The first week of April in Pittsburgh felt like a National League Division Series in the midst of October with tons of energy and excitement. Francisco Liriano threw six shutout innings with 10 strikeouts and led the Pirates to a game 1 win. In game 2, the Pirates revived some late-inning magic from 2015 and walked off in the 11th on a Jordy Mercer single down the first base line. In game 3, Juan Nicasio showed many that his spring training stats were not a fluke and led the Pirates to a 5-1 win. The Pirates started 2016 with a three-game sweep of the division rival St. Louis Cardinals and “yinzers” were ecstatic. FanGraphs’ very own Jeff Sullivan wrote a piece examining the changes in playoff odds after just one week of play. His chart had the Pirates’ odds increasing by seven percentage points, while the Cardinals’ odds decreased by almost five percentage points. While it was only the first series of the season between the two teams, it still meant something. However, since that series, the Pirates have faced many ups and downs. Let me elaborate.

Before entering the 2016 season, one major concern of a Pirates’ fan could have been the rotation that they decided to bring north, which consisted of Francisco Lirano, Gerrit Cole, Jon Niese, Juan Nicasio, and Jeff Locke. You will not mistake this rotation with the Mets’ fab four or the Indians’ top three anytime soon. The other night, Jeff Locke surrendered 11 hits and eight earned runs in just three innings against a Padres offense who struggled to score a run in their opening series of the season. On Tuesday night, Liriano returned from a “hamstring injury” by giving up two homers and walking five. However, there is light at the end of the tunnel with former number-two overall pick Jameson Taillon and top prospect Tyler Glasnow nearing their debuts. Believe it or not, pitching may not be the Pirates’ primary concern at the moment.

In the past three years, as an avid fan of the Pirates, I have noticed an ongoing inability to move runners and take advantage of any sort of small-ball approach. Therefore, I decided to take a look at the numbers. Through the first 15 games of 2016, the Pirates are last in the league with 9.33 runners left on base per game. Minnesota comes in a distant second with 7.93 runners left on base per game. Now, I am very well aware of the small sample size. It is very easy to be overwhelmed by early-season statistics, such as Gerrit Cole starting with an 0-2 record and a 4.22 ERA, but we are only 15 games into a 162-game season and there are many more important statistics than ERA. While the Pirates are leaving the most runners on base per game, they are also sporting the highest team OBP (.380) in the league. Coming in second is the St. Louis Cardinals with a .348 team OBP. Due to the small sample size, I decided to take a look at the past two seasons where I have also noticed their inability to move runners.

In 2015, the Pirates came in dead last in all of baseball with 7.22 runners left on base per game. However, they sported a top-10 OBP of .323, which was not far behind the league’s best OBP of .340 by the Toronto Blue Jays. Lets take another step back. In 2014, the Pirates finished 29th in the league with 7.35 runners left on base per game. The only team to leave more runners on base that year was the Tampa Bay Rays (7.36). Surprisingly, the Pirates finished third in team OBP (.330) trailing only the Detroit Tigers (.331) and the Los Angeles Dodgers (.333).

Interpret this however you may like, but it is apparent that the Pirates lack a very important skillset of moving runners, or executing successful situational baseball. In the past three years, the Pirates have finished in the top 10 in stolen bases. While this statistic is by no means the only measure of team speed, it is very clear that the Pirates have some speed and athleticism in their lineup among guys like Andrew McCutchen, Starling Marte, Gregory Polanco, Josh Harrison, and Jordy Mercer. These are not guys that should be taken lightly on the base paths. According to Moneyball, Billy Beane and the Oakland A’s went after undervalued position players who had a knack for getting on base, thus, scoring more runs. So far, the Pirates are getting on base more than anybody this year. With better pitching performances from their rotation and moving runners more efficiently, whether that’s through more smallball or just better situational hitting, the Pirates could easily be one of the better teams in the league this year. Don’t lose hope too early, Pittsburgh.

