MVP and Cy Young Prediction Update

As the 2012 regular season is now officially complete, it is a prudent time to revisit a couple of theories proposed in recent weeks that attempted to predict the winners of the MVP and Cy Young Awards. These theories do not represent who should be voted as the award winners, but attempt to identify who will be voted as the award winners.

The theory for the Most Valuable Player award stems from a player's performance in situations most likely to garner attention in highlight reels. These are situations with the game on the line, or those where runs are scored in general where the player is the batter responsible for those runs scoring. The original post discusses the theory in more detail. Here are the final tables showing how the top three MVP candidates from each league performed in highlight situations in 2012:

AL MVP Candidates, High Leverage and Runner in Scoring Position Batting Average, 2012

NL MVP Candidates, High Leverage and Runner in Scoring Position Batting Average, 2012

Note that for the third MVP AL candidate, Robinson Cano replaced Josh Hamilton (and Adrian Beltre among others would also likely place above Hamilton at this point). Hamilton's HL numbers in particular were horrendous so removing him is not skewing the results of this exercise.

If this theory is correct, then the voters will select Miguel Cabrera as AL MVP and Buster Posey as NL MVP, as each of them raised their performance to much higher levels in these highlight situations than their elite peers.

Of course in the American League, this is perhaps the most talked about and debated MVP race in recent memory. Cabrera held on to win the Triple Crown, a feat not accomplished for 45 years. Trout had a rookie season for the ages, becoming the first player (not just rookie) to record 30 home runs, 45 stolen bases and 125 runs in one season. The vote will come down to those who cherish the longstanding baseball metrics along with the mystique that is the Triple Crown against those who believe we have better, more complete metrics with which to assess who is the best all-round player in the game. Both of these players received a lot of media attention, and so it will be interesting to see who ends up taking the award. If the theory proposed above holds true, then the media will be swayed in favor of Cabrera in 2012.

The National League also has an interesting back story, as strong candidate Ryan Braun had to endure a reported failed drug test in the offseason heading into 2012. While Braun managed to wiggle off the hook by citing inappropriate handling of the sample, many people believe he did so on a technicality, and that he was in fact guilty of failing the test. Whether or not this will weigh into voter decision making remains to be seen. Another interesting note is that aside from Posey, Yadier Molina also should garner many votes for NL MVP, likely putting two catchers in the top five spots. Catcher defense is one aspect of the game that is widely accepted to be under accounted for in even the most advanced defensive measurements that we have today. Perhaps years from now if this is better measured we will look back on this season and rate the 2012 performance of these two backstops in a different light.

Moving on to the Cy Young races, we also suggested a simple model to predict the winners of these awards from each league. The model was built by looking at the winners from the previous eight seasons, just after the last reliever won the award in 2003. The original post goes into more detail about how the simple predictive model was generated. In general, in the AL, ERA appears to have much more significance than SO with respect to the award. In the NL, SO appears to have much more significance than ERA. With that said, here is the updated table for the 2012 season from each league:

AL Cy Young Candidates, Big Three Category Performance with Cy Young "Score", 2012

NL Cy Young Candidates, Big Three Category Performance with Cy Young "Score", 2012

If this theory is correct, then the voters will select David Price as the AL Cy Young Award winner and R.A. Dickey as the NL Cy Young Award winner.

Price held off a late charge from Verlander, who finished the season on a strong note. Price holds on to the top spot primarily because of his extra three in the win column, which appears to be of particular importance in AL Cy Young voting.

Dickey was the only player to overcome the lead over the final weeks since the tables were first calculated, as Cabrera, Posey and Price were all in the lead when originally measured. Dickey and Gonzalez were neck-and-neck, and in the end the superior strikeout total by Dickey overcame his one win deficit to Gonzalez in the NL Cy Young Award predictive model.

