Archive for May, 2014

Foundations of Batting Analysis – Part 1: Genesis

This was originally written as a single piece of research, but as it grew in length far beyond what I originally anticipated, I’ve broken it into three parts for ease of digestion. In each part, I have linked to images of the original source material when possible. There has been nothing quite as frustrating in researching the creation of baseball statistics as being misled by faulty citations, so I figured including actual copies of the original material would mitigate this issue for future researchers. Full bibliographic citations will be included for the entirety of the paper at the conclusion of Part III.

“[Statistics’] object is the amelioration of man’s condition by the exhibition of facts whereby the administrative powers are guided and controlled by the lights of reason, and the impulses of humanity impelled to throb in the right direction.”

–Joseph C. G. Kennedy, Superintendent of the United States Census, 1859

In a Thursday afternoon game in Marlins Park last season, Yasiel Puig faced Henderson Alvarez in the top of the fourth inning and demolished a first-pitch slider to straight-away center field. As Puig flipped his bat with characteristic flair and began to trot towards first base, remnants of the ball soared over the head of Justin Ruggiano and hit the highest point on the 16-foot wall, 418-feet away from home plate; Puig coasted into second base with a stand-up double.

Two months earlier, in another afternoon game, this time at Yankee Stadium, Puig hit the ball sharply onto the ground between Reid Brignac and second base causing it to roll into left-center field. Puig sprinted towards first base, rounding the bag hard before Brett Gardner was able to gather the ball. Gardner made a strong, accurate throw into second base, but it was a moment too late; Puig slid into second, safe with a double.

In MLB 13: The Show, virtual Yasiel Puig faced virtual Justin Verlander in Game Seven of the Digital World Series. Verlander had managed to get two outs in the inning, but the bases were loaded as Puig came to the plate. The Tiger ace reared back and threw the 100-mph heat the Dodger phenom was expecting. Puig began his swing but, at the moment of contact, there was a glitch in the game. Suddenly, Puig was standing on second base, all three baserunners had scored, and Verlander had the ball again; “DOUBLE” flashed on the scoreboard.

If the outcome is the same, is there any difference between a monster fly ball, a well-placed groundball, and a glitch in the matrix?

Analysis of batting presented over the past 150 years has suggested that the answer is no – a double is a double. However, with detailed play-by-play information compiled over the last few decades, we can show that the traditional concepts of the “clean hit” and “effective batting” have limited our ability to accurately measure value produced by batters. I’d like to begin by examining how the hit found its way into the baseball lexicon and how it has impacted player valuation for the entire history of the professional game.

The earliest account of a baseball game that included a statistical chart, the first primordial box score, appeared in the 22 October 1845 issue of the New York Morning News edited by J. L. O’Sullivan. This “abstract” recorded two statistics—runs scored and “hands out”—for the eight players on each team (the number of players wasn’t standardized to nine until 1857). Runs scored was the same as it is today, while hands out counted the total number of outs a player made both as a batter and as a baserunner.

For the next two decades, statistical accounting of baseball games was limited to these two statistics and basic variations of them. Through the bulk of this period, the box score was little more than an addendum to the game story – a way to highlight specific contributions made by each player in a game. It wasn’t until 1859 that a music teacher turned sports journalist took the first steps in developing methods to examine the general effectiveness of batters.

Henry Chadwick had immigrated to Brooklyn from Exeter, England with his parents and younger sister a few weeks before his 13th birthday in 1837. He came from a family of reformists guided by the Age of Enlightenment. Henry’s grandfather, Andrew, was a friend and follower of John Wesley, who helped form a movement within the Church of England in the mid-18th century aimed at combining theological reflection with rational analysis that became known as Methodism. Henry’s father, James, spent time in Paris in the late-18th century in support of the French Revolution and stressed the importance of education to learn how to “distinguish truth from error to combat the evil propensities of our nature.” Henry’s half-brother, Edwin, 24 years Henry’s senior, was a disciple of Jeremy Bentham, whose philosophies on reason, efficiency, and utilitarianism inspired Edwin’s work on improving sanitation and conditions for the poor in England, eventually earning him knighthood. This rational approach to reform that was so prevalent in his family will be easily seen in Henry Chadwick’s future promotion of baseball.

Chadwick’s work as a journalist began at least as early as 1843 with the Long Island Star, when he was just 19 years old, but he worked primarily as a music teacher and composer as a young adult. By the 1850s, his focus had shifted primarily to journalism. While his early writing was on cricket, he eventually shifted to covering baseball in assorted New York City and Brooklyn periodicals. Retrospectively, Chadwick described his initial interest in promoting baseball, and outdoor games and sports in general, as a way to improve public health, both physically and psychologically. In The Game of Base Ball, published in 1868, Chadwick recounted a thought he had had over a decade earlier:

“…that from this game of ball a powerful lever might be made by which our people could be lifted into a position of more devotion to physical exercise and healthful out-door recreation than they had hitherto, as a people, been noted for.”

From his writing on baseball during the 1850s, Chadwick became such a significant voice for the sport that, in 1857, he was invited to suggest amendments at the meeting of the “Committee to Draft a Code of Laws on the Game of Base Ball” for a convention of delegates representing 16 baseball clubs (two of which were absent) based in and around New York City and Brooklyn. The Convention of 1857 laid down rules standardizing games played by those clubs, including setting the number of innings in a game to nine, the number of players on a side to nine, and the distance between the bases to 90 feet. The following year, another convention was held, now with delegates from 25 teams, which formed the first permanent organizing body for baseball: the National Association of Base Ball Players (NABBP).[i] The “Constitution,” “By-Laws,” and “Rules and Regulations of the Game of Base Ball” adopted by the NABBP for that year were printed in the 8 May 1858 issue of the New York Clipper.

As the rules were being unified among New York teams, the methods used to recount games were evolving. By 1856, early versions of the line score, an inning-by-inning tally of the number of runs scored by each team, were being tested in periodicals, like this one from the 9 August issue of the Clipper. On 13 June 1857, the Clipper included its first use of a traditional line score for the opening game of the season between the Knickerbockers and the Eagles.[ii] In August 1858, Chadwick—who by this time had become the Clipper’s baseball reporter—began testing out various other statistics, noting the types of outs each player was making and the number of pitches by each pitcher. A game on 7 August 1858, between the Resolutes and the Niagaras, featured 812 total pitches in eight innings before the game was called due to darkness.

In 1859, Chadwick conducted a seasonal analysis of the performance of baseball players—the first of its kind. In the 10 December issue of the Clipper, the Excelsior Club’s performance during the prior season was analyzed through a pair of charts titled, “Analysis of the Batting” and “Analysis of the Fielding.” Most notably, within the “Analysis of the Batting” were two columns, both titled “Average and Over.” These columns reflected the number of runs per game and outs per game by each player during the season – the forebears of batting average. The averages were written in the cricket style of X—Y, where X is the number of runs or outs per game divided evenly (the “average”) and Y is the remainder (the “over”). For instance, Henry Polhemus scored 31 runs in 14 games for the Excelsiors in the 1859 season, an average of 2—3 (14 divides evenly into 31 twice, leaving a remainder of 3). Runs and outs per game became standard inclusions in annual batting analyses over the next decade.

These seasonal averages marked a significant leap forward for baseball analysis, and yet, their foundation, runs and outs, was the same as that used for nearly every statistic in baseball’s brief history. It’s important to note that the baseball players and journalists covering the sport in this period all generally had a cricket background.[iii] In cricket, there are three possible outcomes on any pitch: a run is scored, an out is made, or nothing changes. When the batter successfully moves from base to base in cricket, he is scoring a run; there are no intermediary bases states like those that exist in baseball. Consequently, the number of runs a cricket player scores tends to be a very accurate representation of the value he provided his team as a batter.

In baseball, batters rarely score due solely to their performance at the plate. Excluding outside-the-park home runs, successfully rounding the bases to score a run requires baserunning, fielding, help from teammates, and the general randomness that happens in games. It was 22 years after the appearance of that first box score in the New York Morning News before an attempt was made to isolate a player’s batting performance.

