mound has accepted that I have my own philosophy behind the stuff I do and he was very open to letting me follow my routine. High school was the same way. The commonalities between the two is that I was pitching well. As long as I do well, my coaches have stayed away from changing me mechanically and philosophically. From what I can tell, the Blue Jays follow the same approach. After listening to our pitching coordinator here, he has been discussing a lot about his philosophies and what the ideal pitchers have done to make it to the big leagues. He’s been making suggestions to us that he thinks will help us. He doesn’t expect us to change, but if we start pitching poorly those suggestions are gonna have to be worked into our routine. So my take on that is I’ll just keep pitching well and there shouldn’t be an issue.

 

SM:  It should be interesting to see how that plays out. I know different organizations tend to have different philosophies on how their pitchers should conduct themselves. Was it Daisuke Matsuzaka who threw 300-foot long toss between starts? That got shut down quickly by the Red Sox.

I also noticed that you had 5 unearned runs this year. How many of those were legit unearned? Did your ERA benefit from some friendly scorekeeping?

Yeah they shut down a lot of the stuff Matsuzaka did that seemed unusual for baseball in the United States. For now, they are just encouraging us to just go out there and pitch our game so they can see what we have and make adjustments from there.

Thinking back, maybe one of those unearned runs could be scored as an earned run. But at the same time, one of my earned runs could have turned out as unearned, so I think in the end it’s balanced itself out.

 

SM:  Yeah, it’s just interesting to think about the difference between really good and great. I guess that difference gets that much tighter in affiliated ball.

I saw an awesome interview with Lance McCullers that really felt like a new-age way of thinking about attacking hitters. I’d love to hear your reaction to his theory of emphasizing spin over movement and velocity.

Jake: It really does. We got to see some big leaguers a couple days ago who were recovering. They threw an inning to our drafted position players and you could tell there was a difference but it’s such a small one. Everything’s just a little bit tighter.

I like his approach. As a former hitter in college, I can relate to what he’s talking about in terms of picking up the spin on the ball. Not being able to see the spin was what beat me most. It’s definitely new-age now that we can pick up spin rates of the ball and I think it can be an extremely useful tool to use.

I like his view on a lot of things he mentions in his interview like adjusting to the hitters’ mentalities whether they are being aggressive or patient at the plate and his changeup (because that’s how I throw my changeup). But at the same time, I think location of the pitch is just as important. Or maybe I should say it’s another way to fool the batter in combination of spin. I can see having spin rate as a priority though, because if you can’t see the spin you don’t know where the ball is going.

 

SM Exactly. Well I’m sure the Blue Jays will get some spin reads on you and you can start to use that information to your advantage.

Thanks so much for the exchange of emails. We’re definitely be looking out for you and I will likely reach back out in the offseason to see how things are going.

Now, it’s time for the rapid fire all-important questions. You must answer honestly and you’re only allowed to provide explanation for 2. No clarification from me of any kind will be provided.

  • Which Pokemon game was the best: red, blue, gold or silver?

Gold. Because you can go back to the Kanto region and Ho-oh is badass.

 

  • Who wins in a fight to the death, assuming both parties are savage, LeBron James or 1,000 kindergardeners?

1,000 kindergardeners

 

Yes.

 

  • How tall is the average tree?

20 feet.

 

  • True or False: Vassar’s coach Jon Martin resembles a Tardigrade.

I love this. True.

 

  • Would you ride a polar bear if it asked you to?

Depends. What kind of drugs am I tripping on?

 

  • Why are you afraid of heights?

I’m not.

 

  • What’s your favorite flavor of chocolate ice cream?

Chocolate chip cookie dough

 

  • In a game of horse against a horse, don’t you automatically win?

Ah here we go again. The classic horse vs. a horse example.  Everybody makes this mistake: you actually automatically lose.

 

  •  Is a hot dog a sandwich?

It has bread.  And meat in the middle.  Gotta say yes.


Lineup Construction is Changing

Lineup construction is a topic that comes up far more often in proportion to how important it is. But if you can save a few runs in a year by using the proper lineup, it’s worth it. Put your OBP up top, not your steals. The #2 hitter should be better than your #3.

With 14 going on 15 years of lineup splits available on FanGraphs, are any trends clear? Yes, actually. In regards to the two specific issues above, managers do seem to be getting better. Let’s explore. (Note: All “league averages” are non-pitchers. Pitchers aren’t real hitters, after all.)

The on-base percentage of leadoff hitters vs. the league average has climbed. In 2002, the league average OBP was .336 whereas it was just .332 for leadoff hitters. Ten years later, in 2012, league average was .324 but leadoff hitters hit .344. The gap has begun to decline since then, but the trend is still apparent, and in 2016 leadoff hitters have a .332 OBP vs. the league’s .324. Overall, here’s a simple chart of the league’s leadoff OBP minus the overall average OBP for each year since 2002:

Not everyone has caught on; either Dusty Baker or Ben Revere really need to figure things out soon for the Nationals, for example. But leadoff hitters are getting better at getting on base.