One assumption made in the model is that a relief pitcher will not be in the running for the Cy Young Award. While in most seasons this is true, in 2012 there will be a reliever from each league that will be in contention for significant numbers of votes. In the American League, Fernando Rodney broke the all-time single season relief pitcher ERA record, coming out of oblivion before the year began to shave Dennis Eckersley's 0.61 from 1990 down to a sparkling 0.60. In the National League, Craig Kimbrel became the first reliever in history (with a reasonable innings pitched threshold) to strikeout more than half of the batters he faced, finishing the season with a 50.2 K%. Both of these record-setting seasons will receive considerable attention among the voting public, but will it be enough in either case to result in a Cy Young Award victory? Likely not, although they may both finish higher in the vote standings that many of the starting pitchers listed in these tables.

How many of these four will be correct? What do you think?

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[Credit and thanks to Fangraphs for data upon which this analysis is based]

Matt Wieters

There have been few players in recent memory hyped as much as Matt Wieters was prior to his arrival to the Major League level. Switch-hitting, power-hitting catchers with good plate discipline and plus defense to boot do not grow on trees. Coming into the bigs as a catcher brings with it extra challenges above what most position players have to deal with, as catchers have to adjust to calling games at the highest level on top of learning to deal with big league pitching in the batters box.

Wieters has developed into a fine major league catcher, scoring well in defensive metrics and providing above average offensive contributions as well. In looking at Wieters' performance over the last two seasons, we see a remarkable consistency, as his 2012 season numbers are almost identical to his 2011 statistics:

Matt Wieters Offensive Statistics, 2011 and 2012 (to date)

While his performance to date has been more than acceptable, it would seem that many expected even better things from the young backstop. The hype was incredible, after all. Wieters has the swing to match the hype as well, fashioning a very smooth, powerful stroke that just screams success when you watch it in action. Joe Posnanski at Sports on Earth described Wieters' swing in a recent article, comparing it to some of the great swings of the modern baseball era:

That said, there are games like Sunday’s when you just watch Wieters and find yourself in awe. Obviously he had a particularly good game -- he hit two homers, walked twice (once intentionally), handled the game pretty flawlessly and so on. But it’s the way he does it that leaves you shaking your head. His swing, especially from the left side, is absolutely beautiful. I mean it’s BEAUTIFUL -- it’s Griffey beautiful, Strawberry beautiful, Billy Williams beautiful, Will Clark beautiful. Even when he strikes out, which he did in his fifth plate appearance, it’s like art.

As you can see from the video of his two home runs on this day, in particular the first one, his swing looks especially effortless and he generates considerable power.

There is one way to compare Wieters to the other names mentioned as swing comparables from the left side that demonstrates an area where he may need to change his plate approach when batting left handed:

Career Groundball and OPS Statistics of Matt Wieters and Swing Comparables

There are a few points to make about this table. For one, Billy Williams is not included in the list, because no GB splits could be found for him given that his career was earlier than the others on the list. Also, we know that platoon splits for batters do not stabilize for at least one thousand plate appearances from each side, and while Wieters is over one thousand now from the left side, there is still the potential that this can change. What the table does show, however, is that in relation to hitters who are his alleged swing comparables, Wieters hits the ball on the ground with a much higher frequency. The reason that this is bad news, is that like his swing comparables, Wieters has an awful BABIP on ground balls. Of the 136 qualified hitters over the past two seasons, Wieters has the fifth worst BABIP on ground balls. Some of this can be explained by his speed, but it seems that some of this may have to due with his beautiful looking swing. The hitters on this list could muster a lot of power out of their smooth strokes, partly generated by a slight uplift in the swing. Hitting the ball on the ground with a swing plane that rises cannot be the best way to make contact, and so perhaps this is partly to explain why these smooth swingers posted below league average BABIPs on grounders. Bradley Woodrum has recently explored swing planes and how they can affect performance against different types of pitchers.