In June 1867, Chadwick began editing a weekly periodical called The Ball Players’ Chronicle – the first newspaper devoted “to the interest of the American game of base ball and kindred sports of the field.” To open the first issue on 6 June, a three-game series between the Harvard College Club and the Lowell Club of Boston was recounted. The deciding game, a 39-28 Harvard victory to win the “Championship of New England,” received a detailed, inning-by-inning recap of the events, followed by a box score. The primary columns of the chart featured runs and outs, as always. What was noteworthy about this box score, though, was the inclusion of a list titled “Bases Made on Hits,” reflecting the number of times each player reached first base on a clean hit. Writers had described batters reaching base on hits in their game accounts since the 1850s, but it was always just a rhetorical device to describe the action of the game. This was the first time anyone counted those occurrences as a measurement of batting performance.

Three months after this game account, in the 19 September issue of the Chronicle, Chadwick explained his rationale for counting hits in an editorial titled “The True Test of Batting”:

“Our plan of adding to the score of outs and runs the number of times…bases are made on clean hits will be found the only fair and correct test of batting; and the reason is, that there can be no mistake about the question of a batsman’s making his first base, that is, whether by effective batting, or by errors in the field…whereas a man may reach his second or third base, or even get home, through…errors which do not come under the same category as those by which a batsman makes his first base…

In the score the number of bases made on hits should be, of course, estimated, but as a general thing, and especially in recording the figures by the side of the outs and runs, the only estimate should be that of the number of times in a game on which bases are made on clean hits, and not the number of bases made.”

Taking his own advice, Chadwick printed “the number of times in a game on which bases are made on clean hits” side-by-side with runs and outs for the first time in the same 19 September issue of the Chronicle.[iv] Over the next few months, most major newspapers covering baseball were including hits in the main body of their box scores as well. The hit had become baseball’s first unique statistic.

By 1868, hits had permeated the realm of averages. On 5 December of that year, the Clipper included a chart on the “Club Averages” for the Cincinnati Club.[v] In addition to listing runs per game and outs per game for each player, the chart included “Average to game of bases on hits,” the progenitor of the modern batting average. All three of these averages were listed in decimal form for the first time in the Clipper. A year later, on 4 December 1869, “Average total bases on hits to a game” appeared as well in the Clipper, the precursor to slugging average.

As hits per game became the standard measurement of “effective batting” over the next few seasons, H. A. Dobson of the Clipper noted an issue with this “batting average” in a letter he wrote to Nick E. Young, the Secretary of the Olympic Club in Washington D.C.—and future president of the National League— who would be attending the Secretaries’ Meeting of the newly formed National Association of Professional Base Ball Players (NAPBBP).[vi] The letter, which was published in the Clipper on 11 March 1871 was “on the subject of a new and accurate method of making out batting averages.”

Dobson was a strong proponent of using hits to form batting averages, noting that “times first base on clean hits…is the correct basis from which to work a batting average, as he who makes his first base by safe hitting does more to win a game than he who makes his score by a scratch. This is evident.” He notes, though, that measuring the average on a per-game basis does not allow for comparison of teammates, as the “members of the same nine do not have the same or equal chance to run up a good score,” and it does not allow the comparison of players across teams, “as the clubs seldom play an equal number of games.” Dobson continues:

“In view of these difficulties, what is the correct way of determining an average so that justice may be done to all players?

This question is quickly answered, and the method easily shown.

According to a man’s chances, so should his record be. Every time he goes to the bat he either has an out, a run, or is left on his base. If he does not go out he makes his base, either by his own merit or by an error of some fielder. Now his merit column is found in ‘times first base on clean hits,’ and his average is found by dividing his total ‘times first base on clean hits’ by his total number of times he went to the bat. Then what is true of one player is true of all…In this way, and in no other, can the average of players be compared…

It is more trouble to make up an average this way than up the other way. One is erroneous, one is right.”

At the end of the letter, Dobson includes a calculation, albeit for theoretical players, of hits per at-bat—the first time it was ever published.

Thus, the modern batting average was born.[vii]

[i] The Chicago Cubs can trace their lineage back to the Chicago White Stockings who formed in 1870 and are the lone surviving member of the NABBP. The Great Chicago Fire in 1871 destroyed all of their equipment and their new stadium, the Union Base-Ball Grounds, only a few months after it opened, holding them out of competition for two years. If not for the fire, the Cubs would be the oldest, continually-operating franchise in American sports. That honor instead goes to the Atlanta Braves which were founding members of the National Association of Professional Base Ball Players (NAPBBP) in 1871 as the Boston Red Stockings.

[ii] Though the game was described as the “first regular match of Base Ball played this season,” it did not abide by the rules set forth in the Convention of 1857 that occurred just a few months prior. Rather, the teams appear to have been playing under the 1854 rules agreed to by the Knickerbockers, Gothams, and Eagles where the winner was the first to score 21 runs.

[iii] The first known issue of cricket rules was formalized in 1744 in London, England and brought to America in 1754 by Benjamin Franklin, 91 years before William R. Wheaton and William H. Tucker drafted the Rules and Regulations of the Knickerbocker Base Ball Club, the first set of baseball rules officially adopted by a club. Years later, Wheaton claimed to have written rules for the Gotham Base Ball Club in 1837, on which the Knickerbocker rules were based, but there is no existing copy of those rules. Early forms of cricket and baseball were played well before each of their rules were officially adopted, but trying to put a start date on each game before the formal inception of its rules is effectively impossible.

[iv] There is an oft-cited article written by H. H. Westlake in the March 1925 issue of Baseball Magazine, titled “First Baseball Box Score Ever Published,” in which Westlake claims that Chadwick invented the modern box score, one that included runs, hits, put outs, assists, and errors, in a “summer issue” of the New York Clipper in 1859. However, the box score provided by Westlake doesn’t actually exist, at least not in the Clipper. For comparison, here is the Westlake box score printed side-by-side with a box score printed in the 10 September 1859 issue of the Clipper. While the players are listed in the same order, and the run totals are identical (and the total put outs are nearly identical), the other statistics are completely imaginary.

[v] This club, featuring the renowned Harry Wright, became the first professional club in the following season, 1869, when the NABBP began to allow professionalism.

[vi] The NAPBBP is more commonly known today as, simply, the National Association (NA). However, before the NAPBBP formed, the common name for the NABBP was also the National Association.  It seems somewhat disingenuous after the fact to call the later league the National Association, but I suppose it’s easier than saying all those letters.

[vii] I immediately take this back, but only on a technicality. “Hits per at-bat” is the modern form of batting average, but at-bats as defined by Dobson are not the same as what we use today. Dobson defined a time at bat as the number of times a batter makes an “out, a run, or is left on his base.” In the subsequent decades after the article was published, “times at bat” began to exclude certain events. Notably, walks were excluded beginning in 1877 (with a quick reappearance in 1887 when they were counted the same as hits), times hit by the pitcher were excluded in 1887, sacrifice bunts in 1894, catcher’s interference in 1907, and sacrifice flies in 1908 (though, sacrifice flies went in and out of the rules multiple times over the next few decades, and weren’t firmly excluded until 1954).

Where is Matt Carpenter and What Have You Done With Him?

A few days ago, I tweeted out some data that I had parsed from Baseball Savant after I decided to see who had seen the most pitches outside of the strike zone get called strikes.  I found the leader of that unfortunate group to be none other than St. Louis Cardinals’ 2B/3B Matt Carpenter. After a sizable amount of interest in that tweet, I decided to look into Carpenter’s numbers a bit further to see if it had anything to do with Carpenter’s decline this year.

As of May 20th, Carpenter has been the victim of 81 pitches out of the zone that have been called strikes — a ratio of about 9.6% of pitches thrown. Next on that list is former Cincinnati Reds outfielder Shin-Soo Choo, hoodwinked 67 times (9.3%). However, two other hitters are seeing a slightly higher ratio of strikes out of the zone — Boston Red Sox outfielder Jackie Bradley, Jr. (9.9%) and Washington Nationals infielder Adam LaRoche (9.8%). Both of the aforementioned hitters have about 150 less plate appearances than Carpenter.