Meanwhile, managers have a longer way to go in their understanding of the fact that a #3 hitter will most often find themselves batting with the bases empty and two outs which, naturally, is not a good situation for scoring runs. However, just by comparing the wRC+ of the league’s #2 and #3 hitters shows that some teams are learning. In the dark days of 2002, #2 hitters had a wRC+ of 92, compared to 128 for #3 hitters. Since then, #2 hitters haven’t been that bad, but they haven’t been great, either. However, the last three years have been #2 hitters’ most productive since 2002: they had a 102 wRC+ in 2014, 107 in 2015, and currently a 105 in 2016. Teams haven’t moved their best hitters out of the three hole (this will be #3 hitters’ seventh straight year with a wRC+ of 120 or better), but they are starting to see the value of a good #2 hitter. This has led to the wRC+ gap between #2 and #3 hitters to exhibit a clear downward trend since 2002:

 

Even if you take out that 2002 season, the trend holds. It is still basically due to a change in the past two years, but the more hitters like Andrew McCutchen or Manny Machado, Corey Seager or George Springer bat in that second spot in the order and have success, the more we can expect out of the two hole. A lot of these #2 hitters, you might note, are young guys with a lot of career ahead of them with their current teams. It’s up to managers to keep them at #2 instead of moving them to #3 as these players continue in their careers. They may not, leaving 2015 and 2016 as anomalies so I can be wrong again. (Actually, I’m never wrong, because where’s the fun in that?)

But next time you lament the general failures of managers to put out the correct lineup, remember, things are getting better. Maybe it’s just your favorite team’s manager.


Hardball Retrospective – What Might Have Been – The “Original” 1984 Giants

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. 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 teams with the biggest single-season difference in the WAR and Win Shares for the “Original” vs. “Actual” rosters for every Major League organization. “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. Supplemental Statistics, Charts and Graphs along with 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

AWAR – Wins Above Replacement for players on “actual” teams

AWS – Win Shares for players on “actual” teams

APW% – Pythagorean Won-Loss record for the “actual” teams

Assessment

The 1984 San Francisco Giants 

OWAR: 42.9     OWS: 294     OPW%: .508     (82-80)

AWAR: 27.7      AWS: 198     APW%: .407     (66-96)

WARdiff: 15.2                        WSdiff: 96  

The “Original” 1984 Giants ended the season with a winning record but merely earned a fifth place finish, 9 games behind the Astros. Gary “Sarge” Matthews established a career-best with 101 runs scored while pacing the circuit with 103 walks and a .410 OBP. Chili Davis contributed a .315 BA and merited his first All-Star invitation. Dave “Kong” Kingman walloped 35 four-baggers and knocked in a personal-best 118 baserunners. Bob Brenly achieved his lone All-Star nod with a .291 BA, 20 dingers and 80 ribbies. Jack Clark supplied a .320 BA with 11 long balls prior to a season-ending injury in mid-June. Dan “Dazzle” Gladden ignited the offense following his recall from the minor leagues in late June, posting a .351 BA and swiping 31 bags.

Jack Clark is ranked 27th among right fielders according to Bill James in “The New Bill James Historical Baseball Abstract.” “Original” Giants teammates listed in the “NBJHBA” top 100 rankings include George Foster (34th-LF), Gary Matthews (46th-LF), Garry Maddox (56th-CF), Chili Davis (64th-RF), Chris Speier (68th-SS) and Dave Kingman (98th-LF).  Al Oliver (31th-CF), Manny Trillo (49th-2B) and Dusty Baker (54th-LF) make the register for the “Actual” Giants. 

  Original 1984 Giants                              Actual 1984 Giants

LINEUP POS OWAR OWS LINEUP POS AWAR AWS
Gary Matthews LF 2.68 22.93 Jeffrey Leonard LF 2.38 20.37
Dan Gladden CF 2.81 16.46 Dan Gladden CF 2.81 16.46
Chili Davis RF/CF 4.19 21.58 Chili Davis RF/CF 4.19 21.58
John Rabb 1B -0.14 1.01 Scot Thompson 1B 0.35 6.89
2B Manny Trillo 2B 0.76 8.83
Johnnie LeMaster SS -0.47 7.23 Johnnie LeMaster SS -0.47 7.23
Chris Brown 3B 0.31 2.26 Joel Youngblood 3B -0.89 9.5
Bob Brenly C 3.58 21.32 Bob Brenly C 3.58 21.32
BENCH POS OWAR OWS BENCH POS AWAR AWS
Dave Kingman DH 2.49 21.48 Jack Clark RF 2.01 11.84
George Foster LF 1.16 18.27 Dusty Baker RF 1.19 8.81
Jack Clark RF 2.01 11.84 Al Oliver 1B -0.85 6.56
Bob Kearney C 0.26 8.63 Steve Nicosia C 0.79 4.99
Garry Maddox CF 0.53 6.67 Brad Wellman 2B -0.45 3.74
Chris Speier SS -0.24 2.96 Chris Brown 3B 0.31 2.26
Rob Deer LF 0.28 1.24 Fran Mullins 3B 0.24 2.08
Randy Gomez C -0.02 0.18 Gene Richards LF -0.04 1.92
Tom O’Malley 3B -0.5 0.03 Rob Deer LF 0.28 1.24
Jose Morales -0.19 0 John Rabb 1B -0.14 1.01
Casey Parsons -0.01 0 Duane Kuiper 2B -1.06 0.82
Randy Gomez C -0.02 0.18
Joe Pittman SS -0.17 0.12
Alejandro Sanchez RF -0.4 0.08
Tom O’Malley 3B -0.29 0.01

Bob Knepper rebounded from an 11-28 mark in the previous two campaigns to achieve a 15-10 record with a 3.20 ERA and 1.190 WHIP. Gary Lavelle notched 12 saves and fashioned a 2.76 ERA as the primary closer. Frank Williams collected 9 victories in a long relief role during his rookie year.