Recently the New York Mets took the lead in the top of the first inning for the fifth straight game, setting the tone early in their 11-1 victory over the Philadelphia Phillies.  The Mets hitters looked extremely comfortable in the batter’s box, taking aggressive swings at good pitches all game.  The result was 11 runs all scoring through six home runs.  After hitting only two home runs in the first eight games of this season, the Mets have hit 17 home runs over their last five.

Every good team hits home runs, especially timely home runs.  However, great teams don’t need a lot of home runs.  Great teams live by the old adage, get on, get over and get in, meaning, get on base, advance on the base paths and score.

Since the wild card playoff system began in 1995, only two of 21 World Series championship teams finished in the top four in home runs during the regular season (2008 Phillies, 2009 New York Yankees).  However, during the same span of time, eight of 21 World Series championship teams finished in the top four in on-base percentage during the regular season, including 13 champions finishing in the top 10.

Home runs are an exciting, quick confidence boost for a batting lineup.  The only problem for a home-run-reliant team is home runs come in bunches.  Between facing MLB pitching every night and the natural difficulty in hitting a home run, sustaining home runs every game and the corresponding confidence is extremely difficult.

Conversely, a lineup with high on-base percentage forces the pitcher to uncomfortably pitch from the stretch more often and drives up pitch count which helps get the opposing starting pitcher out of the game earlier and into the opposing team’s weaker bullpen pitchers.

Currently, the Mets rank sixth in Major League Baseball with 19 home runs, two behind the third-ranked teams.  However, the Mets rank 21st in MLB in on-base percentage, 20th in batting average and have scored 56.6% of their total runs through home runs (30 of 53 runs).

Comparatively, the St. Louis Cardinals rank third in MLB with 21 home runs.  However, the Cardinals are second in MLB in on-base percentage, fifth in batting average and have scored 44.2% of their total runs through home runs (38 of 86 runs).

Additionally, the Mets are 24th in contact rate (percent of swings on which contact was made) and 29th on O-Contact rate (percent on which contact was made on swings outside the strike zone) according to FanGraphs.  What does that even mean?

A low contact percentage creates fewer balls in play resulting in a lower opportunity for the Mets to get hits and a greater challenge advancing runners along the bases.  The O-Contact rate shows the Mets aren’t hitting bad pitches, particularly two-strike pitches, well, a staple of many great teams (see 2015 Royals, recent Cardinals and Giants teams).  Making high contact percentages with pitches outside the strike zone lowers strikeout rates, forcing opposing pitchers to throw more pitches and puts additional pressure on the fielders to complete more defensive outs.

Additionally, in the nine games the Mets hit one home run or none, they averaged 2.9 runs per game.  In the other four games hitting two or more home runs, the Mets averaged 6.8 runs per game.  Obviously, runs per game will be higher when two or more home runs are hit but the disparity shouldn’t be as high as almost four runs or 2.3 times as high.

I’m not suggesting Mets hitters can’t manufacture runs through singles, extra-base hits and taking extra bases (not only by steals but going first to third on singles).  I’m not suggesting it’s time to panic.  I’m suggesting it’s something to pay attention to as the season progresses.

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

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

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

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

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

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

“Grit” in baseball has long been a gag for the saber crowd. Fire Joe Morgan was basically one long joke about how gritty David Eckstein was. And there’s good reason to distrust “grit.” Grit, hustle, guts — they’re unquantifiable (sabermetrician attempts to the contrary), often racially coded, and poorly defined skills. (Grit does predict great legal representation, though!)

Yet “grit” has evolved into a buzzword and teachable skill — one that social scientists suggest correlates with success in school, work, and life. Grit is defined by Prof. Angela Duckworth, who pioneered the field of “grit” research, as follows:

We define grit as perseverance and passion for long-term goals. Grit entails working strenuously toward challenges, maintaining effort and interest over years despite failure, adversity, and plateaus in progress. The gritty individual approaches achievement as a marathon; his or her advantage is stamina. Whereas disappointment or boredom signals to others that it is time to change trajectory and cut losses, the gritty individual stays the course.