An interesting note is when Wieters' plate appearances are broken out by his platoon splits, we see that he hits far fewer ground balls from the right side than he does from the left. From the right side, his GB/FB is approaching the level of his swing comparables, and so is his OPS. Unfortunately OPS+ was not available by platoon split, but given the relatively low offensive environment of the past few seasons, his 822 OPS would lead to an OPS+ that measures much more comparably to the others on this list than his overall numbers. From the left side, all those extra ground balls are turning into a lot more outs, which shows with his significantly lower OPS from that side of the plate.

While there is no shame in not stacking up to the types of names on this list, it would appear that if Matt Wieters is to take another step forward toward matching the elevated hype that existed when he entered the league, he may need to make adjustments at the plate from the left side. With the majority of his at bats coming against right handed pitchers, Wieters would be well served to loft more balls into the air with that sweet swing of his and take advantage of what that stroke has proven to do for other players in years past.

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[Credit and thanks to Fangraphs and Baseball Reference for data upon which this analysis is based]

Sophomore Performance

It is difficult to imagine what it must be like for young hitters in their rookie MLB season. Players will enter the league with different amounts of seasoning at different levels. Some are high draft picks with high expectations, others fight their way up the minor league system and find themselves promoted to fill in for an injured regular. One thing that is constant for all of these hitters is that they will have never faced pitchers that possess the arsenal of major league pitchers. Multiple plus pitches from starters. Commonplace 95 MPH+ fastballs from relievers. Hitters of course experience a variety of success in their rookie seasons, and from their initial success expectations are adjusted for their sophomore seasons. This is where the story gets the most interesting, as carrying success (or lack thereof) into a second season is definitely not a done deal. We see many cases of "sophomore slumps" every season. Eric Hosmer, Jemile Weeks and Dustin Ackley are prime examples from 2012. Is it possible to find a metric from rookie numbers that can help us predict sophomore season performance?

To assess whether a player will be able to improve their batting performance in their sophomore season, we can try to determine whether they are being overmatched in the batters box. The theory will be that a good sign that a player is starting to click offensively is that they are making adjustments at the plate during the game. In order to remove defense and chance from the equation, we will focus solely on strikeouts, which are completely under the hitter's control. To assess whether hitters are making adjustments in the game, we will look at the difference between their K% the first time that they face pitchers in a game and their K% when they face pitchers subsequent times within the same game. For example, assume a hitter faces a starter three times, then a reliever once, then a different reliever for a five plate appearance game. In this example, the first, fourth and fifth plate appearances were facing pitchers for the first time in a game, and the second and third plate appearances were facing pitchers subsequent times in the same game. The theory is that hitters who are able to greatly reduce their K% after seeing a pitcher at least once earlier in the game are hitters who are making the necessary adjustments for success at the plate. We will call this difference "K% differential" from now on to make it easier for ourselves.

To test this theory, we will look at players who are in their age 25 season or younger in the MLB. Some of these players are rookies in 2012, and some of these players are already in their second, third, fourth, fifth or even sixth season in the major leagues. For all players that are not rookies in 2012, we will calculate their K% differential from their rookie season, and then calculate their wRC+ differential between their sophomore season and their rookie season. If the theory holds true, then we would expect players with higher K% differentials to post higher wRC+ improvements in their sophomore seasons. Conversely, players with lower K% differentials we would expect to post lower or even worse wRC+ changes year-to-year.

In calculating the results, if players had some plate appearances from years prior to their official rookie season (i.e. from September call up situation), these were included in their rookie season plate appearances. Consider the following table showing the results:

K% Differential from Rookie Seasons of Players 25 or Younger and wRC+ Change in Sophomore Seasons from Rookie Seasons (to date if sophomore season is 2012)

Overall, we see the theory tends to predict the correct wRC+ change direction for the sophomore season, if we set the K% differential threshold to 5.0%. 11 of the 15 players who posted K% differentials above 5.0% increased their wRC+ in their sophomore seasons. 12 of the 16 players who posted K% differentials of 5.0% or lower decreased their wRC+ in their sophomore seasons.

