On Monday night, Yoenis Cespedes became the 26th player to win Major League Baseball’s Home Run Derby, joining the ranks of such elite power hitters as Barry Bonds, Mark McGwire, Ken Griffey Jr. and … Wally Joyner.

Cespedes edged Bryce Harper in the finals and put on one of the most impressive performances the Derby has seen, starting off by hitting 17 home runs in one round and hitting 32 overall, both feats which tie for third-best in the Derby’s history.

This year’s lineup featured, as it always does, some of the game’s premier power hitters, including robot humanoid Chris Davis and two-time Derby champ Prince Fielder.

Behold, a fully functional (however unsortable, to the great dismay of the author) table of this year’s Home Run Derby participants and some relevant first-half batting/power statistics:

American League captain Robinson Cano was given the liberty of choosing three men to represent his team in the world’s annual derby of batsmanship, and he chose Cespedes. An interesting choice, as Cespedes has not been even a league-average hitter this season according to wRC+, but probably not one unwarranted through the eyes of Bud Selig as Cespedes taps into the Cuban market and is still one of the game’s more exciting young players.

And so, in the true nature of sport, Cespedes – the most unlikely of victors given his struggles this season – went out and won the whole damn thing.

Upon Cespedes’ win, I naturally went to his FanGraphs page and noticed his wRC+ was under 100, provoking me to silently think to myself: “I wonder if any other Home Run Derby champion failed to be even a league-average hitter at the time of his crowning?”

Behold, a fully functional and regrettably still unsortable table, this time of past Home Run Derby winners and their relevant first-half batting/power statistics:

The answer is no, and it really isn’t even close.

Since the Derby changed to its current format in 1990, no winner has been within 20% of being “just” league average, and a full 57 points of wOBA separates Cespedes from Miguel Tejada’s 2004 first-half campaign.

In fact, Cespedes is only the fourth player to have entered the Home Run Derby as a below-league-average hitter. That’s right, even in the years that Hee-Seop Choi and Damion Easley competed, they had been at least league-average.

In 2005, Ivan Rodriguez had a wRC+ of 97, Rafael Palmeiro came in at 96 in 2004 and you have to go all the way back to 1994 for Ruben Sierra to “top” Cespedes with a first-half wRC+ of 92.

Interestingly enough, they all performed fairly well in the Derby, despite walking away as losers – or, not winners. Each advanced past the first round, with Pudge finishing runner-up to Bobby Abreu’s monster performance. Palmeiro and Sierra each took third.

Similar to how people say the Derby can throw locked-in power hitters into second-half slumps, maybe it can also get struggling power hitters into a groove again. Probably not, but it was an intriguing observation nonetheless.

Robinson Cano had to choose three men to represent his team of lumber swingers to hit dingers, and he threw caution to the wind by choosing Yoenis Cespedes, who had a worse first half at the plate than Cano’s teammate Lyle Overbay. But this wasn’t a first-half regular season baseball game and Yoenis Cespedes doesn’t play first base for the New York Yankees (and now apparently sometimes right field, too). It was the Home Run Derby, and Yoenis Cespedes reaffirmed Robinson Cano’s bold choice by making history.

I have a bone to pick with Fox Sports’ Ken Rosenthal, and it’s not about the bow ties. I respect a man who can rock a bow tie, especially when he’s doing it for some great causes.

I do, however, have a problem with his column encouraging the White Sox to deal Chris Sale.

It’s not that the idea is without merit; he provides some solid reasoning, but when you consider all of the factors at play, moving the youthful all-star doesn’t make enough sense.

Sale, 24, has less than 500 innings on his resume, a career K/9 rate near 10 and an ERA sitting at 2.89 to boot. Even if the return has the seductive appeal Rosenthal calls for in a proposed swap, the possibility of whiffing is too high for the Sox.

Pitching – young pitching – is the lifeblood of a successful franchise. Ask the low-budget Rays and Athletics how they stay competitive with baseball’s Big Boys. Or if hardware is more your thing, take a look at San Francisco and St. Louis.

For clubs, like the Rays with limited capital, sustained success starts with two integral aspects: assembling a farm system with a deep stable of arms to develop (David Price, Matt Moore, Alex Cobb) or deal (James Shields) and identifying your studs from your duds and controlling their futures into their free agent years (Evan Longoria). The better teams are at accomplishing those goals, the sooner they’ll be annually competitive.

Now the White Sox, not exactly an organization needing to pinch pennies, but certainly tightening the purse strings with an average home attendance of 14,000 fans fewer than in 2005 (as per Rosenthal’s column), have sort of skipped the stockpiling arms part, but with Sale, have correctly located a stud. The southpaw is in the first year of team-friendly 5-year $32.5 million contract, including two club options that would keep him in a White Sox uniform until he’s 30.

That gives the Sox – if they start right now – 6-1/2 years to rebuild around their ace. Plenty of time. The Giants were a last place, 71-win team in 2007. In 2010, behind former farmhands, Tim Lincecum, Matt Cain and Madison Bumgarner, they won their first of two championships. I understand the Giants already had those guys in their system, so it might take the Sox longer, but again, many teams have reversed their fortunes in fewer than 6-1/2 years.

But if you’re not convinced, I understand. I’m hoping this next section might do the trick. Let’s take a look at the specifics involved in the risk Rosenthal suggests the Sox take.