Duckworth’s research suggests that grittiness corresponds with success in everything from spelling bees to West Point.

So why not in baseball? In a sport where we are constantly prophesizing how players develop, isn’t the predictive power of “grit” something we should be looking at? And can “grit” help us ID players who are more than meets the eye? Read the rest of this entry »

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

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

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

Repertoire

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

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

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

Verrett’s Four Keys to Success

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

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

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

Cause for Concern

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

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

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

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

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

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

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

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

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

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

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 1919 Philadelphia Athletics

OWAR: 33.3     OWS: 224     OPW%: .381     (53-87)

AWAR: 9.0       AWS: 107     APW%: .257   (36-104)

WARdiff: 24.3                        WSdiff: 116.4  

The “Original” 1919 Athletics outperformed the “Actual” squad by 17 victories with a staggering WSdiff of 116.4. The “Actuals” were reduced to a shadow of their former dynasty due to a variety of factors, primarily financial. The “Originals” featured second-sacker Eddie Collins (.319/4/80), the League-leader with 33 stolen bases. “Shoeless Joe” Jackson supplied a .351 BA with 31 doubles, 14 triples and 96 ribbies in his penultimate season. Their counterparts, Whitey Witt (.267/0/33) and Merlin Kopp (.226/1/12) were barely adequate. In addition to left field and second base, the “Originals” surpassed the “Actuals” at catcher and third base. Wally Schang furnished a .306 BA and pilfered 15 bags while Steve O’Neill contributed a .289 BA with 35 doubles. Home Run Baker (.293/10/83) bested Fred Thomas (.212/2/23) at the hot corner.

Eddie Collins placed runner-up to Joe Morgan in the All-Time Second Basemen rankings according to Bill James in “The New Bill James Historical Baseball Abstract.” “Original” Athletics teammates listed in the “NBJHBA” top 100 rankings include Baker (5^th-3B), Jackson (6^th-LF), Wally Schang (20^th-C), Jimmie Dykes (52^nd-3B), Steve O’Neill (54^th-C), Stan Coveleski (58^th-P), Stuffy McInnis (68^th-1B), Charlie Grimm (85^th-1B), Joe Dugan (88^th-3B), Jack Barry (90^th-SS), Bob Shawkey (95^th-P) and Amos Strunk (100^th-CF). George H. Burns (79^th-1B) and Terry Turner (92^nd-SS) round out the roster for the “Actuals”.

  Original 1919 Athletics                                                       Actual 1919 Athletics 

Stan Coveleski averaged 23 victories per season over a four-year stretch (1918-1921). “Covey” delivered a 24-12 mark with a 2.61 ERA for the “Originals” staff. Bob Shawkey fashioned a 2.72 ERA and a 1.186 WHIP to complement his 20-11 record. Herb Pennock aka “The Squire of Kennett Square” added 16 wins with a 2.71 ERA. The “Actuals” countered with Walt Kinney (9-15, 3.64), Jing Johnson (9-15, 3.61), Rollie Naylor (5-18, 3.34) and Scott Perry (4-17, 3.58).

  Original 1919 Athletics                                                       Actual 1919 Athletics

Notable Transactions

Shoeless Joe Jackson

July 30, 1910: the Philadelphia Athletics sent Shoeless Joe Jackson to the Cleveland Naps to complete an earlier deal made on July 23, 1910. July 23, 1910: The Philadelphia Athletics sent a player to be named later and Morrie Rath to the Cleveland Naps for Bris Lord.

August 21, 1915: Traded by the Cleveland Indians to the Chicago White Sox for a player to be named later, Ed Klepfer, Braggo Roth and $31,500. The Chicago White Sox sent Larry Chappell (February 14, 1916) to the Cleveland Indians to complete the trade.

Eddie Collins

December 8, 1914: Purchased by the Chicago White Sox from the Philadelphia Athletics for $50,000.

Home Run Baker

February 15, 1916: Purchased by the New York Yankees from the Philadelphia Athletics for $37,500.