  Original 1984 Giants                                   Actual 1984 Giants

ROTATION POS OWAR OWS ROTATION POS AWAR AWS
Bob Knepper SP 2.16 12.43 Bill Laskey SP -0.02 4.8
Pete Falcone SP 0.91 5.33 Mike Krukow SP -1.04 3.94
John Montefusco SP 0.58 3.27 Jeff D. Robinson SP -0.67 2.84
Jeff D. Robinson SP -0.67 2.84 Atlee Hammaker SP 0.96 2.28
Mark Calvert SP -0.39 0.22 George Riley SP 0.19 0.98
BULLPEN POS OWAR OWS BULLPEN POS AWAR AWS
Gary Lavelle RP 1.78 7.85 Gary Lavelle RP 1.78 7.85
Frank Williams RP 0.43 5.7 Greg Minton RP -0.02 6.29
John Henry Johnson RP 1.22 4.39 Frank Williams RP 0.43 5.7
Scott Garrelts SW -1.13 0 Randy Lerch RP 0.11 2.58
Gorman Heimueller RP -0.7 0 Bob Lacey RP -0.07 1.51
Mark Grant SP -1.1 0 Renie Martin RP -0.09 0.99
Mark Calvert SP -0.39 0.22
Mark W. Davis SP -1.91 0.18
Jeff Cornell RP -1.25 0
Scott Garrelts SW -1.13 0
Mark Grant SP -1.1 0

Notable Transactions

Gary Matthews

November 17, 1976: Signed as a Free Agent with the Atlanta Braves.

March 25, 1981: Traded by the Atlanta Braves to the Philadelphia Phillies for Bob Walk.

March 26, 1984: Traded by the Philadelphia Phillies with Porfi Altamirano and Bob Dernier to the Chicago Cubs for Bill Campbell and Mike Diaz.

Dave Kingman

February 28, 1975: Purchased by the New York Mets from the San Francisco Giants for $150,000.

June 15, 1977: Traded by the New York Mets to the San Diego Padres for Paul Siebert and Bobby Valentine.

September 6, 1977: Selected off waivers by the California Angels from the San Diego Padres.

September 15, 1977: Traded by the California Angels to the New York Yankees for Randy Stein and cash.

November 2, 1977: Granted Free Agency.

November 30, 1977: Signed as a Free Agent with the Chicago Cubs.

February 28, 1981: Traded by the Chicago Cubs to the New York Mets for Steve Henderson and cash.

January 30, 1984: Released by the New York Mets.

March 29, 1984: Signed as a Free Agent with the Oakland Athletics.

George Foster

May 29, 1971: Traded by the San Francisco Giants to the Cincinnati Reds for Frank Duffy and Vern Geishert.

February 10, 1982: Traded by the Cincinnati Reds to the New York Mets for Greg Harris, Jim Kern and Alex Trevino.

Bob Knepper

December 8, 1980: Traded by the San Francisco Giants with Chris Bourjos to the Houston Astros for Enos Cabell.

Honorable Mention

The 1906 New York Giants 

OWAR: 65.9     OWS: 361     OPW%: .591     (91-63)

AWAR: 50.8       AWS: 287      APW%: .632    (96-56)

WARdiff: 15.1                        WSdiff: 74

The New York Giants secured the organization’s fourth consecutive pennant in 1906 with a record of 91-63, placing three games in front of the St. Louis Cardinals. Third-sacker Art Devlin pilfered 54 bases and delivered a .299 BA. Harry H. Davis topped the leader boards with 12 big-flies and 96 ribbies. Converted outfielder Cy Seymour nabbed 29 bags and drove in 80 baserunners while “Wee” Willie Keeler batted .304 with 23 steals. Christy Mathewson furnished 22 victories along with a 2.97 ERA. Left-hander Hooks Wiltse recorded 16 wins with an ERA of 2.27 and a WHIP of 1.143.

On Deck

What Might Have Been – The “Original” 2004 Royals

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

The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at “www.retrosheet.org”.

Seamheads – Baseball Gauge

Sean Lahman Baseball Archive


Taking a Look at David Price’s Turnaround

After signing a massive seven-year, 217-million-dollar contract with the Red Sox this past offseason, David Price got off to a slow start. After his May 7th start against the Yankees in which he gave up six earned runs in just 4.2 innings, Price’s ERA stood at a whopping 6.75 yet his peripherals remained strong. He had a 2.98 FIP and 11.5 K/9. However, he was giving up hard contact over 41 percent of the time. The immediate fix was a mechanical issue noticed by Dustin Pedroia that was limiting Price’s leg lift and diminishing his velocity. Frustrated with his failures, Price vowed to be better.

And better he has been. After throwing a gem in Sunday’s win over the Mariners where he went eight innings allowing his only run on a solo shot by Franklin Gutierrez, Price lowered his season ERA to a still high 4.24 and had his eighth straight quality start. Over those eight starts, Price has been much better, allowing 16 runs over 58.1 innings for an ERA of 2.47. During this stretch, he has a 3.88 FIP and 8.6 K/9 and has only allowed hard contact around 27 percent of the time. Although his strikeouts have gone down and his FIP went up due to his decrease in strikeouts to go with an increase in home runs allowed, Price has limited the amount of hard contact he has given up. This can be seen in the BABIP over the two stretches. In his first seven starts, his BABIP against was around .370, while in this current eight-start stretch it is hovering around .230.