In 2011, Royalsreview.com writer Scott McKinney provided some wonderful insight into the success rate (using WAR) of baseball’s top prospects. Here’s the link to the article, but I’ll do my darndest to summarize it justly.

McKinney – piggybacking some work done by Victor Wang in 2007 – studied the production of Baseball America’s top 100 prospects from 1990 to 2003, giving each prospect a seven-year span to produce.

Here’s what he found: Right off the top, 70 percent of top prospects are destined for failure – qualified by an average per-season WAR below 1.5.

But we already know there is risk in dealing proven stars for prospects, even premium guys. That’s an inherent part of the game. It happens every season, and it always will.

Sure, but let’s look at the success rate of top 100 pitching prospects, which is what the White Sox should demand — even though GM Rick Hahn disagrees — to restock Baseball America’s 29th-ranked cupboard, which is practically barren of difference-making hurlers.

According to McKinney’s study, pitching prospects have a much smaller chance at success that position players. In fact, a pitcher ranked from 21-100 on Baseball America’s list fails at least 70 percent of the time with odds of failure increasing as the list moves toward #100.

In other words, the White Sox would have to land a Dylan Bundy- or Gerrit Cole-type pitcher (Baseball America’s preseason #2 and #7 prospects) in the deal to give themselves a better than 30-percent chance of succeeding at the major league level. Why would the Sox roll the dice on an arm like that when they have Sale’s locked up, if they choose, for the next 6-1/2 years?

In short, they shouldn’t. His contract is extraordinarily reasonable, and the frontline prospect(s) they’d receive in return would likely only be a couple years younger than Sale with no guarantee they’ll produce or sign a team-friendly contract.

OK. Now let me address the glaring hole in this argument: The Sox would surely receive more than one elite prospect in such a deal.

And many would justly argue that the best way for organizations to produce a high quantity of talent is to load as many proverbial bullets into the chamber as possible, hoping one or two’s projectile is a major league rotation/starting lineup.

I understand that mentality. In fact, normally, I agree with it, but that 70 percent failure rate for top prospects looms large, especially when trading the caliber of pitcher Sale is.

Let’s look at Baseball America’s top 10 prospects from 2006 (giving them seven years to produce, just like the study): No. 1 Delmon Young; No. 2 Justin Upton; No. 3 Brandon Wood; No. 4 Jeremy Hermida; No. 5. Stephen Drew; No. 6 Francisco Liriano; No. 7 Chad Billingsley; No. 8 Justin Verlander; No. 9 Lastings Milledge No. 10 Matt Cain.

I see this list and think: There was a time when the consensus was that Chad Billingsley was a better pitcher than Justin Verlander; that Brandon Wood was more a highly regarded shortstop than No. 25 Troy Tulowitzki; and that Lastings Milledge wasn’t playing in Japan.

In all seriousness, what this says is that dealing with prospects, all prospects, is a crapshoot. And it’s a crapshoot not worth playing for the Sox who already have their silver bullet.

Rosenthal suggests in order for the Sox to pull the trigger on such a deal, they would have to hold out for the kind of haul Texas Rangers brought in when, in 2007, they traded Mark Teixeira for Atlanta’s farm system. In the trade, widely considered a coup for Texas, the Rangers received Baseball America’s preseason No. 36 prospect Jarrod Saltalamacchia, No. 65 Elvis Andrus, No. 90 Matt Harrison, unranked Neftali Feliz, who was 17 at the time, and unranked  Beau Jones.

Since the trade, the highest-rated prospect of the bunch, Saltalamacchia, has accumulated a career (Baseball-Reference) WAR of 4.2. Andrus, despite two All-Star appearances, has never produced at an All-Star level with just one season with a WAR above 4. The lefty Harrison has produced a 9.2 WAR in his career; not bad, but not Sale. And finally there’s Feliz, whose impact was felt in 2010 and 2011 but whose value — WAR has never eclipsed 2.5 — was limited in a relief role. Add it all up, and Salty, Andrus, Harrison and Feliz have combined for 34.4 Wins Above Replacement in a combined 20.5  major league seasons (2008-today), giving the foursome a 1.67 WAR per season average, just barely avoiding failure by McKinney’s standards. Not exactly the steal it appeared to be a few years ago.

Sure, the players acquired in the trade did help the Rangers reach back-to-back two World Series, but what was the thing the Rangers were desperately chasing in 2010? An ace, and they unloaded their farm system to acquire one, getting Cliff Lee from the Mariners for Justin Smoak, Blake Beavan, Matthew Lawson and Josh Lueke.

Sorry for the reminder, Seattle fans, but the White Sox should see how this deal worked out for the Mariners and stash Sale with Eric Snowden.

The Sox should sell whatever they can to begin the rebuilding process. Sell Jake Peavy. Sell Jesse Crain. Sell Alex Rios. But hold onto Chris Sale, the most effective and polished pitcher in the American League under 25 (1.01 WHIP, 1st; 9.8 K/9, 1st; 4.85 K/BB, 1st; Opponents OPS .597, 1st) who will lead their pitching staff for years to come.

The lefty has already produced a 14 WAR in 3-1/2 major league seasons — one abbreviated and one as a reliever. For comparison, Cy Young-winner Clayton Kershaw produced 18.1 WAR in his first four seasons, but pitched 716.1 innings, 300 plus more than Sale thus far.

And let me address what I’ll call a minor consideration Rosenthal makes as an argument for why the Sox should trade Sale. The sidewinder has an awfully violent motion and a rather slight frame; what if he breaks down?