Wally Schang

December 14, 1917: Traded by the Philadelphia Athletics with Bullet Joe Bush and Amos Strunk to the Boston Red Sox for Vean Gregg, Merlin Kopp, Pinch Thomas and $60,000.

Morrie Rath

July 23, 1910: Traded by the Philadelphia Athletics with a player to be named later to the Cleveland Naps for Bris Lord. The Philadelphia Athletics sent Shoeless Joe Jackson (July 30, 1910) to the Cleveland Naps to complete the trade.

September 1, 1911: Drafted by the Chicago White Sox from Baltimore (Eastern) in the 1911 rule 5 draft.

August 23, 1913: Purchased by Kansas City (American Association) from the Chicago White Sox.

September 20, 1917: Drafted by the Cincinnati Reds from Salt Lake City (PCL) in the 1917 rule 5 draft.

Steve O’Neill

August 20, 1911: Purchased by the Cleveland Naps from the Philadelphia Athletics.

Stan Coveleski

December, 1912: Purchased by Spokane (Northwestern) from the Philadelphia Athletics.

November 27, 1915: Sent from Portland (PCL) to the Cleveland Indians in an unknown transaction.

Bob Shawkey

June 28, 1915: Purchased by the New York Yankees from the Philadelphia Athletics for $3,000.

Herb Pennock

June 6, 1915: Selected off waivers by the Boston Red Sox from the Philadelphia Athletics.

Honorable Mention

The 1998 Oakland Athletics 

OWAR: 41.6     OWS: 306     OPW%: .510     (83-79)

AWAR: 28.7     AWS: 222     APW%: .457   (74-88)

WARdiff: 12.9                        WSdiff: 84.8  

Mark McGwire launched 70 four-baggers and drove in 147 runs for the “Original” 1998 Athletics. “Big Mac” placed runner-up in the MVP balloting while his protégé Jason Giambi (.295/27/110) completed his third season for the “Actuals”. Scott Brosius (.300/19/98) socked 34 two-base hits and earned his lone All-Star invitation as he outclassed Mike Blowers, who batted .237 with 11 dingers in his solitary campaign for the green-and-gold crew. Darren Lewis posted career-bests in runs scored (95) and RBI (63), a significant upgrade over “Actuals” center fielder Ryan Christenson (.257/5/40). Rickey Henderson, a member of the “Original” and “Actual” A’s roster in ’98, notched the American League stolen base title for the twelfth time in his career. “The Man of Steal” tallied 101 runs scored and a League-leading 118 bases on balls.

On Deck

What Might Have Been – The “Original” 1905 Beaneaters

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

It’s like Rob Deer and Gorman Thomas don’t even know this franchise anymore.  What happened to our free-swinging Brewers, the same ones that just two seasons ago had Carlos Gomez remarking, “It has to be, like, wayyy a ball for us to not swing…everybody here has the green light?”

Well, for one, a small sample size.

But, through mid-April in 2016, the Brewers have swung less than any other team in baseball.  This, after swinging the second-most in each of the past two seasons.  They’re swinging less at pitches out of the zone, and they’re swinging less at pitches in the zone, leading to sequences like this from Monday:

And then Domingo Santana also struck out looking to lead off the sixth!

So, to recap: we’re less than two weeks into the season and not even at the point where swing rate has stabilized.  But it sure looks like the Brewers are making a concerted effort to swing less, given the drastic fluctuations in their swing rates from the past couple of years:

Part of that must be the overhaul the organization has gone through in the past year.  Jean Segura and Carlos Gomez both swung at over half the pitches they saw in 2015, and their O-Swing% was north of the team average.  Adam Lind and Gerardo Parra also chased and drove the team’s O-Swing% up.  So it’s partially a function of a new team with a new front office that may place a higher premium for on-base guys.

But the holdover hitters from last year have also seen their swing rates decrease both outside the zone and overall.  Ryan Braun, Scooter Gennett, and Domingo Santana have thus far decreased their O-Swing% from last year’s totals by 10% or more in the early going.  Brewers beat reporter Tom Haurdicourt reported Manager Craig Counsell saying, “It’s an everyday message (to the hitters) and it’s really about swinging at good pitches.  It’s discipline. (Hitting coach) Darnell (Coles) is preaching that every day.”