Unfortunately, the relationship is not perfect, as we have a few huge outliers. Oddly, three of the four biggest outliers are all Seattle Mariners in Dustin Ackley, Michael Saunders and Justin Smoak. To provide some support/explanation for this, we can at least fall back on the fact that both Saunders and Smoak have trended in the direction suggested by the theory in 2012, their third seasons. Ackley has not had a third season yet to recover - so perhaps we should be bullish on Ackley heading into 2013. The fourth giant outlier is Pedro Alvarez, who has also recovered nicely in his third season.

Some interesting success stories for the theory is the correct binning of Desmond Jennings, Jason Heyward, Eric Hosmer and Brett Lawrie as wRC+ decliners. All of these players were widely expected to have excellent sophomore seasons, only to regress from their rookie numbers. The fact that they were not capable of making significant in game adjustments could have perhaps been used as a signal that not everything was rosy at the plate for these players heading into season two.

There is something notable about the largest outliers, highlighted in orange in the table, that suggests a type of player that the model does not represent well. All of the largest outliers but Alcides Escobar fashioned very high rookie strikeout rates, as seen in column three. It would appear that hitters who strikeout well above the league average rate are a different breed of hitter that is not necessarily relying on in game adjustments for success as much as more "contact" hitters.

So the theory is not completely generalizable. If we remove hitters who posted rookie K% of 21% or higher, it removes 13 of the 31 hitters from our pool, leaving us with 18 rookies. At this point the model appears to be quite successful at predicting sophomore season wRC+ changes using K% differential:

Scatter Plot of K% Differential from Rookie Seasons vs wRC+ Change in Sophomore Seasons from Rookie Seasons, Rookies with K% < 21%

The R-squared value of 0.68 is fairly good, in my estimation. Given the relative success of the theory in recent seasons, we can now calculate the K% differentials of 2012 rookies, in an effort to predict their 2013 performances relative to their rookie seasons. In order to have faith in the model, we restrict the rookies to those who have posted K% under 21% this season. Here is a table showing this year's rookie crop:

K% Differential from 2012 Rookie Seasons of Players 25 or Younger, 2012 wRC+ and 2012 K% (to date)

Keep in mind that this result is not inferring that DJ LeMahieu will be better than Yasmani Grandal next season. The high K% differential is merely an indication that the player can improve on his own particular wRC+ next season. This certainly looks to be good news for folks expecting a big season from Bryce Harper next year. Mike Trout's rookie K% is slightly above the 21% cutoff where the model appears to be predictive, so he does not appear on this list. Other notable rookies who have strikeout rates too high to appear on the list include Starling Marte, Will Middlebrooks, Wilin Rosario, Chris Carter and Dayan Viciedo. Perhaps more thinking will lead to another model that may yield better predictive results for these types of hitters.

It seems to me most people assume that a rookie hitter who has a good season at the plate will continue that success into their sophomore season. Yearly there players that fall flat in their second seasons, leaving most people to wonder what happened. Perhaps using metrics like this one can help us understand which players are truly ready to succeed going forward, and which may need more time getting settled in the batters box at the big league level.

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[Credit and thanks to Fangraphs and Baseball Reference for data upon which this analysis is based]

Matt Holliday

Since 2007, the top two MLB players in fWAR are Albert Pujols and Chase Utley. Can you guess which MLB player ranks 3rd in fWAR? While his defense has been slightly above average, he is not one who like Utley has shot up the leaderboard with his glove. He ranks 6th in wRC+ in that time frame, behind Pujols, Joey Votto, Miguel Cabrera, Ryan Braun and Prince Fielder. You can likely only guess the correct answer because the title of this article is Matt Holliday.

Holliday is the king of hiding in the tier just below the absolute elite players in every single season. Consider his yearly wRC+ finishes since 2007 - 7th, 10th, 18th, 7th, 8th and 15th to date in 2012. Always near the top, but never close enough to garner serious MVP contention. Every year he's overshadowed, but over the course of many seasons, his consistency and relative level of health have made him truly one of the best players in the game.