My answer: It doesn’t matter. The risk involved in the trade remains far greater.

Even if the worst happens, and Sale tears his UCL and needs the king of all pitching surgeries, the Tommy John, there is a very good chance he comes back from it and pitches like he did pre-surgery. I’d cite such successful examples such as Stephen Strasburg and Adam Wainwright, but I know there are examples to the contrary.

So, I’ll call upon an expert witness: Dr. Christopher Ahmad, an associate professor of orthopedic surgery at Columbia University and head team physician for the New York Yankees.

Last year, he told FoxNews.com, “… the success rate of having Tommy John surgery is between 70 and 80 percent to full level of throwing.”

That’s not perfect. There are no guarantees. This is still a major injury and surgery is required, but it is still superior to the 30 percent success rate for prospects we looked at earlier. I understand what Rosenthal was getting at. Why let a stud toil on a middling team? Look at Felix Hernandez. Weren’t all those years in Seattle wasted? Yes. I can’t argue against it. And that might happen to Sale if the White Sox keep him around and don’t embark on a successful rebuilding mission. But what the Mariners knew and White Sox should know is rebuilding shouldn’t come at the cost of a Cy Young caliber 24-year-old. He’s the ground floor. He’s the building block. He’s where you start.

If you watched the Home Run Derby on ESPN, you saw Yoenis Cespedes and his raw, yet explosive swing, hit 17 home runs in the first round of the derby. You also saw Chris Davis staying true to his swing and swinging at any pitch that he thought he could handle, hitting the ball where it’s pitched, and even swinging at some pitches that were borderline balls. If there was anyone to be concerned about changing his swing to fit the Derby, it was Davis–the guy who has so much strength that all he needs to do is stay within himself and swing easy to hit a homer. One might worry that Davis would swing too hard or try to pull everything, thus regressing into the “quadruple-A” player as he was once labeled, swinging and missing at a such a rate that he became a liability.

Anyone who has played baseball at a high level knows that a successfully executed sacrifice bunt, or grounder to the right side of the field with a man on second and nobody out, is frequently celebrated as much as a hit. Quality “team baseball” seems to be more effective than a mere amalgamation of flashy superstars that doesn’t mesh (I’m looking at you, 2012 Red Sox or 2013 Blue Jays). The Home Run Derby is kind of counter-intuitive to many MLB managers. Old-schoolers like Mike Scioscia would rather his players did not participate, saying, “I haven’t seen somebody come away from that derby and be a better player for it.”¹ The Home Run Derby turns the team game into an individual competition. Players exhaust themselves and risk tweaking their swings, but has the derby really affected the second-half performance of its participants?

To answer this question I looked at what goes into a player’s stats. There is a lot of luck involved in baseball, so I took a look at the differences in the way players hit the ball before the derby compared to after the derby. Looking at the past five derbies, I calculated the average batted-ball flight for players that were healthy for both halves of the season (38 players, excluding only Rickie Weeks in 2011 and Jose Bautista in 2012).

The consistency in the way players hit the ball is incredible. Derby participants hit the ball almost the same before and after the derby as a group. The HR to FB ratio drops considerably, and could explain a decrease in batting average and slugging percentage, as well as on-base percentage. It seems that players hit the ball the same way, just with slightly less power. Here are some of their standard stats from the second half:

Isolated Power (ISO) measures a hitter’s power in extra bases per at-bat (2B+3Bx2+HRx3)/AB. The large drop is ISO shows that indeed power does decrease for derby participants in the second half, and the overall line shows that players do perform worse. It’s not merely a function of hitting the ball to the wrong place, as the .oo6 drop in Bating Average of Balls in Play (BABIP) is not really significant. Players strike out a little bit more, but the notion that players change their swings and have trouble hitting the ball the same way after participating in the derby seems misguided when considering the small change in K% along with the consistent batted-ball percentages outlined in the first table.

Data suggests that players do perform worse in the second half of the season after participating in the HR derby, but that their performance isn’t due to a change in their swings. There have, however, been some significant changes in performance for some individuals. Taking a closer look at some of them, the poor performances can be explained without blaming the Home Run Derby.

Uggla has a reputation as a streaky player, but he went from an MVP candidate in the first half to a guy who didn’t belong in the starting lineup after the derby. Taking a closer look, however, Uggla began slowing down in late June, and suffered a leg injury that kept him out nearly two weeks just prior to the All-Star Game. He only lasted one round, anyways, so it’s hard to blame the derby for his drop off, although it was certainly a big one.

By 2008 Berkman had been a good hitter for many years. His second half was hurt by the amount of pop-ups he hit. a 10.4% increase in infield fly balls mean close to a 10% increase in outs, and his average decrease supports that notion. His increase in pop-ups could have been a result of an uppercut swing that developed in the derby, but his average had dropped 20 points in 16 games prior to the derby, and his career IFFB% is 11.5%, not too far off from his second half percentage. Perhaps the derby hurt Berkman’s swing, but more likely  he was finally coming back down to earth after his torrid start.

Brandon Inge? Yeah, Brandon Inge was in a Home Run Derby. He only has a career HR/FB ratio of .10, and a career batting average of .233, so his second half was closer to what Inge’s career looked like. Plus Inge didn’t even hit one out of the park, so could ten swings really ruin his season?

Wait a second…? Was Ryan Howard better after participating in the derby? Yes! After the slugger hit 15 big flies in the derby, he went on to hit more homers in less at-bats afterward. With zero infield flies in the second half of the season, his swing was just fine.