Could this honestly be the explanation as to why Cardinal Nation’s breakout star of 2013 isn’t anywhere near as good as he has been in the previous two seasons? To take it a step further, should we assume that there is a major umpiring conspiracy against Carpenter?

Not exactly.

I looked into this data further and I found that since 2008 (minimum 5000 pitches), there are thirty-eight other hitters within two percentage points of Carpenter’s current rate of 9.6%. The leader of that group is Oakland Athletics catcher John Jaso, who has faced 5731 pitches of which 546 were out of the zone and called strikes (9.5%). The miserable hitter who has fallen prey to the fallible umpire eye 1,324 times — the most in that time span — is Baltimore Orioles outfielder Nick Markakis (8.2%).

So let’s look a little closer at what’s going on with Carpenter in 2014. His BABIP sits at .331, well above the league average but nothing to get excited about because his career average is .348 — which can be considered stabilized after 1,100-plus at-bats. His batting average is currently .265; again, above the league average but well below his career mark of .300. Carpenter still manages to get on base consistently (.371 OBP) and his walk rate is actually three percent higher than his norm of 10.8%. Most importantly, he has yet to hit an infield fly; an indication that he’s making good contact and swinging the bat well.

Are pitchers attacking him differently? The answer again is no because there seems to be no variance in the types of pitches he’s seeing in 2014 compared to previous seasons.

Plate discipline would be the next logical place to go. Here, I’ve spotted something interesting — a Z-Swing rate of just over 50%. Only swinging at half the pitches he sees in the strike zone? Is this indicative of a lack of confidence? That kind of swing rate is bound to get a few extra ‘phantom’ strikes called on you. The league average swings in the zone for 2014 is a much higher 64.9%; Carpenter’s career ratio is 57.3%.

Has he lost his eye? His O-Swing rate is actually lower this year (along with his overall swing rate). He apparently wants to take more pitches and it hasn’t effected his ability to get on base regularly; still sporting a well above-average OBP of .371.

So here’s the biggie — his contact rates. An astounding 95.1% of swings in the zone result in contact and his general contact rate hasn’t varied at all from the past three seasons. You can cancel those requests for an eye doctor visit now. Need more proof? His whiff rate is a minuscule 3.9%.

Obviously when Carpenter sees a pitch he likes, he hits it. The problem seems to be what happens when he does.

I mentioned before that his BABIP is fairly high (currently 39th overall in baseball) and that typically correlates with an elevated batting average. Not the case with Carpenter and here is an example of why. Line drives fall for hits much more than any other type of contact. So far, Carpenter has 23 line-outs this year, highest in the majors. For a guy who is known for his extra-base hits (55 doubles in 2013), he relies on those to fall for hits and they aren’t. His wOBA has taken a major hit for that, down to a pedestrian .319 so far.

I wish I could tell you that this research would involve some sort of diagnosis of Carpenter’s struggle; there is none. His walk rate is up a bit, but he is striking out more (18.8%) than his average ratio of 15.9%. It could simply be that he might not be as good as he’s advertised. It could simply be a down year. But let me leave you with a one last piece of data.

Carpenter is a career .264 hitter in March/April. His average elevates to .321 during the month of May. So far, his average this May has risen slightly but not significantly. Its possible he has a major hot streak simmering on the back burner.

For the sake of Cardinal Nation, I hope that one of the most dynamic players in the game starts to have a shift in hitting abilities sooner rather than later. He’s a fun hitter to watch.

Pitch Win Values for Starting Pitchers — March/April 2014


The baseball pitcher is one of the few positions in all of team sports where a supreme talent can pretty much individually win a team a game.  A great hitter can be pitched around or not pitched to at all.  A quarterback is only as successful as his offensive line and defense allow him to be.  A great scorer in basketball can be double-, triple-, or quadruple-teamed (e.g. the Stephen Curry defense in the 2009 NCAA Tournament) as necessary.  Pitching is the only team sports endeavor where someone can complete a perfect game.  The term doesn’t even exist in other team sports.  You can roll a perfect game at the bowling alley.  You can play a Golden Set in tennis, but you can’t score a perfect game in basketball.  Even if you hit every shot you take, you could have always taken one more.  The closest thing in other team sports to the influence a dominate pitcher has is a goalie in hockey, but a goalie can only post a shutout.  Pitchers can post shutouts and not be perfect.  I imagine the same is true for goalies.  It is this unique aspect of pitching that makes it the most interesting position in all of sports to me.

For a few years, I’ve attempted multiple times to come up with a new way of determining the value a pitcher provides.  Even further than that, I’ve searched for a way to evaluate individual pitches in a pitcher’s repertoire.  FanGraphs provides linear weight values for pitch types, and they can be useful in determining the quality of a pitch.  The problem exists in understanding the numbers.  Sure, we know that, in the linear weight analysis of pitches, the greater value is the better pitch.  What exactly does a pitch being 15 runs above average really mean though?  One of the major tenets of sabermetric pitching analysis is that runs allowed in strongly influenced by the defense, and thus out of a pitcher’s control.  Why are we discussing pitch values as run values then?  The currency of baseball is the win.  When we talk about Mike Trout being a 10 win player or Clayton Kershaw being a six win pitcher, its not hard to explain to someone what that means.  Shouldn’t we then talk about pitch values in terms of wins as well?


The first step in determining the win value for a pitcher per FanGraphs WAR methodology is to determine the pitcher’s FIP.  For reference, here’s the formula for FIP.

FIP = ((13*HR)+(3*(BB+HBP))-(2*K))/IP+constant

In the formula, the constant is used to bring the value equivalent to league average ERA.  For the purposes of WAR, an adjustment is made to convert league average ERA into league average RA.  The constant used in this scenario will therefore adjust each pitcher’s FIP to league RA.  No adjustment will be made for individual leagues.  With that said, we must determine each of the six variables.

1.) Home Runs Allowed

This is the easiest factor to determine.  The fine folks over at Baseball Prospectus provide PitchF/x leaderboards for each of nine pitch types.  One of the things they tabulate is home runs allowed on a given pitch.  That simplifies our task a little.

2.) Walks Allowed

Once again, we can consult the PitchF/x leaderboards for this information, though not directly.  Yes, the PitchF/x leaderboards provide a column for walks, but this is the number of walks that ended with a certain pitch.  For our purposes, we’ll need to calculate expected walks based on the frequency of called balls.  Luckily, there’s a column for called balls to help us out.  Now, how should we proceed?  Well, maybe since four balls equal one walk we should just divide this number by four.  This isn’t correct though because even the best pitchers will only through something like 70% strikes.  In a 100 pitch outing, the divide by four methodology would yield 7.5 walks each game, which is only slightly ridiculous.  Clearly, the number we are looking for is not four.  According to FanGraphs, there were 28,172 balls thrown and 1,523 walks allowed by starting pitchers in March and April.  That’s a ratio of 18.50 balls per walk.  Back to our 30% example, that equates to 1.6 walks per 100 pitches, which is much more realistic.  For our purposes, one walk will be credited for each 18.50 balls thrown by a pitcher.

3.) Hit-by-Pitch

I have been unable to find any data from which to determine how many times a pitcher hit a batter with a certain pitch.  HBP is normally a small factor in the overall FIP equation though, so we will just assume zero hit-by-pitches.

4.) Strikeouts

Similar to the section on walks allowed, we cannot simply take the number of strikeouts tabulated in the PitchF/x leaderboards, as this is the number of strike threes on a certain pitch.  Once again, we have a tabulated value for called strikes, but we cannot simply divide by three.  First, swinging strikes need to be included.   Foul balls need to be included as well because they can count as strikes.  For our total strikes thrown, we can start by using Called Strikes + Swinging Strikes + Foul Balls.  Swinging strikes can be calculated by multiplying Whiff/Swing x Swing Rate x Pitches Thrown.  Foul balls can be calculated by multiplying Fouls/Swing x Swing Rate x Pitches Thrown.  Now, we need to determine the number by which to divide our total strikes.  Well, in March and April, 49,293 strikes were thrown by starters to record 4,057 strikeouts.  That’s a ratio of 12.15 strikes thrown per strikeout.  Should we use 12.15?  No, we shouldn’t because hits and batted ball outs are included in the 49,293 strikes thrown.  Starters allowed 4,647 hits in March and April.  They also pitched 4,780.2 innings, which converts to 14,342 outs.  If we subtract out strikeouts from the outs recorded, we’re left with 10,285 batted ball outs.  If we subtract, 10,285 and 4,647 from 49,293, we’re left with 34,361 strikes left.  34,361 strikes and 4,057 strikeouts is a ratio of 8.47 strikes per strikeout.  This is the divisor for which we were looking.