Someone who rates as the 4th best player in the game must do something better than everyone else in the league. The investigation into finding such a skill took a little bit of time, but there is in fact something that Matt Holliday has done better than anyone else during that time that helps explain his success.

On Baseball has an article on sliders with the following introduction:

There are many people who believe the slider is the most deadly weapon in a pitcher’s arsenal. In fact, Ted Williams — the last Major League hitter to bat .400 and arguably the “Greatest Hitter Who Ever Lived” — once told a young Sparky Lyle to throw the slider because, to quote Lyle: “Ted Williams told me the slider was the one pitch he couldn’t hit.”

Sliders may be too tough for Ted Williams, but Matt Holliday destroys sliders. Since Pitch F/X data became available in 2007, nobody else has done close to the amount of damage against that pitch. In fact, although the only tool we have to gauge performance against individual pitches is able to use data that has only been around since 2002, Holliday ranks first all-time in career performance against the slider.

The tool that exists for measuring pitch-specific performance is called Pitch Type Linear Weights. The statistic attempts to measure the total runs generated by a player on a particular pitch, and then reports the total in runs better or worse than league average for this pitch. On Fangraphs, the formula is applied to both BIS pitch data (since 2002) and Pitch F/X pitch data (since 2007). Regardless of the data set used, Holliday ranks first overall when it comes to wSL. This is the heat map that shows Holliday's run generation against sliders compared to the league average since the start of 2007:

Matt Holliday Run Value Heat Map against Sliders, 2007 to 2012 (to date)

From this heat map we can see Holliday has destroyed sliders left over the plate, as well as belt high hanging sliders. Since wSL is a counting stat, it is interesting to note that since 2007, Holliday has been served an almost exactly league average percentage of sliders, at 15.4% of all offerings. This tells us a couple of things. First, pitchers have not been shying away from the pitch with Holliday in the box, perhaps not realizing the amount of damage that he can do on these pitches. Second, Holliday has risen to the top without having faced an excess of sliders with which to create runs. At just 15.4% of all pitches seen, how much of his batting totals can be accounted for solely by his hitting against sliders?

There may be no readily available data to show exactly how many home runs Holliday has hit off of sliders, for example. One exercise we can do to show just how impressive his slider prowess is would be to examine his weighted total runs on sliders, and look at what percentage this accounts for of his entire total runs output. We can then compare this to his peers, as seen in the following table:

Weighted Total Runs on Sliders as a Percentage of Weighted Total Runs on All Pitches, Top 20 wRC+ Producers, 2007 - 2012 (to date)

Holliday's total run production from sliders is about 50% more than his closest peer, when compared to other elite hitters since 2007. Note that these are cumulative results, showing weighted total runs on all sliders thrown to each of these hitters, even though each hitter would have faced differing numbers of sliders over this time period. This shows what actually happened, and what happened is that Holliday crushed sliders more than anyone else.

Matt Holliday will likely never win a league MVP Award. He will likely never be the first player chosen in your fantasy baseball draft. He has, however, quietly been one of the top few players in the game over recent years. There is one thing that he is the best at, and it happens to be doing the one thing that Ted Williams claimed that he himself couldn't do: hit the slider.

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[Credit and thanks to Fangraphs, Baseball Heat Maps and Texas Leaguers Pitch F/X for data upon which this analysis is based]

David Price, Gio Gonzalez

Last week, we considered a theory that could explain how the winners of the MLB MVPs from each league emerge from the pack of top competitors to capture the award. Today, we look at the recent winners of the Cy Young Awards from each league in an effort to identify trends that could help us determine the 2012 winners.

While sabermetric approaches to comparing players is gaining steam, the mainstream media that accounts for the majority of the voting pool for these award races still tend to rely on traditional, easy to understand metrics. With respect to the Cy Young Award, the Big Three categories for selecting the winner are Wins, ERA and strikeouts. We can restrict our history to the last eight seasons, for a couple of reasons. First, voting patterns can change over time, so when trying to predict the current season champion, it is best to focus on recent voting patterns. Also, nine years ago was the last time a reliever won the Cy Young Award. While there will definitely be some relievers garnering votes this season (i.e. Fernando Rodney, Aroldis Chapman, Craig Kimbrel), they will almost certainly not be winning the award. Including relievers in a model for Wins, ERA and strikeouts is also not very constructive.