After a hot start in April and May, Bautista had his worst month of the season in June, before the HR Derby. While Bautista was better overall before the derby, he was better in the two months following the derby than he was before it.

Prince puts a lot of power into his swings, and when he hits 28 balls out of the park, he exerts a lot of energy. Prince won the derby in 2012, and continued winning games for the Tigers after the All Star Break. Hitting for a better average, and with an improved HR to FB ratio, Prince shows that the derby can kick start a player’s second half.

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Conclusion: The notion that participating in the Home Run Derby leads to a drop off in performance is a myth. Although data suggests that Home Run Derby participants do indeed regress in the second half of the season, the derby is not to blame. As baseball is a game of superstitions, players are aware that the derby can have harmful effects if they aren’t careful. Even Chris Davis was wary, saying, ”I wanted to be conscious of not changing my swing at all… I tried to stay up the middle and let the ball travel and not try to get pull heavy. But it looks a lot easier on TV than it really is. Once you get out there and start swinging and your adrenaline wears off, you realize how tough the Derby really is. It’s exhausting.”² While the derby curse isn’t real, it’s hard to continue chasing a 60-home-run season with a popped blister. Get some treatment on that hand, Chris.

1 http://www.latimes.com/sports/sportsnow/la-sp-sn-angels-relieved-mike-trout-not-in-home-run-derby-20130709,0,7051643.story

2 http://mlb.mlb.com/news/article.jsp?ymd=20130715&content_id=53853822&vkey=news_bal&c_id=bal&utm_source=twitterfeed&utm_medium=twitter

All data from Fangraphs.com

Adam Wainwright has been absolutely phenomenal this season. If you prefer old school stats: 12-5, 2.30 ERA, with an 8.06 K/9 ratio. If you prefer advanced statistics, he looks even better: 2.12 FIP to go along with a 2.69 xFIP. My favorite stat about his season so far though is his K/BB ratio which in mid July now stands at a staggering 9. For every 9 strikeouts he walks 1 batter. You don’t need me to tell you how good that is. The pitcher nearest his efficiency is Cliff Lee and he isn’t even close.  I decided to compare Adam Wainwright’s impeccable ratio to some of the greatest pitchers in the past 20 years. I’ll take their best season (regarding K/BB) and see how it stacks up to the masterful performance Wainwright is putting up this season.

Adam Wainwright is having a phenomenal year. His 9.00 K/BB is surpassed only by Cliff Lee’s and Curt Schilling’s most efficient seasons, respectively. I’m not really counting Smoltz, due to his best K/BB ratio coming as a closer with only 60+ innings pitched. Here are the following seasons since 1900 where someone had a K/BB greater than or equal to 9.

•  Bret Saberhagen (11 K/B 1994)
• Curt Schilling (9.58 K/B 2002)
• Cliff Lee (10.28 K/BB 2010)

What is making him this successful?

Mea culpa. After posting an in-depth look at Albert Pujols‘ lone sacrifice bunt, readers both friendly and unfriendly pointed out to me that there is record of three more major-league Pujols bunt attempts, two for hits and one a squeeze (but no other known sacrifice attempts). The only satisfactory way to own up to my mistake is to follow up with a new essay asking: why did Pujols bunt those other times? Any errors in this new post are the responsibility of Session Lager the author.

Bunt No. 2: May 23, 2003

What was the bunt? Albert Pujols had a good day. He struck out in the first inning and then racked up five hits (two doubles), including one in the top of the tenth inning. It’s the 10th inning we’re looking at here.

With two outs and a runner on second base, J.D. Drew hit a triple to deep center field; the runner scored, giving the Cardinals a 9-8 lead. Next, Albert Pujols singled on a bunt to third base, scoring Drew and making the lead 10-8. The Pirates couldn’t recover in the bottom of the inning.

Was it a good idea? This was a squeeze play with two outs. In the tenth inning. Using a batter who had only bunted once before. On the other hand, the Cardinals already had the lead they needed. It was a daring mad-scientist gamble. The bunt had to be perfect.

Did it work? The bunt was perfect.

Bunt No. 3: July 27, 2003

What was the bunt? Only two months later and against the same Pirates, Pujols attempted to bunt for a hit and failed in the 8th inning. His Cardinals were losing 3-1, and there was one out and no runner on base.

Was it a good idea? Albert Pujols was facing Brian Boehringer (5.41 FIP, 4.33 BB/9, -0.7 WAR that season). He may have been emboldened by the memory of his recent success, but given how good Pujols was at not-bunting, and how bad Boehringer was at pitching, this attempt is only understandable if it was an attempt to take the enemy by surprise. Pujols bunted on 0-1; whether he showed bunt on the first pitch (a called strike) is lost to the sands of time.

Did it work? No, but in the next (9th) inning, with two outs, Pujols had a walk-off single to win the game.

Bunt No. 4: August 25, 2004

What was the bunt? It came on another good day: Pujols singled, doubled, and homered. And the single was a bunt to third base on a 1-0 count in the 8th.

Was it a good idea? See, this is the thing with bunt-for-hit attempts; without seeing the defense at work, and without understanding the state of play, all we have to go on is hindsight. John Riedling was another troubled pitcher, almost identical to Boehringer (5.24 FIP, 4.64 BB/9, -0.7 WAR that year); both also suffered from inflated home run rates. They were, presumably, easy pickings. And, indeed, Jim Edmonds brought Pujols home on a game-tying line drive over the fence.