This mix of the front office acquiring more on-base players and the on-field management working with the players on adjustments seems to be making an impact.  The Brewers are fifth in walk rate, after finishing in the bottom third each of the previous three seasons.

Whether this is an organizational philosophy change, or more a function of the players on the current roster remains to be seen.  Or, given the small sample size, this could look completely different in May, with the Brewers back to their free-swinging ways and me wondering why I didn’t use this time instead to plant those jalapenos I’ve been meaning to get around to, but now it’s too late and the harvest won’t come until at least September.

In the meantime this is something to watch for a young team with more organizational talent than Milwaukee has seen in a while, and that is sure to go through rough stretches in a rebuilding year.  The new and veteran Brewers are watching pitches, and we’ll watch with them, watching pitches.

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

The “results” stats that I used are:

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

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

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

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

The PD-SIERA leaders for 2015 were:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Steven Matz’s season debut quickly went south, with him giving up seven earned runs in the second inning en route to a 10-3 New York Mets loss against the Miami Marlins.  Matz exhibited one mechanic flaw leading to his lack of command, particularly in two-strike counts, resulting in the Marlins’ second-inning carousel around the bases.

Steven Matz (L, 0-1) 1.2 IP, 7 R, 6 H, 1 SO, 2 BB

Arrows were pointing up after watching a 1-2-3 first inning with fastball velocity at 95 mph, culminating in striking out one of Major League Baseball’s best power hitters, Giancarlo Stanton.

Unfortunately, Matz started the second inning breaking one of the cardinal rules of pitching: walking leadoff man Martin Prado.  When a leadoff hitter makes it to first base, he scores approximately 35% of the time.  Making matters worse, Matz walked the following batter, Chris Johnson.  Five of the next seven batters ground out hits, including a Giancarlo Stanton man-bomb home run to left field, knocking Matz out of the game.

The frustrating aspect for Matz and Mets fans alike was during all three Marlins RBI single at-bats, Matz was ahead in the count 1-2 or 2-2.  Matz proceeded throwing hanging curveball after hanging curveball.  Even in Marcell Ozuna’s pop-out, both two-strike pitches were hanging curveballs which thankfully Ozuna missed (Side note: Ozuna can’t hit an outside pitch….at all).  Obviously, Matz’s objective was not to hang curveballs or throw hittable two-strike pitches.  The reason lies in Matz’s release point.

Simply, Matz’s throwing arm lagged behind his body forcing his release point to be late, rushed and higher than normal as opposed to his normal release point out in front of his body.  This results in an inability for Matz’s throwing fingers to stay on top of the baseball.

Matz, and every other Major League pitcher, needs his fingers on top of the baseball at release, allowing his fingers to stay on top of the seams on the baseball.  This allows his fingers to manipulate the spin of the baseball at release, whether ripping down on the seams for a four-seam fastball or getting over the top of the baseball throwing a curveball.

Consequently, Matz’s fingers come around the seams of the baseball instead of over the seams of the baseball when throwing his curveball, resulting in a weak spin rate and a floating or hanging curveball.  Additionally, fastballs tend to sail high and towards the throwing arm side (up and to the left for Matz) out of the strike zone as seen in four straight fastballs during Prado’s leadoff walk.

Why Matz’s arm lagged is a separate question I couldn’t unveil through the TV broadcast.  Originally, Matz appeared throwing across his body, meaning his stride/planting leg lands too far left towards first base, blocking off his arm from releasing the baseball out in front of his body.  But this was not the case as Matz was landing with good alignment towards home plate.  Other reasons could include rushing his motion or opening his front shoulder and glove hand too soon but I didn’t see those either.

Whatever the reason, pitching on ten days’ rest is very difficult, especially for a starting pitcher in a rhythm and routine created during spring training.  Do not put too much stress in the results of this start.