The most interesting observation in looking at the Cy Young Award winners from the last eight seasons from each league, is that the relative importance of the Big Three categories is very different between the two leagues. Consider the following table:

Cy Young Award Winners by League, First Place Finishes among Vote Getters by Category, 2004-2011

In the American League, ERA is of particular importance, followed by Wins and then closely by strikeouts. In the National League, strikeouts lead the way, slightly ahead of Wins, while ERA is almost a non-factor, relatively speaking. These observations of recent voting patterns allow us to build up empirically-based, predictive models for Cy Young voting in 2012. These models, customized to each league, are about the simplest that one can imagine, for the sheer entertainment value of seeing who the predicted winners are for this year. The models essentially make use of the relative importance of the Big Three categories in each league, to created a weighted "score" for each pitcher based on his yearly Wins, ERA and strikeout totals. The model is constructed such that the highest score is best.

The following models fell out of this work as Cy Young pitcher "score" calculators:

AL "score" = (100 / ERA) + (1.2 x Wins) + (strikeouts / 12)

NL "score" = (15 / ERA) + (1.25 x Wins) + (strikeouts / 7.5)

Using these simple formulas, seven of the last eight Cy Young Award winners are correctly predicted from each league. The two outliers are Bartolo Colon's win in the AL in 2005 (where it selects second-place finisher Johan Santana as the winner) and Roger Clemens' win in the NL in 2004 (where it selects second-place finisher Randy Johnson as the winner). These formulas correctly predict the Cy Young winners from both leagues for each of the last six seasons.

With the "hard" part done (okay, this is really just fun, simple math), we can now move on to applying these wonderful formulas to the top starting pitchers of 2012 to observe the current leaders in the Cy Young race should the models hold true this year.

American League Cy Young Candidate "Scores", 2012 (to date)

National League Cy Young Candidate "Scores", 2012 (to date)

[NOTE: comparing "scores" between leagues has no meaning in this set of models]

The American League Cy Young discussion has seemingly included these five pitchers for many weeks now as the legitimate contenders for the award this season. Not surprisingly, since ERA and Wins seem to drive the AL Cy Young voting the most, David Price has the top "score" by a fair margin, leading the league in both categories. Some interesting notes are the fifth place ranking of Felix Hernandez, who has hurt is case with a string of three poor efforts resulting in a ballooning ERA and no Wins. Last year's winner Justin Verlander has posted another strong season, and leads the league in strikeouts. His vastly lower Wins total from a year ago, however, has placed him third on this list.

The National League picture has an extremely close race at the top, with Gio Gonzalez and R.A. Dickey being separated by the slimmest of margins. Gonzalez' extra Win at this juncture is essentially providing enough value to push him over the top, according to the model. These two could easily flip-flop over the final two and a half weeks of the season, if Dickey can pull even in Wins with Gonzalez.

Typically we do not spend much time mentioning the Big Three Cy Young pitching categories here, as in general there are better ways to assess the performance of a pitcher relative to his peers and even historical players. When looking at the potential Cy Young winner, however, we have to look at the way voters have typically analyzed pitchers in recent years in order to understand who may rise to the top in 2012.

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[Credit and thanks to Fangraphs and Baseball Reference for data upon which this analysis is based]

Mike Napoli

Make Napoli must wish that he had qualified for free agency at the end of the 2011 season instead of at the end of this season. Last season was a career year for Napoli, as he set new highs in literally every offsenive category across the board in his first year as a Texas Ranger. Had he qualified for the batting title, Napoli's wRC+ of 178 would have placed him third in the league, behind only Jacoby Ellsbury and Ryan Braun. This kind of offensive production combined with his ability to catch a significant number of games would have made Napoli an incredibly sought after commodity had he hit the free agent market last offseason.