Did it work? Yes.

Conclusions (Again)

What can we learn, aside from that the author needs to be a little more diligent? That Albert Pujols has done okay as a bunt artist. His first try, as a rookie, remains incomprehensible, but he then executed a flawless two-out squeeze play and went 1-for-2 in tries for a hit. I’m inclined to believe that the tries for hits represent opportunism, and that the lone sacrifice and the squeeze play represent Tony La Russa’s management philosophy at work. On my last post, reader Tim A wondered if that first bunt was La Russa simply testing Pujols’ ability to lay the ball down.

It’s still kind of weird that the then-best (or best non-Bonds) hitter in baseball tried a squeeze bunt on two outs. It’s definitely weird that a rookie with 20 homers would be called upon to bunt from the cleanup spot. But hey, we discovered a new wrinkle: Pujols is pretty good at yet another part of baseball. And in games in which Albert Pujols bunts, his team is 4-0.

Possible Teasers if I Decide to Write More of These at Some Point

According to the batted ball data (except where this data is incomplete, starred*), here are some more career bunt attempt totals: Adam Dunn 3, Manny Ramirez 2*, David Ortiz 11. In 2009 Jack Cust went 3-for-3 on bunt hit attempts. That same year, 3 successful bunt singles were laid down by Pablo Sandoval.

Craig Biggio came about 7% of the vote shy of spending late July of this year in Cooperstown giving a tearful speech about his playing career, but it’s likely he’ll get a chance to make that speech sometime in the next couple of years. Biggio was a very good major-league player over 20 seasons and ranks 83rd all time in WAR. He has 3,000 hits, which is generally a gold standard among voters, and ranks higher than a number of other current Hall of Famers in WAR such as Tony Gwynn and Roberto Alomar.

Certainly, some of Biggio’s value is based on longevity and the second half of his career was not nearly as productive as the first. Even if Biggio doesn’t make the Hall of Fame by your own personal standards, he’s likely to get in and is at least worthy of a conversation on the subject.

I’ve always been fond of players who play multiple positions like Ben Zobrist (who does it while being an excellent hitter) or Don Kelly (who does it while being something around replacement level). It’s a type of player I enjoy watching, and Biggio’s 428 games at catcher, 366 games in the outfield, and 1989 games at second base put him in that category. As I often do with players who peak my interest, I spent time exploring his career statistics and one particular season stands out as his best, but it also stands out for another reason entirely: Biggio grounded into exactly zero double plays that season.

The year was 1997 and Biggio’s Astros were heading toward an 84-78 record, a Central division title, and a brief appearance in the postseason before being swept at the hands of the Braves. Over the course of the campaign that would end with Biggio finishing fourth in the NL MVP race, he lead MLB with 9.3 WAR narrowly topping players named Griffey, Walker, Piazza, and Bonds. Biggio accumulated those wins with an extremely balanced attack.

In 744 PA, he hit .309/.415/.501 for a .401 wOBA and 148 wRC+. His Total Zone was 19 and his baserunning runs above average came in a 5.2. He stole 47 bases, hit 22 HR, scored 146 runs, and was hit by 34 pitches. Pretty much everything he did that season was his career best or very close to it. It was easily the best season he ever had and one of the most valuable seasons in recent memory, coming in 36th in WAR since 1961.

Biggio’s 1997 season is remarkable because it’s the biggest feather in the cap of a very good player and one of the more balanced and interesting stat lines you’ll see, but it’s also remarkable because Biggio did it without grounding into a single double play.

Baseball-Reference appears to have complete data on the matter going back to 1939 and since then only seven qualifying hitters have gone an entire season without grounding into a double play. This list itself is truly amazing.

Pete Reiser, 1942 (4.4 WAR)

Dick McAuliffe, 1968 (5.2 WAR)

Rob Deer, 1990 (1.2 WAR)

Ray Lankford, 1994 (2.4 WAR)

Otis Nixon, 1994 (0.3 WAR)

Rickey Henderson, 1994 (2.8 WAR)

Craig Biggio, 1997 (9.3 WAR)

First of all, you’ll notice that three of the seven seasons on this list came in 1994 when the season was cut short due to a strike, so while these seasons count they should be taken with a grain of salt because the guys on this list played 85-105 games each instead of 162. Aside from those three, this has only been done four times in major league history and one of the times was by Rob Deer. You can’t make that up.

Reiser and McAuliffe had very good seasons during the years they didn’t ground into any double plays, but they didn’t have the kind of year Biggio did. McAuliffe was four wins behind the leader in 1968 and Reiser was seven wins behind Ted Williams in 1942. Biggio accomplished this feat, which is exceedingly rare, while being one of the league’s very best players. From 1939-2012 there have been 8,636 qualifying seasons and just seven instances of a player avoiding a double play all season long.

Only .08% of all major league seasons have ended with a player not grounding into a double play. Three of them happened in the same strike-shortened season. One during a below-average season from Rob Deer. Two came during very good seasons more than 40 years ago. One came during Biggio’s amazing 1997 campaign in which he did just about everything you could ask a baseball player to do.

