Archive for Player Analysis

While Ervin Santana and Ubaldo Jimenez certainly have their similarities, they each have different risks and benefits associated with them. They have often been connected throughout the offseason, as they have similar price tags and each is connected to draft pick compensation. They have also been linked this offseason because each is coming off an impressive season following a very bad season, and overall inconsistencies in their careers. However, the two pitchers are not incredibly similar, as one profiles more as a durable innings-eater and the other carries more upside.

The 31-year-old Ervin Santana provides many more innings than Ubaldo Jimenez, as he has eclipsed the 200-inning plateau three times in the past four seasons. Santana, however, has often outperformed his peripherals, especially this past season. In 2013, Santana posted his career-best 3.24 ERA, but his FIP was 3.93, which suggests some regression in 2014. Even looking back at the past five seasons, Santana has had an FIP under 4.00 just once. It may seem as if he has the ability to outperform his peripherals consistently, but during that same span his ERA surpassed 5.00 during two seasons most recently in 2012.

As I mentioned above, Santana’s best quality is his ability to go deep into starts consistently throughout the season. Santana is also a tremendous strike-thrower, as he walked just 2.18 batters per 9 innings, which is an improvement upon his still impressive 2.81 BB/9 for his career. Santana is also an effective groundball generator, as his groundball rate has been above 43% for the past three seasons. The real knock on Santana has been his inconsistencies throughout his career, with three seasons of an ERA above 5.00 and just four seasons of an ERA under 3.00 during his 9-year career. While Santana’s ERA was the best of his career, in 2013, his other metrics were not much better than his career norms, which suggests he hasn’t necessarily figured anything out.

The 30-year-old Ubaldo Jimenez, unlike Santana, has a reputation for struggling to go deep into games. He has not thrown 200 innings in a season since 2010 and has only done it twice in his 8-year career. His struggles to last deep into games are likely related to his high K/9 and very high BB/9. Both strikeouts and walks drive a pitcher’s pitch count up and he has never had a BB/9 lower than 3.50. As I stated above, Jimenez carries more upside with him, as his career K/9 is a full strikeout per 9 higher than Santana, but Jimenez’s peripherals are also better than his ERA. Jimenez has a career 3.78 FIP, compared to his 3.92 ERA. During his time with the Rockies, Jimenez was an outstanding groundball pitcher, but since moving to the Indians, his GB% has slipped to 38.4% in 2012 and 43.9% in 2013. Despite pitching in hitter-friendly Coors Field for the majority of his career, Jimenez’s Hr/9 has been better than Santana’s in every season of his career.

Compared to Santana, who has had an FIP under 4.00 just once in the past five seasons, Jimenez has had an FIP under 4.00 four of the last five seasons. Jimenez’s only truly bad season, in terms of FIP, was 2012 when his FIP ballooned to 5.06 and his ERA climbed to 5.40. While being able to go deep into starts is pivotal in being a reliable and consistent starter, Jimenez certainly carries the highest upside and actually most consistent performance between the two starters. Jimenez has also proven that he can pitch in a high run-scoring environment, such as Coors Field. Santana, however, has pitched the majority of his career in a pitcher-friendly park at Angels Stadium of Anaheim for every season except one.

Looking into the numbers, it is clear that Ervin Santana is the best bet of the two starters to reach 200 innings. It is also evident that Ubaldo Jimenez has the greatest potential to provide above-average production inning per inning. Neither starter is an ace or likely to become one and each comes with legitimate questions. However, in terms of which starter is better, it really depends on what a team is looking for. If they want a starter that can provide 200+ innings season after season, then Santana is by far the better option. If the team is seeking a starter that can consistently provide an ERA around or below 3.50, then Jimenez is the better option. Since each starter has a similar price tag, it is really a question of which type of starter the team is looking for. Personally, I prefer Jimenez to Santana because he has provided more consistent numbers across the board and has only had one truly bad season.