Flash forward to 2012, and Napoli has regressed in nearly every offensive category. A slight uptick in his BB% is about all he can hang has hat on this season. While having missed a portion of the season due to injury, all other categories have seen major downturns, perhaps none more glaring than the reappearance of his high K% ways. After using a career low 19.7% K% to fuel his 2011 success, Napoli has seen his K% rise all the way to a career high of 30.1% this season (to date). Putting less balls in play has obviously hurt his average, and thus OBP and SLG as a result.

In comparing Napoli's plate discipline profile to last season, it is interesting to note that his O-Swing%, Z-Swing% and Swing% are almost identical. His SwStr% is not surprisingly higher, but has only risen to 11.5% from 10.1% last season. This relatively small increase cannot on its own explain the massive K% rise in 2012.

In analyzing Pitch F/X data, we can see that Napoli's struggles this year as compared to his banner 2011 season are almost completely due to his ineffectiveness at handling occasions where he's in a pitcher's count:

Mike Napoli Strikeout Totals by Type and Count, 2011-2012 (to date)

[One note about this graph - this data was hand-mined from Pitch F/X data, and for some reason not understood to me, accounts for only 82 of Napoli's 85 strikeouts from 2011, and 101 of his 108 strikeouts in 2012. Perhaps foul tips are not counted as whiffs? In any case, the analysis that follows still shows absolute changes in Napoli's strikeout totals, despite these few missing Ks.]

The change to notice in the graph is that when Napoli has fallen behind 0-2 or 1-2 this season, he has done a much poorer job at staying alive in the plate appearance. When he is even or ahead of the count, at 2-2 or 3-2, Napoli has actually struck out less in 2012 than 2011. To make this clear, Napoli has struckout 25 more times in 2012 on 0-2 and 1-2 counts so far this year than he did last season, more than accounting for the total strikeout increase he has absorbed this year. We can drill down further into the 0-2 and 1-2 count situations to see where pitchers are succeeding this season with Napoli in the box. To start, 21 of these 25 additional strikeout were due to swinging strikes, so we will focus our attention on these types of strikes. Of the 21 extra swinging strikes leading to strikeouts, the pitch breakdown has been as follows:

Mike Napoli Extra Swinging Strikeout Pitches by Type, 2012 (to date) as compared to 2011

The four-seam fastball total is shocking, as Napoli struck out swinging on only 5 of these pitches in 2011. The curveball/slider combination is also notably higher this season. So Napoli is being beat in pitcher's counts by both hard fastballs and breaking balls. Clearly this is not a good situation. We noted earlier that Napoli's O-Swing% was basically flat year to year. Could it be higher in these situations? By manually judging using the Pitch F/X strike zone, it would appear his O-Swing% on breaking balls is fairly static, but his O-Swing% on four-seem fastballs is actually up, from around 32% to around 45%. In terms of pitch frequency, however, pitchers are throwing Napoli more breaking pitches out of the zone, so while he is chasing at the same rate, he is racking up more strikeouts overall. As for four-seam fastballs, pitchers are throwing him less of these out of the zone, but his increased susceptibility to swing has led to poorer results.

Mike Napoli has increased his BB% in 2012, and from this analysis, appears to be faring just fine when he works the count even or into his favor. When he falls behind and gets to a two strike count, his 2011 success at putting the ball in play has disappeared, leading to a career-high K% just one year after recording a career best.

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[Credit and thanks to Fangraphs and Texas Leaguers Pitch F/X for data upon which this analysis is based]

Jeremy Hellickson

In August 2010, Jeremy Hellickson became the latest in a long line of high-ceiling starting pitchers developed in the Tampa Bay Rays farm system to reach the major leagues. His AAA numbers that season were impeccable, and upon reaching the bigs, Hellickson did not disappoint. He posted a 3.47 ERA, 3.88 FIP, 3.83xFIP with a sparkling 8.17 K/9, 13.0% SwStr% and 1.98 BB/9. Bright days ahead were expected for Hellickson.