In 1997, Biggio came to the plate in 78 situations in which grounding into a double play was possible. In those situations he hit an impressive .403/.487/.677. Of the 40 times he didn’t get a hit, walk, or get hit by a pitch, he hit 13 ground balls. Two of those ground balls turned into errors and he got down the line fast enough the other 11 times to prevent the defense from converting the second out.  It is worth noting, however, that Biggio did line into a double play once during the season, but that hardly seems fair given that it isn’t considered a GIDP and is more the fault of the baserunner than the batter. Additionally, he was the strikeout half of one strike-em-out-throw-em out double play in 1997, so he wasn’t completely without his faults.

Craig Biggio is a likely Hall of Fame player with 3,000 hits who had one of the most impressively balanced seasons in recent memory in 1997. If I were the one responsible for writing the text on his Cooperstown plaque, I would be sure to find room for the phrase, “One of seven players in MLB history to go an entire season without grounding into a double play” because I’m not sure he’s ever done anything on a baseball field more noteworthy than that.

Yasiel Puig has been in the news a lot lately. He’s had phenomenal start to his career, well aside from the Diamondbacks’ catcher Miguel Montero hating him. He’s also had most of his success without drawing many walks, which inevitably has sent him sliding down a mountain into inevitable comparison to known hacker Jeff Francouer. Francouer never tore up the minors the way Puig did, but it’s somewhat of a fair comparison due to how much fanfare Frenchy had after such a quick start to an otherwise poor career. As Jeff Sullivan from FanGraphs noted, the league is beginning to adjust to Puig, now he has prove he can counter those adjustments.

Fangraphs lists the BB% of 7% to be below average, 5.5% is poor, and 4% and lower is awful. Puig’s current BB% in the majors after 36 games is 4.5%. He did post a 9% walk rate in AA this year before his call up, so there’s a little reason to believe he is capable of being more patient than he is right now. I’ll take a look at some guys who had solid careers while also sustaining low walk rates. I took the leader-board at FanGraphs, sorted for year 2000-2013, removed everyone with a walk rate north of 8%, and removed everyone with an ISO (isolated power) below .175. The following players have compiled 15 fWAR since 2000 (players in bold are still active).

That isn’t very many names. Of the 202 position players that accumulated 15 fWAR from 2000-2013 only 58 or 28.7% had walk rates less than or equal to 8%. Adam Jones fell slightly below on a few parameters, but for comparison’s sake he felt pretty accurate. Here is Yasiel Puig at the moment. I included his AA stats and his projections for the rest of the season.

We’ve noticed you can be successful without walks, but it isn’t easy. All of the players from the first table were all good to phenomenal players in their own right. It’s unfair to say Yasiel Puig has to turn out to be as good of a hitter as Carlos Gonzalez or Adrian Beltre to be successful, but he’ll have to follow their lead if he can’t learn to draw walks as he gets experience. Personally I see Puig as a .270/30 homer/15+ steal guy in the future. If he can manage that he should be fine, but I’m sure he’ll never meet the expectations some people have for him at this point. Any player on that list would be a win (maybe aside from Vernon Wells because…ugh). Anything on top of the production these guys have managed is just gravy.

Visualizing Pitcher Consistency

When evaluating starting pitcher performance, fantasy owners and fans alike lament the relative inconsistency of certain pitchers deemed especially volatile (Francisco Liriano will break your heart), while others like Mark Buehrle are workhorses often viewed as among the most steady arms available.  A.J. Mass of ESPN has written about the value of calculating “Mulligan ERAs,” in which a pitcher’s three worst outings are subtracted from his overall ERA. His colleague Tristan Cockroft routinely publishes Consistency Ratings to let readers know which pitchers have remained relatively high on ESPN’s player rater from week to week.

While these methods focus on pitcher performance from start to start, it may be useful to evaluate pitcher performance against individual batters. If Tommy Milone gets rocked pitching on the road in Texas, we may be less concerned than if he is routinely unable to get out low quality hitters. To this end, we can examine how pitchers perform against different levels of batters. How well does a given pitcher avoid putting low OBP batters on base? How does this compare to his rate of putting a high OBP batter on base? We would expect to see a linear relationship—the Emilio Bonifacios of the world should be easier to get out than the Joey Vottos.

Methods

We begin by examining the 31 pitchers with the most innings pitched for the 2012-2013 seasons. After obtaining batter vs. pitcher data for each of these pitchers during the last season and a half, we can calculate the OBP allowed by each pitcher to any batter with at least 5 plate appearances during this time period (arbitrary cutoff alert!). We can now see how Buster Posey fares against the likes of Clayton Kershaw, Ian Kennedy, and any other NL pitcher in which he has accrued at least 5 PA. It turns out Posey did pretty well for himself.

In order to obtain the OBP of batters in general, not in relation to particular pitchers, we can examine the leaderboards for players with at least 450 PA in 2012-2013. Based on the work of Russell Carleton, we have confidence that after ~450 PA, a batter’s OBP tends to stabilize and represents their long-term OBP skill level.

Batters were then placed in five buckets, lowest, low, medium, high, and highest OBP levels.

Each batter, assigned a score of lowest to highest, was then matched with the batter vs. pitcher dataset, allowing for us to calculate the mean OBP allowed by individual pitchers to hitters in each of the categories. So, although someone like Zack Cozart sports a .283 OBP in 2012-2013, earning a spot in the lowest category, he does own a .329 OBP against Yovani Gallardo. Maybe this is all the evidence Reds Coach Dusty Baker needs to keep batting Cozart second in the lineup.