One thing we need to consider more closely though for our raw strike total is foul balls.  Some pitchers, such as Phil Hughes, have many more pitches fouled off than others.  This shouldn’t be used to arbitrarily increase a pitcher’s expected strikeout total.  To combat this, a pitcher’s foul rate on a pitch is compared to the league’s foul rate on that same pitch.  This is done by dividing the league rate by the pitcher’s rate.  Pitchers with less than average foul rates have all of their foul balls included.  For pitcher’s with higher than average foul rates, the foul ball total is reduced to the number of expected foul balls at the league average rate.

5.) Innings Pitched

In order to estimate the number of innings pitched with a certain pitch, we must first determine the number of total pitches each pitcher threw per inning.  By dividing the total number of pitches thrown by the total number of innings pitched, we are able to determine for each pitcher how many pitches were required on average to complete an inning.  By dividing the number of each individual pitch thrown by this ratio, we can estimate the number of innings thrown using a certain pitch.  For example, there were 77,465 total pitches thrown by starters in March and April.  Dividing this by our 4,780.2 IP from earlier gives us an average value of 16.20 pitches per inning.  If a pitcher had thrown his curveball 100 times, we would estimate he would have thrown 6.17 innings with his curveball.  Rather than using the league average value, the Pitch/Inning ratio is calculated for each individual pitcher.

6.) Constant

Using all of the starters pitches thrown in March and April tabulated by Baseball Prospectus, the league FIP subtotal calculates as 0.61.  League average RA for March and April for starters was 4.29.  For March and April, our FIP constant is 3.68.

After calculating the FIP for each pitch, we can then use park factors to make the numbers park neutral and run the FIP value through the FanGraph WAR methodology to get a win value for each pitch.  The pitcher’s overall win total is the sum of the individual pitch types.  Please note that the player win totals will most likely not match the standard win total calculated by FanGraphs.  This is because only nine pitch types are tabulated by Baseball Prospectus: four-seam fastball, sinker, cutter, splitter, curveball, slider, changeup, screwball, and knuckleball.  Pitches that could be classified as slow curves or eephus pitches are not included by Baseball Prospectus in their curveball leaderboards.  Any unclassifiable pitch is also not included.  Also, there is always inherent issues with pitch classification.  For example, Baseball Prospectus classified one C.J. Wilson pitch as a knuckleball.  Now, I find it incredibly hard to believe that Wilson decided to break out exactly one knuckleball over the first five weeks of the season having never been known to throw one before.  Simply put, we are at the mercy of the pitch classification system.


Four-Seam Fastball

Rank Pitcher Pitch Value Rank Pitcher Pitch Value
1 Nathan Eovaldi 0.8 163 Eric Stults -0.2
2 Zach McAllister 0.6 164 Josh Beckett -0.2
3 Robbie Ross 0.5 165 Ubaldo Jimenez -0.3
4 Michael Wacha 0.5 166 Dan Straily -0.3
5 Drew Hutchison 0.5 167 Wily Peralta -0.4


Rank Pitcher Pitch Value Rank Pitcher Pitch Value
1 Cliff Lee 0.7 142 Jake Peavy -0.2
2 Charlie Morton 0.5 143 Brandon McCarthy -0.3
3 Felix Hernandez 0.4 144 Erasmo Ramirez -0.3
4 Martin Perez 0.4 145 Dan Straily -0.3
5 Andrew Cashner 0.4 146 Mike Pelfrey -0.3


Rank Pitcher Pitch Value Rank Pitcher Pitch Value
1 Madison Bumgarner 0.4 68 Blake Beaven -0.1
2 Adam Wainwright 0.3 69 C.J. Wilson -0.2
3 Clay Buchholz 0.3 70 Felipe Paulino -0.2
4 James Shields 0.3 71 Franklin Morales -0.3
5 Erik Johnson 0.2 72 Johnny Cueto -0.4


Rank Pitcher Pitch Value Rank Pitcher Pitch Value
1 Tim Hudson 0.2 20 Charlie Morton -0.1
2 Brandon Morrow 0.1 21 Clay Buchholz -0.1
3 Masahiro Tanaka 0.1 22 Franklin Morales -0.1
4 Ricky Nolasco 0.1 23 Miguel Gonzalez -0.2
5 Jorge De La Rosa 0.1 24 Jake Odorizzi -0.2


Rank Pitcher Pitch Value Rank Pitcher Pitch Value
1 Jose Fernandez 0.5 145 Eric Stults -0.1
2 Adam Wainwright 0.3 146 Matt Moore -0.1
3 Sonny Gray 0.3 147 Ivan Nova -0.1
4 A.J. Burnett 0.3 148 Bronson Arroyo -0.2
5 Brandon McCarthy 0.2 149 Felipe Paulino -0.3


Rank Pitcher Pitch Value Rank Pitcher Pitch Value
1 Aaron Harang 0.3 110 Eric Stults -0.2
2 Ervin Santana 0.2 111 Wade Miley -0.2
3 Wily Peralta 0.2 112 Ricky Nolasco -0.3
4 Jeff Samardzija 0.2 113 Tim Lincecum -0.3
5 Jordan Zimmermann 0.2 114 Danny Salazar -0.4


Rank Pitcher Pitch Value Rank Pitcher Pitch Value
1 John Danks 0.3 146 Bronson Arroyo -0.2
2 Chris Sale 0.3 147 Mike Leake -0.2
3 Stephen Strasburg 0.2 148 Bruce Chen -0.2
4 Cliff Lee 0.2 149 Matt Cain -0.3
5 Francisco Liriano 0.2 150 Wandy Rodriguez -0.4


Rank Pitcher Pitch Value
1 Hector Santiago 0.0


Rank Pitcher Pitch Value
1 R.A. Dickey 0.5
2 C.J. Wilson 0.0


Rank Pitcher Value Rank Pitcher Value
1 Nathan Eovaldi 1.0 171 Dan Straily -0.3
2 Adam Wainwright 1.0 172 Mike Pelfrey -0.4
3 Martin Perez 1.0 173 Ivan Nova -0.4
4 Cliff Lee 0.9 174 Felipe Paulino -0.5
5 Justin Verlander 0.9 175 Wandy Rodriguez -0.5

Pitch Ratings

One of the only issues with WAR is that it is a counting stat, so we’re very much tied to playing time (or in this case, number of pitches thrown).  It can also be useful to study, on a rate basis, the quality of a pitch.  Using the park adjusted FIP values used in the WAR calculations above, we can provide 20-80 scale values for each pitch based on the number of standard deviations above or below an average pitch.  The baseline used is the overall average pitch, not the average within a pitch type.  In other words, Jose Fernandez’s curveball will be evaluated against all pitches analyzed, rather than just other curveballs.  Only qualified pitches are shown.  To qualify, a pitcher had to throw an above average number of each pitch.  That is the pitch count had to exceed the total number of pitches within a pitch type divided by the total number of pitchers in a pitch type.