This in turn, has allowed him to be very successful while pitching to contact. His biggest issue remains his ability to keep the ball in the park. Over his last eight starts, Price has allowed at least one home run in seven of them. So while he has limited hard contact against him, the few mistakes that he makes each game are punished. Despite this increase in home runs allowed, he continues to pitch well and go deep into games, allowing the Red Sox bullpen a chance to recover after the consistently shaky starts from their 4th and 5th starters.

There are a few main reasons to this improvement. The first was his ability to regain his velocity. Looking at his velocity each month thanks to data from Brooks Baseball, there is a small but steady increase in his average four-seam and sinker velocity. Before May 8th, his velocity was low by his standards. Typically a pitcher averaging 94 to 95 MPH with his fastball, he had been sitting 93 MPH.

Year Fourseam Sinker Change Curve Cutter
2016, Before May 8th 93.2 93.0 84.3 78.8 88.8

Although just a small dip in velocity, it made him much more hittable.

Since May 8th, his velocity has been back on the rise.

Year Fourseam Sinker Change Curve Cutter
2016, Since May 8th 94.2 93.4 85.0 78.3 89.0

After the mechanical change, his four-seam has been averaging around 94 MPH and his sinker has been averaging around 93 MPH, but still slightly up from what it was before. Although it is a small increase, this added velocity has helped Price dominate hitters, gain confidence, and re-establish himself as an ace.

Another key factor in this improvement has been his pitch usage. Using pitch data from Brooks Baseball, I was able to look at Price’s pitch usage. In his first seven starts, Price relied on mixing different types of fastballs with his main offspeed pitch being a change-up while also displaying the occasional curve.

Year Fourseam Sinker Cutter Curve Change
2016, Before May 8th 27.6 22.6 19.8 6.6 23.4

His four-seam was used around 28 percent of the time yet it lacked the movement displayed by his cutter and sinker. The high four-seam usage to go with decreased velocity spelled trouble for Price.

However, since May 8th, Price has made an adjustment displayed by the fact that he is now using his sinker as his primary pitch while also using his four-seam far less frequently.

Year Fourseam Sinker Cutter Curve Change
2016, Since May 8th 9.0 36.1 22.4 8.3 24.3

His sinker is now used around 36 percent of the time compared to his four-seam being used around nine percent of the time. With this added movement and velocity, Price has been able to be more effective while keeping the use of his curve, cutter, and changeup around the same. This simple switch from a four-seam to a sinker has allowed him to go on a tear.

Looking forward, the Red Sox need Price to continue to be the pitcher that he has been over his last eight starts. They are paying him ace money and he is expected to pitch like one down the stretch as Boston hopes to continue their great turnaround year. If Price continues to have outings like these, the Sox should like their chances come October with him taking the mound with their season on the line.


Who Has Performed Better In the Draft?

The MLB draft has passed but its impact will last. Some selections will go down as busts (e.g. Matt Anderson by the Tigers in 1997). Others will be real bargains such as Carlos Beltran with the 49th pick in 1995. I decided to look at the numbers in an attempt to answer the following questions I read over the last few weeks:

  1. How many Round 1 picks do end up in the big leagues? What’s the average impact of a Round 1 pick? How does that compare to Round 2? Are there differences between pitcher and batters?
  2. What has been the best draft class for the 1993-2008 period? (per three first rounds)
  3. What teams have done a better job?
  4. What is the best round (top 10 overall picks)?

As I usually do, let’s define the data sources and assumptions. First, my data source is Baseball-Reference. There are many assumptions and disclaimers in this process, but the most important ones are:

  1. I am using data from 1993 to 2008 to give ample time for players to reach MLB. As I am using career WAR, I don’t want to over-penalize players that have been selected in the recent years and therefore have not accumulated MLB service time.
  2. Organizations change and so do their ways of conducting business, which evidently includes draft strategy. We are looking at teams rather than specific front offices or general managers.
  3. WAR refers to Baseball-Reference WAR (i.e. bWAR).
  4. Teams may have more than one pick per round due to compensation and supplemental picks.
  5. This methodology does not take into account the overall quality of the draft pool i.e. total WAR per draft year is not constant.
  6. All WAR is allocated to the team that drafts the player. Understandably, that is not true but let’s toy with the idea through this post.

Let’s get to it.

Question 1 – How many Round 1 picks do end up in the big league? What’s the average impact of a Round 1 compare to a Round 2 pick? Are there differences between pitcher and batters?

The table below outlines how many players have been/were called up to the majors and how many actually have had a positive career WAR i.e. over 0.0. I have also added the average career WAR per player and I have broken down the data by round and by position (pitcher and batter) to grasp the differences easily. Just take a moment with this table:

 

Round Pos Total players Players that reached MLB % of Total players Positive WAR % of players who reached MLB Average WAR per player
Round 1
Pitchers 372 242 65% 161 67% 9.7
Batters 320 225 70% 157 70% 14.4
Sub-Total 692 467 67% 318 68% 12.1
Round 2
Pitchers 247 121 49% 60 50% 8.1
Batters 244 127 52% 70 55% 13.1
Sub-Total 491 248 51% 130 52% 10.8
Round 3
Pitchers 244 99 41% 59 60% 5.5
Batters 235 88 37% 50 57% 7.3
Sub-Total 479 187 39% 109 58% 6.3
Total 1662 902 54% 557 62% 10.6

 

Three things come to my mind:

First, this provides some empirical validation of what we intuitively thought: First-round picks produce greater WAR values than the others. While I only have data for the first three rounds, it’s worth noting that the gap between Round 1 to Round 2 (10%) is smaller than from Round 2 to Round 3 (41%).