Results

If we examine the performance of pitchers across five categories of OBP skill, we can calculate the correlation coefficient of these five points. R² in this case is a measure of how well the data fits a straight line—if a pitcher allows a low OBP to low OBP hitters, and a correspondingly higher OBP to high OBP hitters, the data points should increase linearly and the value of R² should approach 1. Conversely, pitchers that are inconsistent in their ability to get hitters of a certain skill level out would have a R² much closer to 0.00.

There is a wide range of R² values among this list of starting pitchers. Adam Wainwright takes the grand prize for consistency. He is far more prone to putting elite OBP hitters on base than lowly hitters. Madison Bumgarner, on the other hand, strangely performs worse against low OBP than high OBP hitters, and has the lowest R².  And R.A. Dickey, as you might expect, is sort of all over the place.

Below is a visual representation of the OBP against pitchers with high and low R² values. We can see that the pitchers with the highest correlation coefficient have a much more linear relationship overall with OBP allowed than pitchers with low values.

Additional analyses showed that there was no relationship between a starter’s FIP and their correlation coefficient. A quick glance at the names in the two graphs above confirms this. Jason Vargas, with a R² of .793 is a worse pitcher, in pretty much all respects, than Felix Hernandez at .076. Interestingly, Jason Vargas has one of the league’s highest HR/9 at 1.28 during 2012-2013, while King Felix sports one of the lowest ratios at .62.

What, then, does pitcher consistency tell us? While it may not tell us much about the overall skill of a pitcher by itself, we can discern from the data which pitchers are doing a good job getting out poor hitters. Pitchers like Adam Wainwright and Max Scherzer are doing extremely well, and their R² values indicate that they are pitching steady—they are less likely to blow up against poor hitters. Of course, pitcher performance can differ greatly from start to start, but one can have confidence that Ricky Nolasco will probably dominate his former Marlins teammates (30^th in team OBP), because he consistently allows a low OBP to low OBP hitters. Conversely, perhaps it’s a good thing Jason Vargas does not have to pitch against his Angels teammates, who collectively have the 4^th highest team OBP in the majors.

Oddly enough, Justin Masterson’s OBP allowed has a small range, from .299 in the middle OBP tier to .371 against the highest tier, indicating that when he’s brought his good stuff, he mostly dominates all batters regardless of their level of skill. We can have less confidence that Justin Masterson will dominate a middling OBP team like Kansas City (6.39 ERA this year), ranked 20^th overall in the majors, while he has repeatedly humiliated the Blue Jays, who just beat out the Royals at 17^th overall.

Despite the comically bad timing of his recent piece on batting Raul Ibanez against CC Sabathia, David Cameron was right to point out the relative worthlessness of individual batter vs. pitcher matchups and the danger of drawing conclusions from such small sample sizes. However, we can use aggregated batter vs. pitcher data to learn more about what kinds of players pitchers are more likely to strike out, or serve up the long ball, or a base on balls. While it’s easy to assume that pitcher X will be less likely to strike out Norichika Aoki than Ike Davis, by studying consistency we may be able to see who deviates from this linear pattern. Are some average strike out pitchers more likely to strike out low strikeout hitters? We can already see from the data above that R.A. Dickey is as likely to put a low OBP hitter on base as a high OBP hitter. While this fact seems to make little sense, these results indicate that the knuckleball can baffle expert hitters as much as less skilled batsmen. It may be worthwhile to use consistency ratings such as these to determine what kinds of pitchers deviate from the expected patterns.

All data courtesy of Fangraphs and Baseball Reference.

Because I’m a big believer in open data, here is a link to the R code used to find Batter vs. Pitcher OBP percentages by quintile.

We all know that Miguel Cabrera had a phenomenal year in 2012, winning the Triple Crown and later being named the American League MVP. His 44 home runs and .330 batting average are all his own but the 139 RBI he amassed are a shared number, as he couldn’t accumulate RBI without the R (runners). What if everybody had Cabrera’s opportunities? Would others have eclipsed his RBI total?

To analyze this I calculated a percentage measure called the Runner Movement Indicator, or RMI for short. It’s a simple calculation once you have the data. Each time a batter comes to the plate with a runner on base, the potential bases that the runners can move are added together. A runner on 1st can move three total bases, 2nd base can move two and 3rd base can move one. Then, at the end of the at-bat, the final positions of the runners are compared with their starting position to determine the total bases moved out of the potential bases. For example if Cabrera gets a single with a runner on 1st, moving the runner to 3rd base, he is awarded two of the possible three bases, for a 0.667 clip. By calculating RMI as a percentage of the opportunities, we’re factoring out the increased benefit Cabrera gets from his stellar teammates.

One of the beautiful things about RMI is not just that it is a simple calculation, but that it reads nearly like a batting average. This makes it is immediately easy to tell the good from the bad. Below is a histogram of the RMI for all qualifying players in 2012.

Now let’s overlay that with the batting averages from the same year in red. You’ll see the distribution is quite similar.

One might think that players with high batting averages also have high RMI, but that’s not quite the case. If we try to correlate RMI with Batting Average, OBP or SLG, we stay below a 0.5 R² in each case although all with the expected positive slopes.

RMI vs BA	RMI vs OBP	RMI vs SLG
0.411 R2	0.429 R2	0.323 R2
*	*	*

Now that we know a little about RMI, let’s look at the leaders from 2012.

We see that Cabrera is 7th on the list for 2012. Still great, but not the best. We also see that Joey Votto moved runners around the bases at the highest rate, 26 points higher than Cabrera. So let’s use the RMI data above to see if anybody would have taken over the RBI lead given the same opportunities as Cabrera.