Four-Seam Fastball

Rank Pitcher Pitch Rating Rank Pitcher Pitch Rating
1 Nathan Eovaldi 59 73 Marco Estrada 40
2 Jonathon Niese 57 74 Homer Bailey 39
3 Jake Odorizzi 57 75 Eric Stults 39
4 Drew Hutchison 57 76 Bartolo Colon 39
5 C.J. Wilson 57 77 Dan Straily 32


Rank Pitcher Pitch Rating Rank Pitcher Pitch Rating
1 Dallas Keuchel 60 57 Trevor Cahill 38
2 CC Sabathia 60 58 Francisco Liriano 38
3 Cliff Lee 59 59 Jake Peavy 36
4 Felix Hernandez 57 60 Lucas Harrell 36
5 Charlie Morton 56 61 Mike Pelfrey 33


Rank Pitcher Pitch Rating Rank Pitcher Pitch Rating
1 Clay Buchholz 59 27 Lance Lynn 43
2 Phil Hughes 59 28 Tim Hudson 43
3 Bruce Chen 57 29 David Price 35
4 Scott Feldman 57 30 Franklin Morales 30
5 Corey Kluber 57 31 Johnny Cueto 25


Rank Pitcher Pitch Rating Rank Pitcher Pitch Rating
1 Brandon Morrow 57 8 Tim Lincecum 44
2 Tim Hudson 55 9 Ubaldo Jimenez 44
3 Masahiro Tanaka 52 10 Danny Salazar 41
4 Jorge De La Rosa 51 11 Jake Odorizzi 30
5 Kyle Kendrick 47 12 Miguel Gonzalez 28


Rank Pitcher Pitch Rating Rank Pitcher Pitch Rating
1 Jose Fernandez 61 56 Jonathon Niese 38
2 Kyle Lohse 60 57 Clay Buchholz 37
3 Stephen Strasburg 58 58 Ivan Nova 37
4 Tommy Milone 58 59 Madison Bumgarner 37
5 Jordan Lyles 58 60 Bronson Arroyo 35


Rank Pitcher Pitch Rating Rank Pitcher Pitch Rating
1 Michael Pineda 59 48 Drew Hutchison 38
2 Max Scherzer 59 49 Wade Miley 37
3 Aaron Harang 59 50 Eric Stults 28
4 Jordan Zimmermann 59 51 Ricky Nolasco 28
5 Jeff Samardzija 59 52 Tim Lincecum 20


Rank Pitcher Pitch Rating Rank Pitcher Pitch Rating
1 Roberto Hernandez 60 58 Madison Bumgarner 35
2 Stephen Strasburg 60 59 Bronson Arroyo 31
3 Robbie Erlin 59 60 Mike Leake 22
4 Yordano Ventura 58 61(t) Bruce Chen 20
5 Brett Oberholtzer 58 61(t) Matt Cain 20


Rank Pitcher Pitch Rating
1 Hector Santiago 46


Rank Pitcher Pitch Rating
1 R.A. Dickey 53
2 C.J. Wilson 39


Well, there we have it.  By valuing his pitches, Nathan Eovaldi was the most valuable pitcher in MLB in March and April, and Wandy Rodriguez was the least valuable.  The most valuable pitch was Eovaldi’s four-seam fastball.  The most valuable offspeed pitch was Jose Fernandez’s curveball.   The least valuable pitch was Danny Salazar’s slider.  The least valuable fastball was Johnny Cueto’s cutter.

By ratings, the best overall pitch was Jose Fernandez’s curveball.  The worst overall pitch was a three way tie between Tim Lincecum’s slider and the changeups thrown by Bruce Chen and Matt Cain.  The best fastball was Dallas Keuchel’s sinker.  The worst fastball was Johnny Cueto’s cutter.

I feel this is the strongest iteration yet in my attempts to value individual pitches.  Hopefully, you agree.  Of course, similar analysis could be done on relievers.  I would expect more extremes, especially in the 20-80 ratings from relievers.

Trade Retrospective: Jonathan Broxton to Reds

The Reds are never known for making a lot of moves at the trade deadline — they make the majority of their moves during the offseason. This was one exception to Walt Jocketty’s past trades and it caught many people by surprise. When it was known that Broxton was likely to be traded, many people thought that it might be the Rangers or the Orioles or the Giants and out of nowhere, the Reds pick him up.

While Broxton was a good pitcher, the Reds gave up some very solid talent to acquire him, giving up both Donnie Joseph and J.C. Sulbaran for a pitcher who everyone knew would not be the closer for the Reds. Many, including myself, thought that this was immediately a bad deal for the Reds. A year and ten months after this deal; this piece is going to cover how the trade looks now and how it could potentially look like in the future.

From the Royals’ perspective:

Losing Jonathan Broxton was not only good for them; it turned out to be great for them. It was incredibly likely that he was going to leave them anyway at the end of the season when he hit free agency but they were able to receive not one but two prospects for him. The better of the two prospects is Donnie Joseph.

Donnie Joseph made his Major League debut last year, coming out of the bullpen on July 11, 2013 for the Kansas City Royals, pitching .1 innings and walking one. He was up only briefly for a little bit before being sent down and then coming right back up in September. While in the majors, he threw 5.2 innings in 6 games, struck out 7 batters, walking 4, giving up 4 hits, and not allowing any runs. Before that, he had a very successful minor league career. He has managed to strike out a lot of batters in the minors while also managing to limit the homers. In Triple A (2012-2013), he had a 12.06 K/9 in Triple A using only two pitches, a fastball that he can throw that will top out at about 92 mph and a lights out slider that he can throw around 85 mph. Part of what makes his stuff so good is his delivery. His delivery is very unorthodox and it makes his slider all the more deadly. What Joseph does is he slows himself down and holds his arm at such an angle that it is tough for the left handed batter to get a good read on him.

Where Joseph struggles is with his control. In those years in Triple A, he averaged about 5.98 BB/9 and while he kept the home run numbers down with only allowing 6 homers in his 93.3 innings (good for a .58 HR/9). He will not be a starter in the majors as neither in the minors nor in the majors did he ever start even one game, but he doesn’t project to be a lefty only kind of pitcher. His stuff indicates that he could face right handed batters in the majors. He looks to become a great piece to one of the already best bullpens in all of baseball.

The other prospect, Juan Carlos (J.C.) Sulbaran is one who definitely needs some polishing up before he can be considered anything other than a prospect. The potential is there for him, but having been in the Minor Leagues for five years, and at the not as young anymore age of 24, he could start to see an opportunity at reaching the Majors start to slip away. His problem has been control or lack thereof. In 2013 at Double A, he had a 5.44 BB/9 but only a K/9 of 5.05. He also tends to give up his fair share of home runs too, having given up 1.75 HR/9 at the Double A level in 2013 as well. He used to be better at striking out people than he is now but his strikeout rate has been on a sharp decline while his walks and home run rates have not been going anywhere. The Royals are looking to turn him into a starter but if he can’t find his control, then he will just become a lost prospect who never panned out.

Part of this trade that many people don’t think about is the door that it opened. Trading Broxton allowed the Royals to look into their bullpen, pull Greg Holland out, and place him in the role of closer and Holland has been nothing short of exceptional since then. Since the start of the 2012 season, only Craig Kimbrel has registered a higher WAR than Holland as a relief pitcher (Kimbrel had a 6.3 WAR to Holland’s 6.0). Holland limits home runs (.46 HR/9 in his career), limits walks (3.32 BB/9 but that number has been going down over his past three seasons), and have always struck out a ton of batters (12.34 K/9 and that number is only going up). All these numbers factor into his 1.80 FIP since 2012 that is only topped by Craig Kimbrel’s 1.32 FIP. By sending Broxton to Cincinnati, the Royals created a vacancy in the closer role that they knew they would eventually need to fill (as Broxton would eventually become a free agent at the end of that season) but by shipping him out mid-season, they were able to test out how Holland would handle the ninth inning in a lost season and he fit in beautifully which provided them a solid closer for when they would be a better team the next season.

From the Reds’ perspective:

When pitching Jonathan Broxton hasn’t been bad but that is about all that I can say positive about Broxton. The Reds acquired him to be a setup man and then all of a sudden signed him to one of the biggest contracts for a relief pitcher overall, let alone a relief pitcher who isn’t even assigned to be a closer. And as if it couldn’t get any better (note the sarcasm), he has been injured for a large part of his tenure as a Reds player. He was injured for a large part of 2013 with a right elbow flexor and only wound up throwing 30.2 innings with them that season. Then in 2014 took a while coming back off the DL after undergoing right forearm surgery. When he has pitched with the Reds, he hasn’t been bad but the time that he has pitched has been very limited. There are other signs that are concerning involving the future of Broxton.