Second, I actually found surprising that 67% of first-rounders reached MLB at some point. That is two players out of three and it’s a testament to how important raw skills are when it comes to moving up through the minors.

Lastly, the answer to the question of whether t draft pitchers or batters looks like an easy one. Batters not only reached MLB at a higher pace but delivered better results as a group and as individuals. While these results are not statistically significant, they provide a pragmatic answer to the question and suggest a sound strategy might be to draft batters and trade for pitchers later down the road.

Question 2 – What has been the best draft class for the 1993-2008 period?

This table should provide guidance on how to answer this question but does not fully explain it. If we think of it as the number of players that got to MLB, then 2008 is the best year. That year highlights Eric Hosmer, Buster Posey, Brett Lawrie, Craig Kimbrel and Gerrit Cole as the most prominent stars, but offers a very low career total WAR as most of its players are still playing – they’re the youngest generation of my sample. In this class, 27 out of the top 30 picks have reached MLB, though a few for a very short stint e.g. Kyle Skipworth or Ethan Martin.

Year Total war Total players that reached MLB Average WAR per player
1993 476.3 54 8.82
1994 243.4 54 4.51
1995 484.9 41 11.83
1996 280.0 45 6.22
1997 409.5 59 6.94
1998 397.6 53 7.50
1999 402.1 52 7.73
2000 236.8 47 5.04
2001 350.9 55 6.38
2002 508.1 54 9.41
2003 297.1 60 4.95
2004 393.2 63 6.24
2005 458.1 63 7.27
2006 282.7 62 4.56
2007 325.4 69 4.72
2008 213.2 71 3.00

 

If we think of the highest total career WAR, then the winner is 2002. This class is led by two of the best picks on the sample (Zack Greinke and Joey Votto) but also features Prince Fielder, Jon Lester and Curtis Granderson. If we think of highest concentration of skills, then the 1995 class has to be the first one with an average of 11.8 WAR per MLB player. On the other hand, only 41 players got the MLB call, the lowest among the sample. While Carlos Beltran and Roy Halladay are the most notable names in that draft, player such as Darin Erstad, Kerry Wood, Randy Winn and Bronson Arroyo enjoyed nice peaks.

 

Question 3 – What teams have done a better job?

Evidently, not every team has selected in the same combination of draft slots e.g. some teams have had the opportunity to choose top picks (Rays, for example), while other have frequently picked from mid-bottom draft slots (Yankees).  It would not be fair to compare total career WAR for players the Yankees has selected against those that the Rays has because the latter had more options and access to a different pool of players than that the Yankees had. How to fix that? I am comparing what each team did on the overall pick they were slotted. If we use 2016 as an example, I would be comparing how good Philadelphia was in choosing Mickey Moniak as pick 1 against the average of all other first picks in the timeframe (1993-2008). Once I know the WAR gap between a particular team and the average WAR per pick, I need to standardize that number by the standard deviation i.e. calculating Z scores. In simple terms, this is understanding how good or bad a pick was in relation to the entire distribution of a particular draft slot. The Z-score number allows us to compare how good a 14th pick was in relation to a third pick, for example. Finally, to identify which teams have fared better, I am calculating the average of Z-scores for all picks.

Again, there are many caveats here, but this should give us a ballpark estimate on how well teams have drafted from 1993-2008. Keep in mind, this methodology does not produce a linear WAR per draft slot. That would mean, for example, that overall pick 4 will produce greater WAR than pick 5. On average, the 4th pick has produced 6.2 WAR on average, while the 5th one has produced 14.3. While this might be counter-intuitive (it is at least for me), the empirical evidence of this sample size shows that.

 

Batter Pitcher    
Teams # of batters drafted Average of OvPck – Zscore # Pitchers drafted Average of OvPck – Zscore Total Count of Name Total Average of OvPck – Zscore
Phillies 26 -0.81 24 -0.46 50 -0.64
Nationals 9 -0.70 6 -1.14 15 -0.88
Athletics 40 -0.99 30 -0.75 70 -0.89
Twins 34 -0.57 32 -1.31 66 -0.93
Diamondbacks 18 -0.84 26 -1.06 44 -0.97
Angels 18 -1.10 27 -0.88 45 -0.97
Rays 14 -0.50 20 -1.31 34 -0.97
Rangers 26 -1.06 28 -1.05 54 -1.06
Cardinals 28 -1.03 34 -1.25 62 -1.15
Giants 34 -1.23 28 -1.10 62 -1.17
Braves 32 -1.24 35 -1.12 67 -1.18
Royals 25 -1.40 32 -1.04 57 -1.20
White Sox 24 -0.65 40 -1.54 64 -1.20
Reds 28 -0.73 27 -1.70 55 -1.21
Blue Jays 32 -1.46 27 -0.91 59 -1.21
Red Sox 29 -1.33 35 -1.14 64 -1.23
Brewers 26 -0.87 27 -1.72 53 -1.30
Dodgers 21 -1.13 32 -1.44 53 -1.32
Rockies 18 -0.85 33 -1.60 51 -1.33
Pirates 27 -1.72 23 -0.88 50 -1.33
Mariners 25 -1.33 20 -1.45 45 -1.38
Mets 17 -1.14 35 -1.61 52 -1.45
Tigers 20 -0.81 32 -1.88 52 -1.46
Orioles 28 -1.05 28 -1.88 56 -1.46
Padres 40 -1.47 24 -1.54 64 -1.49
Marlins 30 -1.59 23 -1.41 53 -1.51
Astros 23 -1.45 26 -1.61 49 -1.53
Expos 26 -1.30 22 -1.85 48 -1.56
Yankees 24 -1.94 29 -1.37 53 -1.63
Cubs 24 -1.46 29 -1.95 53 -1.73
Indians 33 -2.13 29 -1.49 62 -1.83
Total 799 -1.19 863 -1.35 1662 -1.27