To do this we first subtract home runs from RBI, as the batter’s own bases aren’t used in RMI. Of Cabrera’s 139 RBI in 2012, 44 came from himself scoring on his own home run. This means he had 95 RMI influenced RBI based on a 0.316 RMI. If we apply this same ratio to Votto’s RMI of 0.342 we get 103 RBI. Votto’s 14 home runs bring him up to 117 RBI, still well shy of Cabrera.

Of course we know that Josh Hamilton was the one chasing Cabrera’s home run total in 2012, so let’s do the same calculation with him. Hamilton’s 0.323 RMI would give him 98 equivalent RBI. Adding in his 43 home runs brings him to 141 RBI, 2 higher than Cabrera. Too close to call? Nah… Hamilton wins.

Takeaways

The ability to get on base is one of the best predictive factors of runs and therefore wins. It gets better if you add RMI but they should be considered a distinct contribution. RMI leaders may not have great batting averages and vice versa. Undervalued players can be found with high RMI that have average OBP and BA stats.

More Data

Complete player and team RMI stats can be found on with the links below

• Player RMIs from 2010 to 2013

• Team RMIs from 2010 to 2013

Data Collection & Mining Techniques

All of the data used in this post was loaded from MLB’s gameday servers into a MongoDB database using my atbat-mongodb project. This project is open source code that anybody can use, modify, contribute to, etc. Fork me please!
https://github.com/kruser/atbat-mongodb

All data aggregation code and charts are written in Python using MongoClient, matplotlib, scipy and numpy modules. You can find that code on github as well. https://github.com/kruser/mlb-research

Other Notes on RMI

• After collecting my data I ran across Gary Hardegree’s Base-Advance Average paper from 2005, which does a nearly similar calculation, with the exception that it gives the batter credit for moving themselves. I prefer to keep this a clutch stat and remove the batter’s bases.

• The RMI data does not correlate to team run production as high as Batting Average, Slugging Percentage or On-Base Percentage. Adding OBP to RMI correlates much higher, but then again, that’s what a run is–getting on base and moving around to home. So there isn’t anything noteworthy enough there to post numbers.

• In order to qualify for my list a batter must have a minimum of two potential base movement opportunities per game. Opportunities fluctuate largely among regular players so it is important not to keep this requirement too low.

I apologize up front for beating a dead horse with a stick, but Mike Trout is incredible.

As of July 11, he’s sporting the following line:

• 320/399/560 164 wRC+, with 21 SB (87.5% success) for good measure

Last year, Mike Trout’s amazingness was well documented, especially on this site. His 2012 (should be MVP) season line:

• 326/399/564 166wRC+, with 49 SB (89.1% success)

Notice anything about those two lines? They’re basically identical.

At first glance, that’s not particularly interesting. He’s really really good, as we all knew. But what makes it interesting is that he’s actually shown significant signs of improvement in seemingly getting to the same place as last year. He’s walking slightly more (11.1% rate vs. 10.5%), but more importantly, he’s cut down on his K% by over 5%, from a slightly worse than league average 21.8% to a better than average 16.7%. Hence, despite his BABIP dropping by a meaningful 26 points from .383 to .357, he has maintained the exact same AVG and OBP.

Basically, he’s replaced some BABIP luck from last year with actual improvement. His BABIP is still well above league average (currently ranking #15 among qualified), but given his unique combination of speed, power and nearly 23% line drive rate (league average 20.9%), I’m inclined to believe a .350 BABIP is a reasonable true talent level.

I’ve focused on his BABIP and K%, so let’s dig a little deeper into those two rates. In terms of BABIP, his LD/FB/GB rates are essentially the same as last year. Directionally, he’s also hitting about the same percentage of balls in play towards the left, center and right as last year. This could serve as evidence that the decline in BABIP has been nothing more than luck, and that there is no change in the controllable inputs. In terms of his improved K%, what jumps out is that his zone contact rate has improved by 5% so far this year from last year, contributing to a 2% improvement in overall contact rate. He’s seeing 4% fewer fastballs and 1-2% increases in offspeed stuff (sliders, curveballs and changeups). Additionally, he has seen 3% fewer pitches in the zone but been swinging overall at an identical rate. That data can probably be taken multiple ways, but I’d read it that he’s making better contact, despite swinging the same amount at an overall blend of seemingly tougher pitches to hit.

It seems clear that he’s showing improvement, which is to be expected for a 21 year old in his second full major league season. And simple aging curves foretell that there’s much more improvement to come. Using Tango aging curves (1919-1999 data) to get a sense of what Trout’s profile might look like at his peak, the signs are again very encouraging. I’ll use age 27 for a peak year (arbitrarily):

Where a 1.00 is peak for the category

• Age 21: BB: 0.66, K: 1.32, HR: 0.68 and SB: 0.87

• Age 27: BB: 0.88, K: 1.01, HR: 0.95 and SB: 0.88

I won’t actually project his numbers forward using these rates, as this is meant to be purely representative and I don’t care to get into debates about calculating correctly, but basically:

• His walk rate should improve
• His K rate should decline
• His HR rate / power should increase
• And his SB rate / speed should still be more or less the same

Mike Trout is already incredible, so maybe it’s not fair to compare him to the average player’s aging profile. And maybe it’s just not in our best interests to – I’m not sure my mind can handle the concept of a player as amazing as Trout getting that much better.