The days of Broxton being that dominant pitcher with the electric fastball on the mound are over but he can still be a solid pitcher if and only if he changes his approach to pitching. His K/9 has been progressively going down since 2010 when it was 10.54 as in 2013 it was only 7.34. His BB/9 for the most part have remained consistent, sitting at above 3 BB/9 for most of his career and he is still good at limiting the home runs which is a good sign. However, most pitches who don’t strike out a lot of batters have ground ball rates over 50%. His groundball rates have for the most part always been around 45% which aren’t bad but it should be lower as he starts losing strikeouts.

A contributing factor to the reduction in strikeouts is his fastball velocity heading downhill while his off speed pitches haven’t changed speeds. So far in 2014, his fastball has averaged about 92.8 mph and while his slider has lost speed as well (being at about 85.6 mph), his changeup velocity is at 89.9 mph, leaving a difference in velocity between fastball and changeup of 2.9 mph. And while he only throws his changeup 2.7% of the time, there should be a greater difference in speed between the fastball and changeup otherwise it will be much easier for the hitters to hit off of him. Broxton is clearly heading downhill and the Reds definitely got the worse end of this trade.

When the Reds made this trade, it resembled the Sean Marshall deal too much for me not to know Jocketty’s intention which was to extend Broxton after making the trade. Too often I have seen Walt Jocketty trade for a player in his contract year, giving up a lot of talent and then try to extend the player in his contract year. Like with Marshall, this deal isn’t looking too good for the Reds. They signed Broxton to a three year, $21 million deal that the Reds are only halfway through regretting. And while the Royals didn’t necessarily come out as much on top as they could have with this deal, it is easy to see that the Royals got the better of this deal.

The Greatest Cardinal Catcher

Has Yadier Molina been great enough to get the title for the greatest Cardinal Catcher ever to play? Not quite. He is number 2, behind one of the most underrated catchers of all time. He still has to get past Ted Simmons, which he will probably do in a short time.

But until then, Ted Simmons it is.

Arguably a top 10 catcher to ever play the game, and probably a top 5 offensive catcher at that.  A player that had a wonderful 10 year stretch who unfortunately dropped off at the end of his career. A prized bat although only average at best defensively to below average, he posted great numbers in a 10 year peak that is hard to beat for any catcher. This is a player who should easily be in the Hall of Fame, but in his first and only ballot, he only received 3.7% of the votes.

From the years 1971 to 1980, he was almost unstoppable for a catcher, his lowest wRC+ in a season was 113, while his average for the stretch was 128. In comparison, Johnny Bench’s career wRC+ is 125. In a four year stretch, he averaged 138 wRC+. Fantastic numbers for a catcher. Only Mike Piazza and Joe Mauer have really been above that mark for any consistent time

His lowest WAR during this time was 3.8, and he had 5 seasons with 5.0 + WAR. Ernie Lombardi, who is in the Hall, only had 1 season with 5+ WAR. Mickey Cochrane, another Hall of Fame catcher, had 4 seasons with 5.0 + WAR. He is the 11th-best catcher by WAR, ahead of guys like Gabby Harnett.

From a traditional standpoint, he has raked up 2472 hits, second all-time for catchers. Also, 248 home runs, and while that is low for any other position, it puts him 10th for catchers. 1074 runs scored, good for 6th all time. 2nd in RBIs with 1389. He ranks up pretty well in the traditional stats was well as the more advanced metrics. And he did all of this before Mike Piazza, the greatest offensive catcher, ever sniffed at playing at the major league level, making his numbers historic as well.

It’s hard to imagine a guy so dominant at his position like this not in the Hall. Well, like I said earlier, he completely dropped off. In his last five seasons, his highest wRC+ was only 103, with his lowest at 60. Highest WAR was 1.0 while his lowest was -2.4. And he was always considered bad behind the plate.  During his great time as a catcher, 92% of the time he played was as a catcher. In his later years, all that time played caught up to him. Injuries plagued his career after he left St. Louis, only playing more than 150 games once in a season. While with St. Louis, he played over 150 games 9 times.

This is a player who just became overlooked. Not even sniffing at becoming a HOFer, even when he had the stats to make it. He is not even in the St. Louis Cardinals team Hall of Fame. Although a Veterans Committee hopefully will add Simmons to the Hall where he belongs, who knows when that will happen?

I don’t believe he is a Johnny Bench or Berra, but he was a fantastic catcher for the Cards, and deserves to be in the Hall. Especially when catchers like Ernie Lombardi are in it now.

All Your Bases are Belong to Brian Dozier

Taking a look at last year’s most valuable baserunners, not a lot jumps out as being unusual. You’ve got Jacoby Ellsbury, who stole 52 bases. You’ve got Eric Young and Elvis Andrus, who each stole at least 40. You’ve got Mike Trout, who stole 33 and, like, isn’t a human. And then you’ve got Alcides Escobar, who has stolen 35 in the past and still managed to swipe 22 despite having the lowest on-base percentage in baseball.

Thing is, baserunning value doesn’t come solely from successful and unsuccessful steal attempts. That is a big part of it, yes, but there is something to be said about the ability to take the extra base that a less aggressive or less aware baserunner might not take. Matt Carpenter only stole three bags last year and was more valuable on the bases than speedster Alejando De Aza, who stole 20.

Take a look at this year’s early most valuable baserunners and, unsurprisingly, Dee Gordon and his eye-popping 24 steals tops the list. The name after that, though, stands out as a little unusual.

Brian Dozier.

When you think of Brian Dozier, you probably don’t think of a burner. You probably think more along the lines of “non-prospect middle infielder with surprising power and mediocre on-base skills.” Now, Dozier did steal 23 bases in his first season-and-a-half in the big leagues and his 12 steals already this year are tied for fourth. However, that’s half as many as Gordon and they have nearly identical baserunning values. That’s only one more steal than Andrus , and Dozier’s baserunning value is nearly double Andrus’. Dozier clearly is doing something besides stealing bases that is making him the most valuable baserunner in the American League.

Using the incredible, amazing Baseball-Reference Play Index, I was able to identify 25 instances this season in which Brian Dozier took an extra base. Some of them were ordinary, but some were not. Let’s take a look at some of the ones that were not:

OK, this one’s not really out of the ordinary, but that’s why I’m getting it out of the way now. Brian Dozier does this, like, all the time. It’s one thing to go first-to-third on singles to right field. Dozier goes first-to-third on singles to center, regularly. I could have put five or six examples of this exact thing happening, but that would just be silly. Just trust me when I say if someone hits a single to the outfield and it’s not a hard liner to left, Brian Dozier is probably going to just put his head down and go first-to-third.

Again, it’s one thing to tag and advance when the ball is hit to the opposite side of the field. Far less often do you see a guy tag and advance to the base which is closest to the outfielder that caught it. Now, to be fair, the ball hit to Desmond Jennings was pretty deep in center and Michael Brantley was moving back when he caught his. But it’s more about the fact that Dozier is able to recognize these things and know his speed well enough to take the extra base.

Here we have a couple of ground ball singles to left field in which Dozier scored from second. These are the type of things that, when they happen in the midst of a game, can easily go unnoticed. But when they happen repeatedly over the course of a season, they really add up. Neither of these are super aggressive displays of baserunning, but they were hit to corner outfielders, who are closer to home plate than the center fielder, and not everyone scores these runs that Brian Dozier scored for the Twins.

Now for the fun stuff:

Here, Manny Machado almost makes an incredible play at third base to prevent a Brian Dozier infield hit. However, “almost incredible” sometimes become troublesome when you have to stretch the limitations of your physical ability to do so. That was the case for Machado on this play, and the ball skips away from the first basemen, though just barely. I don’t know if Dozier didn’t realize how little the ball actually skipped away, or if he just felt like being aggressive. Either way, it worked out and he turned a slow chopper to third into a double.