 

Perhaps surprisingly, the Phillies come at the top of the list. The Phillies advantage came in three picks: First, Chase Utley was drafted in 2000 with the high 15th pick and has had a great career that is up to 63.4 WAR. Second, in 1993, the Phillies chose Scott Rolen (70 career WAR) with the 46th overall pick – which seems like a bargain now. Finally, Randy Wolf in 1997 was selected in the 54th position and went on to have a 23.1 career WAR. The Nationals have had very much success on their first few years as a franchise with both Jordan Zimmermann and Ryan Zimmerman. The sample size does not include Bryce Harper or Stephen Strasburg, which may push the Nats to the top of the list in the near future.

Astros, Expos, Yankees, Cubs and Indians are the bottom five teams. Coincidentally or not, these teams have long droughts (Yankees exempted). Interesting to see if there is a relationship between draft performance and wins but I guess that’s is another post.

We could go and dig deeper for each team into what they’ve done well and not so much but that would not make sense. Teams make mistakes and it looks like the draft selection is pretty damn hard with an extremely high WAR standard deviation (11.6 WAR through the first 30 picks).

 

Question 4 – What is the best round (top 10 overall picks)?

This question is about finding the best selection on each of the first 10 picks. I’ve used the Z-score which pick was really ahead of the curve.

OvPck Year Tm Player Pos WAR Average WAR of pick OvPck – Zscore
1 1993 Mariners Alex Rodriguez SS 118.8  22.73 3.16
2 1997 Phillies J.D. Drew OF 44.9  16.23 1.88
3 2006 Rays Evan Longoria 3B 43.3  9.00 2.46
4 2005 Nationals Ryan Zimmerman 3B 34.8  6.21 2.67
5 2001 Rangers Mark Teixeira 3B 52.2  14.26 2.02
6 2002 Royals Zack Greinke SP 52.3  4.76 3.63
7 2006 Dodgers Clayton Kershaw SP 52.1  11.86 2.42
8 1995 Rockies Todd Helton 1B 61.2  6.41 3.56
9 1999 Athletics Barry Zito SP 32.6  8.70 2.24
10 1996 Athletics Eric Chavez 3B 37.4  11.31 2.04

 

Well, this is quite a nice group of players. A-Rod is the WAR leader of our sample. Even as a first pick, which on average has yielded the highest WAR, he manages to be three standards deviations above the mean. Five other players are active and two of them (Greinke and Kershaw) still are among the best starting pitchers in the game. They will continue to cement their position as great draft picks for the Royals and Dodgers. Interestingly enough, Barry Zito and Eric Chavez were part of the A’s Moneyball team that frequently over-performed a few years ago — a reminder of how important it is to build a strong core of players.

As a bonus question – these are the top 10 picks, according to this methodology:

Year OvPck Tm Player Pos WAR Drafted Out of OvPck – Zscore
2002 44 Reds Joey Votto C 42.7 Richview Collegiate Institute (Toronto ON) 3.74
2007 34 Reds Todd Frazier 3B 16.8 Rutgers the State University of New Jersey (New Brunswick NJ) 3.71
1997 70 Rockies Aaron Cook RHP 15.9 Hamilton HS (Hamilton OH) 3.71
1995 69 Pirates Bronson Arroyo RHP 26.5 Hernando HS (Brooksville FL) 3.67
1995 53 Indians Sean Casey 1B 16.3 University of Richmond (Richmond VA) 3.67
2007 27 Tigers Rick Porcello RHP 12.2 Seton Hall Preparatory School (West Orange NJ) 3.63
2002 6 Royals Zack Greinke RHP 52.3 Apopka HS (Apopka FL) 3.63
1996 18 Rangers R.A. Dickey RHP 21.1 University of Tennessee (Knoxville TN) 3.61
1997 91 Royals Jeremy Affeldt LHP 10.5 Northwest Christian HS (Spokane WA) 3.61
1995 31 Angels Jarrod Washburn LHP 28.5 University of Wisconsin at Oshkosh (Oshkosh WI) 3.60
1998 33 Expos Brad Wilkerson OF 11 University of Florida (Gainesville FL) 3.60
1995 49 Royals Carlos Beltran OF 68.8 Fernando Callejo HS (Manati PR) 3.59

 

As always, feel free to share your thoughts and comments in the section below or through our twitter account @imperfectgameb.

Note: This analysis is also featured in our emerging blog www.theimperfectgame.com


Zack Cozart Probably Won’t Keep Scorching the Ball

Last week, August Fagerstrom handed Cincinnati fans an ice-cold Gatorade after we’d spent the better part of three months wandering through the Sahara that is the 2016 Reds baseball season.

After quickly touching on the wide range of sadness, of which there is no shortage—the historically bad bullpen, the woeful luck of one Joseph Votto, and oh, the losses—he rationally pointed to a reason for optimism: “[The Reds’] two most encouraging comeback stories, Zack Cozart and Jay Bruce, just so happen to be their two most sensible trade chips.”