Though his ERA in the 2011 and 2012 seasons (to date) have improved, his FIP has increased significantly each year, to 4.44 last year and 4.94 this year. These have been largely driven by greatly reduced K/9, down to 5.57 and 5.83 in the two seasons. The lower strikeout totals can be attributed to much lower SwStr%, which dropped to 9.7% and now 8.3% in 2012. His BB/9 is also up substantially, to 3.43 and then 2.97. After consistently mowing down at least a batter an inning all throughout his excellent minor league career, and mostly carrying over that success upon hitting the bigs in 2010, what happened to his knockout pitch?

The interesting thing is that there is nothing on the surface that jumps out as a possible reason. Velocities almost identical across the board. Movement looks the same. Release points look the same. He started throwing a cutter (more), but it appears to have been a successful pitch for him.

The most alarming change has been Hellickson's ability to generate swings and misses with his offspeed pitches with two strikes on the batter:

Jeremy Hellickson, Offspeed Whiff Rates with Two Strikes, 2010-2012 (to date)

After shooting out of the gate with phenomenal success putting hitters away with his offspeed pitches, Hellickson has struggled to maintain this ability in the past two seasons. In looking at his curveball and changeup velocities and movement year-to-year, nothing immediately stands out as a reason for the sudden lack of success.

The only viable explanation remaining to explore is that something has changed with Hellickson's pitch sequencing to close out hitters. One observation is that while his curveball frequency has stayed roughly the same with two strikes, his changeup usage has dropped off in these counts over time:

Jeremy Hellickson, Changeup Pitch Frequency with Two Strikes, 2010-2012 (to date)

Some added insight into pitch sequencing is available as of earlier this week, using a new sequence mining tool at Brooks Baseball. The most notable sequence that may explain some of this strikeout loss is the abandonment of a back-to-back low over the plate changeup sequence to finish off LHH hitters (which should be hitters against which the changeup is most effective):

Jeremy Hellickson, PA Outcomes from Consecutive Low Over the Plate Changeups to Finish PAs, 2010-2012 (to date)    *NOTE* image slightly reformatted to fit screen

This graphic is not necessarily intuitive to understand. Overall, this shows the frequency of plate appearance outcomes when LHH are finished with back-to-back low over the plate changeups. The red squares indicate a higher frequency, the green squares a lower frequency. Given this legend, we can see that Hellickson started off his MLB career with very good success ending plate appearances with this sequence. He garnered lots of strikeouts, some walks, some groundballs, but very few line drives or flyballs. That type of outcome breakdown sounds like a recipe for success. It is interesting to see how in mid-2011, this sequence began generating more groundballs than strikeouts. It was still generating strikeouts and not allowing line drives and groundballs, so was still an effective closing pitch sequence for Hellickson. For some reason, at that time, Hellickson abandoned this particular two-pitch sequence.

Perhaps he felt hitters were starting to make the necessary adjustments to hit the second straight changeup, and so he moved away from this sequence before the line drives and home runs started? The problem is while this might have been true, Hellickson did not try it, and has seemingly not found other sequences that work to finish off hitters successfully with strikeouts.

Perhaps there was a change in the Tampa Bay catching situation around that time? This actually also looks somewhat plausible. John Jaso and Kelly Shoppach platooned behind the plate for the first half of the season in 2011. John Jaso then did not play between July 7th and August 19th, after hitting the disabled list with a strained oblique. During that time, Robinson Chirinos filled in for Jaso, with Shoppach receiving a little more playing time than usual. Perhaps Chirinos did not call for this sequence much, if at all to try to strikeout hitters?

This level of analysis becomes more subjective, when there is less concrete data to manipulate. In any case, Hellickson abandoned a pitch sequence that was effective for him early in his major league career, and has not found the same strikeout success since that time.

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[Credit and thanks to Fangraphs, Brooks Baseball and Texas Leaguers Pitch F/X for data upon which this analysis is based]