Here, Wade Davis decidedly did not have to stretch the limitations of his physical ability to make this play, yet it still resulted in an error. Again, the ball really didn’t skip that far away. Again, Brian Dozier didn’t care and took the extra base anyway. This one resulted in a run that he scored from second base when the ball barely made it to the pitchers mound.

Here we find, again, Brian Dozier scoring from second on a ball that never left the infield. This one happened just last week. Now, I don’t know how much baserunning goes into pre-series scouting reports, but if it does, Asdrubal Cabrera should have known that one of the most aggressive – and successfully aggressive – baserunners in the league was on second base. Either way, Cabrera gave up on the play and turned his back on home plate just long enough for Dozier to manufacture a run with his legs.


This one doesn’t say much about Dozier, as pretty much anyone in baseball would have scored from third on that. What’s humorous is Puig, in the first inning of a 0-0 ballgame, bypassing the cutoff man and throwing all the way home, nearly from the warning track, allowing every runner to advance in the process.

So what about the times Dozier has been thrown out? Surely, with a baserunner as aggressive as Dozier, he is bound to misjudge a ball or his own speed every now and then and cost his team an out. Let’s look at all the times Dozier has made an out on the bases this year:

And that’s it. The first one, Dozier was originally called safe until Don Mattingly successfully overturned the call with a challenge. Either way, it wasn’t the fault of Dozier being overaggressive or really Dozier’s fault at all. Nothing you can really do in that scenario. The second one, Dozier got a little aggressive, but the Twins had just taken a 1-0 lead in the 10th and he was likely running on any ground ball contact. It was a mistake, but it wasn’t an entirely costly mistake given the situation.

So there you have it. That’s how a guy like Brian Dozier can be among the most valuable baserunners in the MLB despite not being a premier base-stealer. There is being aggressive, and there is being smart with your aggression. Dozier has been able to take the extra base as often as any player in baseball and only has one real mistake to show for it. Last season, Dozier impressed with his surprising power. This season, the power has continued, but what he has done on the bases may be even more impressive.

The Dave Cameron Rules: A Manager’s Guide

A few days ago Dave Cameron published a post outlining some wild new rules for an alternative baseball. I missed it at the time, since I am on holiday in Sweden, but one Wi-Fi hotspot later, I was walking the streets of Stockholm thinking about the Dave Cameron Rules.

This post will make no sense to you unless you read the idea for “Daveball”, so go do that now. In it he asked a number of questions about what managers would do. This is my reply.

Overall Season Strategy

If every current game is divided by 3, the season schedule will be 486 games long. Playoff teams will lose 200 contests a year. The dramatically lower stakes make it easier to deliberately lose games.

Suppose you are facing Jose Fernandez. He will start Game 1 and probably continue to Game 2. Your own available pitchers are a mixed bag, so you save the best ones until the game(s) after Fernandez departs. As with bunts, every manager will need to calculate the risk and reward of trading unlikely wins for increased odds in another.

I also see a need for a new rule restricting roster moves to one time per day. (Not one move; one time.) This closes a new loophole wherein teams can call up a player for one three-inning game only. Not many teams have minor leaguers nearby to do this, but Texas, for example, could have an AA player report to Arlington instead of Frisco, call him up for Game 2, and have a spent pitcher hide in the clubhouse being “demoted”. This would give an unfair advantage to the few teams for whom this possibility exists.


I see options for a manager under these rules. Broadly speaking, there are three. The first is only modest changes to status quo, such as bringing high quality relievers in at the sixth inning as well as the ninth.

The second option is to convert current mediocre starters into one-game pitchers. Consider the Washington Nationals, who have four pitchers capable of throwing two games in a day, and five pitchers, either borderline starters or long relievers, who could pitch one game a day well (Tanner Roark, Ross Detwiler, Taylor Jordan, Craig Stammen, Blake Treinen). Especially if you believe the weakness of a borderline starter is getting through a lineup the second time, they can suddenly become very valuable.

Here’s how to do it. (Listen up, Astros.) Convert a few of your guys and trade for some more. You could have around seven or even eight of these starters, plus relievers for the other innings and for getting out of trouble. The shorter starts will make these pitchers more effective. Today’s market for mediocre one-inning relief will transform into high demand for mediocre five-inning guys who can pitch effectively for three.

The third option is extreme: all short-outing guys, all the time. Every day, every pitcher only goes four or five outs. This would lengthen the games considerably, but on the other hand, fans could see a barrage of 98 mph high heat.

The major change to mound strategy will be an increased reliance on strikeouts and the near death of the intentional walk. I will explain this shortly.


Dave Cameron already pointed out several key changes to batting strategy: put all the best hitters at the top of the order, and pinch-hit early and often. (The pinch-hitter would actually function like a movable DH.) Sometimes it will be advantageous to work counts, but sometimes the short games will call for aggressiveness. Either way, the run-scoring environment will be very different. With a sudden surplus of decent pitching, and probably a slight increase in average velocity, batting will become harder.

Scoring, however, could be easier.


Under Dave Cameron’s rules, Billy Hamilton would become the most valuable player in baseball.

Here’s how it works. The logic of pinch-hitting for weak defenders, then returning them to the next game, applies to pinch-runners, too. If your slugger draws a walk, put in Billy Hamilton. Every time.

Let’s assume your team is fairly good, and has at least one baserunner in 95% of games. Billy Hamilton has scored about 62% of the time he reaches base, with an 83% steal success rate. To compare, Mike Trout has scored about 42% of the time he reaches. There are other factors at work, but I’m on holiday, so ignore them. Hamilton should be running for any player, if the situation demands it, but for sale of argument (and of me writing this on a phone) assume that in 95% of 486 games, Billy Hamilton increases your odds of scoring by 20%. That’s 92 additional runs per year, and not over replacement level, either. Suddenly an elite runner becomes the most valuable weapon in the game.

Three factors could limit the damage. First, managers could be dumb or unlucky and use runners at the wrong times. Second, defenses could invent some kind of wild new “no steals defense”. I have no idea what this would look like, but teams would be forced to try.

Finally, every team will acquire their own super-runner. (Currently a running-only player is a waste of bench space, but the opportunity to use him or her three times per game without penalty would change the math.) Oakland would call up Billy Burns. Some teams would sign actual Olympic sprinters, train them in fundamentals like pitch recognition and sliding safely, and set them loose. (This is how we would acquire the first female player.) If Usain Bolt breaks for second base, a catcher will throw to third to limit the damage.

More than anything else, the runners will change baseball. Intentional walks will never be used with one or zero men on base. Unintentional walks will force wild pitchers out of the league. Strikeouts will be a priority as the third-inning hitting strategy is simply to get on first base.


I couldn’t think of much here, except for almost universal use of the no-doubles defense (especially once the enemy has used his runner). Probably shifts would be more common.


Dave Cameron’s rules would accelerate some trends we already see in baseball: more strikeouts, more speed, more reliance on defense. But it would also inspire madness, like nine-man starting rotations comprised of suddenly valuable borderline starting pitchers, and female sprinters charging toward home plate on squeeze plays. The game would be unrecognizable and loony, but also a lot of fun. And Billy Hamilton would punch a ticket to the Hall of Fame.

Run, Don’t Walk, to Buy Pedro Alvarez Stock

At first glance, it looks like Pedro Alvarez is doing exactly what we thought he would this year. He’s hit 8 long balls and is sporting a Mendozian .210 average, which somehow falls below his pre-season expectations of being in the .230 range. Most fantasy baseball outlets are sounding alarms and wondering aloud how much longer owners can live with his team killing average. In reality though, Pedro is producing a familiar stat line but is getting there in a very different way and mostly through bad luck.

It still feels early in the season but there are already some stats that have stabilized and are now significant for evaluating how players are performing. For when statistics stabilize I’m using this terrific post from 2011 ( which is definitely worth a read on its own. The cliff notes needed for this article are that when statistics stabilize, they start to tell us more about a hitter’s current season than league averages do. Statistics regress to the mean but when a statistic stabilizes we equally weight an individual’s performance with the league average when creating future projections.

Pedro is at the 150 plate appearances plateau and three key statistics have already stabilized and are now telling us more about his performance this year than league averages or his career stats, they are swing percentage (swing%), contact rate (contact%), and strikeout rate (K%).