Of Cozart, he wrote:

He leads the Reds in WAR. He enters his final year of arbitration next season. He’s always been a gifted defensive shortstop, something every team loves to have, but this year, he’s hitting at career-best levels…He’s become more aggressive at the plate, he’s hitting way more balls in the air than he did early in his career, and he’s hitting them with authority (emphasis mine).

This last piece is what’s so interesting. Watch any Reds game this year—or just stay through the leadoff hitter! I swear, that’s all I’m asking!—and you’ll hear announcers remark that Cozart is just hitting the ball differently this year.

As shocking as it may seem given recent broadcaster rankings, they’re right.

Cozart’s 2016 hard-hit rate of 33% is very good, if not earth-shattering. It ranks seventh amongst shortstops, and league-wide places him in the company of (slightly) more celebrated offensive names like Bogaerts, Kinsler, and Beltre.

But there’s a caveat to Cozart’s great contact. The number isn’t just a career high; it’s a massive outlier, sitting 8.5% above his career average. How many other hitters this year are enjoying similar spikes? I pulled all “jumps” above six points for 2016 qualified hitters, with a minimum of four seasons to ensure a stable career average:

Name Team Age 2016 Hard Hit % Career Hard Hit % “Jump”
Jose Altuve Astros 26 34.2% 24.5% 9.7%
Daniel Murphy Nationals 31 38.2% 28.7% 9.5%
Victor Martinez Tigers 37 41.5% 32.3% 9.2%
Matt Carpenter Cardinals 30 43.6% 34.7% 8.9%
Zack Cozart Reds 30 33.0% 24.5% 8.5%
Buster Posey Giants 29 40.8% 33.1% 7.7%
Joey Votto Reds 32 44.4% 37.0% 7.4%
Curtis Granderson Mets 35 40.2% 33.1% 7.1%
Salvador Perez Royals 26 35.6% 28.5% 7.1%
Chase Utley Dodgers 37 41.9% 35.3% 6.6%
Ben Zobrist Cubs 35 36.0% 29.4% 6.6%
David Ortiz Red Sox 40 46.9% 40.3% 6.6%
Josh Donaldson Blue Jays 30 40.5% 34.0% 6.5%
Yoenis Cespedes Mets 30 39.5% 33.2% 6.3%
Evan Longoria Rays 30 40.7% 34.6% 6.1%

This list shouldn’t be too surprising. While not a perfect indicator, we know that hitting balls hard is generally better than the alternative—and these guys, with one giant, Vottoian exception, are all in the midst of stellar years by more traditional metrics. Altuve owns baseball’s third-best WAR; Murphy remains one of baseball’s best bargains; Martinez and Ortiz continue to defy Father Time to the tunes of wRC+ of 142 and 194(!), respectively. Even Votto, recovering from a BABIP 60 points below his career average, is rapidly coming around.

The group presents club evaluators, though, with a very tough question: How “real” are these spikes in hard-hit rate, and by extension the jumps in offensive performance? For Cozart, the question for the Reds front office basically translates to: How likely is he to keep the hard contact up, and how quickly should we trade him?

Let’s start with what we know about hard-hit rate. It’s generally a repeatable skill, as a FanGraphs study from last year puts hitters’ YoY correlation at 0.69. We can also say that there’s no real drop in age to adjust for; I found the r-squared correlation between age and hard-hit rate to be 0.02.

It’s not crazy, then, to think that a career-high spike in hard-hit rate could be the start of long-lasting improvement. And if it is, we should see it in the years around the spike: an increase the year before that hinted at a breakout, or retaining/coming close to the same rate in the next few seasons.

But is that the case?

I pulled all hitters with a hard-hit-rate YoY “jump” above 9% since we began tracking the stat in 2002 to see how they fared in the years immediately before and after. In this chart, “Year Before” is the hard-hit rate versus career average for the season prior to the jump, with Y+1/Y+2 representing the two years following it:

Year Name Team Age Year Before “Jump” Year Y+1 Y+2
2007 Edgar Renteria ATL 30 2.2% 12.8% -3.7% -2.4%
2007 Derek Jeter NYY 33 5.1% 12.5% 0.7% -0.6%
2007 Ryan Howard PHI 27 2.0% 12.4% 3.5% 2.8%
2007 Jimmy Rollins PHI 28 3.5% 11.5% 3.7% -1.1%
2007 Carl Crawford TB 25 -1.8% 11.4% -3.6% 3.0%
2007 Coco Crisp BOS 27 2.5% 11.4% -0.4% -1.5%
2013 Marlon Byrd NYM/PIT 35 3.6% 11.1% 6.9% 1.3%
2007 Chone Figgins LAA 29 2.1% 10.9% -1.9% -0.5%
2007 Mark Teixiera TEX/ATL 27 -1.8% 10.7% 3.5% 1.0%
2009 Carlos Pena TB 31 -0.3% 10.3% 1.6% 6.4%
2007 Aaron Rowand PHI 29 -2.0% 9.7% -0.7% -2.5%
2010 Nick Swisher NYY 29 -0.8% 9.6% -3.4% 1.4%
2007 Michael Young TEX 30 0.4% 9.5% 0.2% 4.0%
2009 Raul Ibanez PHI 37 2.1% 9.5% 4.4% -4.0%
2007 Grady Sizemore CLE 24 0.5% 9.3% 1.4% -1.5%
2007 Ichiro Suzuki SEA 33 2.4% 9.2% 0.5% -1.4%

If you’re looking for a pattern, don’t bother: none really exist, aside from the observation that 2007 was, apparently, The Year of Hitting Baseballs Hard (a poorly anticipated sequel to The Year of Living Dangerously).