2014 Pedro is swinging at 44.4% of pitches. This is down from swinging at 50% of pitches last year and is close to being a career low (in his call up season his swing% was 43.7%). This doesn’t tell us all that much by itself. You can get yourself in bad counts by watching strikes go by just as much as you can by swinging at balls. But, Pedro is making contact with 73% of pitches, four points above his career 69.3% average and almost a full 7% higher than last season. A hitter’s swing% first stabilizes at 50 PAs and contact% stabilizes at about 70-75 PAs, and this shows Pedro turning into a more patient and more selective hitter. He’s actually swinging less often than the league average and while the league average contact rate is 79% this year, Pedro has much more power than your average hitter.

The third stat I want to look at is the big one, strikeout rate. In each of Pedro’s first four seasons in the majors he has posted a K% north of 30%. The league average K% ranged from 18.5% to 19.9% during that time, so Pedro really excelled at striking out. Pedro’s K% through 150 PAs this season is only 21% though. Now it just stabilized, so there will probably be some regression towards his career norm but this is 9% lower than his career rate and is only .4% higher than the league average this year. I’m expecting this to regress, at least somewhat, because a 9% drop in K% is too good to be true but Pedro has definitely improved in this area and even regressing to a 25% or 26% strikeout rate would be a significant improvement.

All of these stats might look good but Pedro is still batting an abysmal .210, what’s up with that. The biggest culprit is his .209 BABIP. BABIP doesn’t every stabilize, if Pedro’s reverted to his career average (.292) he’d have a batting average of .267, if it reverted to last year’s rate (.276) he’d be batting .256. Home runs are BABIP-proof, there’s nobody to field them, and Pedro’s is off to a great start with 8 already. More of the non-homers are going to start falling for hits and barring injury, Pedro looks to be good for 35+ HRs and closer to a .250 average. Every fantasy team can use that guy. So before his bad luck starts to end, run out and buy low on Pedro.

Ottoneu Tools: Advanced League Standings

Ottoneu Tools: Advanced Standings (Part One)

Whether you’re brand new to Ottoneu or a “seasoned” veteran in your fourth year, your league’s Standings page is likely to become your best (or worst) friend over the course of a given baseball season. However, if you often find yourself cheering or panicking based on just a few days’ worth of small but evolving linear weights data without the proper, broader context with which to make meaningful decisions about your team, you are not alone. Welcome to the Ottoneu “Advanced Standings” dashboard. The brainchild and early creation of Bill Porter (@wfporter1972), the Advanced Standings dashboard will provide you with the sabermetric performance data you want with the detail you need.

How It Works:

Before you get started you will need to download the current version of the Advanced Standings dashboard here ( Note: You will need the most up to date version of Excel to take full advantage of the dashboard features. Also, this Advanced Standings dashboard only works with FGPoints Ottoneu format leagues (for now).

While it may look overwhelming at first, the dashboard is designed to be easy to use. In fact, it’s designed to be updated quickly and often without requiring a lot of Excelmanship. With as little as two easy steps you will be able to see “inside” your league standings in a way not available on the website.

First, go to your league’s traditional STANDINGS page within Ottoneu. From the bottom right of the standings stats (begin just to the right of the last P/IP on the right hand bottom corner), highlight all standings data with your cursor (including team names). Do not export the standings to Excel. Also, do not highlight the headings bar that includes the column titles (AB, H, 2B, etc.). COPY this information and then go to the first tab (“Advanced Standings”) of the Excel dashboard. In cell A4 (1st team name in column), PASTE SPECIAL and select TEXT. When pasted, your league’s standings will populate this tab and you will have visibility of many advanced statistics tailored exactly to your league.

Second, to have more accurate league standings information, go to your league’s REPORT page within Ottoneu and at the bottom of the page highlight all the information (excluding the column headings) in the “Projected Games Played and Innings Pitched” section. Once selected, COPY this information (including team names), and PASTE SPECIAL – TEXT this data into Tab 2 (“Reports”) of the dashboard spreadsheet, in cell A2.

Yeah, it’s that easy.

In Part Two I will revisit some of the key features of the Advanced Standings Dashboard and how it can be best used to analyze your league  You can also learn how to go much deeper into these advanced standings from reading Bill’s recent post on this subject here ( Until then, enjoy playing with the dashboard tool. If you have questions or want access to some additional Ottoneu tools, feel free to DM me on Twitter @Fazeorange and I will send you a link to the Ottoneu Dropbox folder.


Beating the Shift (& Physics)

After reading some questions in Dave’s chat today (May 7), and in response to never-ending questioning from un-informed commentators across baseball, I wanted to provide what I think is a very simple explanation for why groundballs are so often pulled. Here goes:

In terms of the direction a ball travels after hitting a bat, there are three factors:

  1. Vertical contact point on the barrel – below the sweetspot of the barrel is a groundball, above the sweetspot is more of a flyball
  2. Horizontal plane at contact – is the bat pointed directly perpendicular to the angle of the pitch and batter’s body, is the batter’s swing out in front, or is he behind?
  3. Vertical plane at contact – is the bat plane directly parallel to the ground, pointing slightly up towards the sky, or pointing slightly down towards the ground?

To start, let’s fix two of the three factors above and leave the third factor as the variable. Let’s assume that since we’re talking about groundballs, factor 1 will be set so that the contact point is slightly below the sweetspot of the barrel, resulting in a groundball. Let’s also set factor 2 and assume the batter squares up the pitch, so that in the horizontal plane his bat makes contact with the ball when it is directly perpendicular to his body. And now let’s focus on factor 3, the vertical plane.

In practice, the vertical plane is already set. Batters (almost*) always make contact with their hands above the head of the bat, so that it is vertically pointing downwards. So given that we’ve set factor 1 to be below the sweetspot on the bat and factor 2 to be square horizontally, we know that the groundball WILL be pulled. Why? Let’s look at it at the extreme to illustrate the point.

Visualize the vertical plane being taken to its extreme, so that the bat is pointing directly downwards. Now, since we’ve set the other two factors in place, we know that the ball will make contact with the bat slightly towards the batters side (which would be below the sweetspot were the bat at a more normal vertical angle). Which way will the ball deflect? Always towards the pull side, and it may actually hit the batter. Now clearly, this is an exaggerated example, because a batter wouldn’t make contact with a ball while his bat is completely vertical. However, the same physics apply when the bat is pointed only slightly downwards vertically, just to a lesser degree. So the point that we’ve established is that there is a structural, physics-based reason that groundballs tend to be pulled, because the bat is (almost*) always pointed slightly downwards at contact.

With that established, let’s take a step back to factor 2. This is the factor which most heavily influences whether or not the groundball will actually be pulled. If the batter is late or behind on the pitch, than in the horizontal plane (factor 2) the bat will be pointed more backwards toward the catcher than if it were exactly perpendicular. In this case, the ball would be pushed the opposite way. On the opposite end of that spectrum, if the batter is early on the pitch and his bat is pointing more forwards towards the pitcher than backwards towards the catcher, the groundball will be pulled more extremely.

So how early or late the batter is on the pitch is clearly an important determinant in whether the groundball will be pulled, pushed, or hit right back at the mound. But remember what we’ve already established – there is a natural tendency for groundballs to be pulled because of factor 3. So if a batter is to take a groundball the opposite way, he must not only be late on the pitch (factor 2), but he must be late enough to overcome the natural pulling force caused by factor 3.  And the more his bat is pointed downwards, the larger that natural pulling force is. The lower and more inside the pitch is, the more the bat will likely be pointed downwards, meaning that the batter must be that much later on the pitch to push it the opposite way.

I’m sure a lot of you will read this and say “duh”, because it is all pretty intuitive and this is FanGraphs after all. But for those of you who have just learned something, any time you ask why a batter can’t just push his groundball away from the shift, remember that he’s having to overcome the natural laws of physics, and, per Dave at 12:58 this afternoon, “it’s not easy to do.”

* All analyses exclude the superhuman skills of Evan Gattis