The “Jump” years make up a few of the better hitting seasons in modern history: Jimmy Rollins’ MVP campaign of 2007, Teixiera’s famous Rangers/Braves split season in which he posted a wRC+ of 146, even a Raul Ibanez “I’m Not Dead Yet” season with Philadelphia at age 37.

More importantly, though, surrounding these seasons on either side is case after case of regression—and not even particularly close regression at that. There doesn’t seem to be any ability to carry over a hard-hit-rate jump into the next year or beyond.

These seasons aren’t necessarily the same as those supported by BABIP-fueled mirages…but they are propped up by a contact rate that just doesn’t seem to hold up in any type of long run. It’s something that makes sense on an intuitive level: no one, even someone as skilled as a big-league hitter, wakes up and says, “Oh, yeah—that’s how I can hit the ball hard from now on,” then keeps it up for the rest of their career.

A 162-game baseball season may seem long, but it’s subject to many forms of chance, including the odds that some years you’ll strike the ball harder than others. For the purposes of evaluating our 2016 list, it’s info that is more “useful” than immediately actionable: every player on the list except Cozart is signed through at least 2018, while Ortiz, in a Breaking Bad-level identity switch, will hang up his spikes to try his skills as a masseur in Minneapolis.

But it’s a worthy piece of evidence that our protagonist will spend next year likely reverting to average or even worse at the plate—and that the Reds, by extension, should pursue every possible trading avenue for Cozart this summer while the hitting is hard.

 


Chris Sale’s Rarest of Mistakes

Chris Sale is unusually skilled at throwing a baseball left-handed. This process is not generally viewed as aesthetically pleasing, but it is generally effective. It is particularly so against left-handed hitters. This effectiveness is why anything else is noteworthy, and thus why you are reading an article about Sale giving up his first home run to a left-handed hitter since 2012, and then his second such home run three innings later. Oh, right: Eric Hosmer hit two home runs off of Chris Sale Friday night, which is two more homers from the left side than Sale has given up over more than three seasons.

Chris Sale has been phenomenal against left-handed batters well beyond the fun fact of “no home runs allowed since 2012.” In his career he had allowed three total homers by lefties prior to Friday, with a triple slash of .202/.261/.263, all while playing half his games in the bandbox that is US Cellular. This dominance has not gone unnoticed by the rest of the league, and he has become justifiably feared by left-handed hitters and all-handed managers. During his 104 start, 712 inning homer-less streak, he has only faced left-handed hitters 18% of the time, despite batters hitting from the left batter’s box account over 40% of all plate appearances. Only the best face Sale. For perspective, Clayton Kershaw has had 609 plate appearances against left-handed batters since 2013 and has allowed eight home runs. For more perspective, it only took Bartolo Colon 246 plate appearances to hit his first home run.

For his part, Eric Hosmer was not a particularly likely player to end Sale’s streak, let alone to do so in this fashion. He has not yet had a 20-home-run season, and he has now matched his career-high season home-run total against left-handed pitching with five. He went into Friday with three career multi-home run games. If you care about this sort of thing, Hosmer’s numbers against Sale before then were relatively impressive in a small sample: .333/.351/.361 over 37 plate appearances. He is now tied with teammate Alex Gordon for most hits against Sale by a left-handed batter.

Now that we have established why Hosmer’s two home runs off Sale were unlikely to happen, we should look into the homers themselves. But before we get into the actual at bats, here is a plot of Sale’s pitches vs. Hosmer. I do not believe it hard to guess which cluster contains the two big mistakes.

Sale v Hosmer 6/10/16

The first at-bat came in the first inning, with two out and nobody on. Sale started with a fastball off the plate away, then a slider more off the plate away. Down 2-0, this happened:

With a low and away target, Sale left a fastball high and over the heart of the plate. Hosmer crushed it the other way.

Hosmer’s second at-bat led off the fourth inning. Sale started Hosmer with another fastball, equally over the middle of the plate and about four inches higher than the one that went out to left three innings earlier. The target was again low and away. The second pitch was a slider off the plate away, taken for a ball. Third, a slider inside and at the knees that went foul. Fourth, a fastball off the plate inside that Hosmer deflected just enough to hit into his own leg. With the count 1-2, this:

With a low and away target, Sale left a slider high and over the heart of the plate. Hosmer crushed it the other way. Sound familiar?

Hosmer did have a third at-bat against Sale in the fifth inning, and it progressed much as Sale’s interactions with lefties usually do. Called strike one on a low-ish slider, swing through a low slider, then weak contact on a changeup low and in off the plate. Three pitches, all strikes, and a routine groundout.

Contrary to the past three years of evidence, Chris Sale is not immune to left-handed slugging. Specifically, he cannot groove a fastball in a hitter’s count nor hang a slider in any count without expecting that bad results might occur. Eric Hosmer is good enough to punish those sorts of mistakes, and he proved it. He should get credit for that. But the last place a pitcher wants to miss is high and over the plate, and Chris Sale did that twice to the same hitter in the same game. These are certainly not the only such mistakes Sale has made against a left-handed hitter since 2012, but they are certainly the first two to be punished fully. It could be a while before we see the next two.