Lately I’ve been hearing some rumors connecting the Tigers to free agent outfielder Nelson Cruz. I understand how fans have been hungry for another power bat since Prince Fielder was traded, but Nelson Cruz is not the guy you want. It’s not because of the whole PED suspension last year, or even the fact that he single-handedly dismantled the Tigers in the 2011 ALCS. No, it’s simply because he is not that valuable of an all around baseball player.

I don’t particularly enjoy writing pieces where I talk about a player’s shortcomings. At the end of the day, these guys are major leaguers and I’m still a kid who’s a fringe high school bench player who doesn’t know whether he’s a natural right-handed or left-handed hitter (I’m really bad at both). But due to the recent clamoring for Cruz, I figured it was my duty to all my readers to expose the truth about him.

The Good

Nelson Cruz is a solid power hitter. Despite having a shortened season due to a 50 game suspension, Cruz still managed to hit 27 HR in 109 games. With a respectable ISO of .240 in 2013, and a career ISO of .228, Nelson can still manage to hit for very good extra base power. His wOBA in 2013 was .359 and is .353 over the course of his career, both being good. Bottom line, he’s a good power hitter, but I never said that I’m debating that aspect of his game.

The Bad

Nelson Cruz does not have very good plate discipline. Assuming that we’re talking about the guy that’s supposedly going to be “protecting” Miguel Cabrera in the batting lineup, plate discipline does play a huge factor in this discussion. We don’t want a guy who’s a free swinger batting after a walk to the best hitter in the game who also happens to be really slow on the base paths. Last season, Cruz swung at 30.8% of pitches that were outside the strike zone (O-Swing%), which is really bad. He only made contact with 73.1% of the pitches that he swung at (Contact%), which is also bad. His BB/K was also bad, clocking in at 0.32. Bad. What have we learned so far? Basically, Nelson Cruz is an all or nothing hitter, which some fans really don’t mind. In the case that he’d be hitting behind Miguel Cabrera, I’d tend to shy away from a hitter like Cruz.

The Ugly

To an extent, all the bad I mentioned could be forgiven if Nelson Cruz wasn’t such a terrible defensive outfielder. Move him to DH you say? The Tigers have Victor Martinez and Miguel Cabrera who will both rotate time at 1B/DH, so there is no room whatsoever for another DH. Cruz would have to play everyday in RF or LF. He is 34 years old and 240lbs. His ability to chase down balls in open space is clearly declining. Sticking him in the outfield with Torii Hunter, who looked lost in the outfield for most of 2013, would be a horrible idea for a team that used the offseason to vastly improve their infield defense. The stat that I like to use for defense is UZR, but because of Nelson’s shortened season though, I’m going to use UZR/150. Last year, Cruz’s UZR/150 was -6.5, which is way below average. Considering he’s posted a negative UZR for the last three seasons, you can see that he is not very good at defense and is clearly not getting any better. It’s also worth mentioning that the Tigers would have to give up their 2014 first-round draft pick to the Texas Rangers considering Cruz turned down their qualifying offer of $14 million.

Total Value

In 2013, Cruz was worth 1.5 Wins Above Replacement. Andy Dirks 2013 WAR: 1.7. Obviously WAR is not the end-all-be-all statistic, but it does give a pretty good idea of what a player is worth when you replace him with someone who is league average at his position. In this case, the WAR of each player is practically identical, which means over the course of a season they will somehow be worth the same amount of wins to their team. Cruz will probably cost around $7-9 million in 2014, whereas Andy Dirks is already under contract for only $1.625 million. Assuming Cruz signs for $8 million and has the same WAR as 2013, the Tigers would be paying $5.33 million per win for him. Andy Dirks with his current contract and WAR? $956,000 per win. I know this might be some moneyballin’ right here, but if the goal of baseball is to buy wins, wouldn’t you rather have the wins at a cheaper cost?

Conclusion

When all aspects of the game are taken into account, you see that Nelson Cruz is a below-average baseball player with a plus power tool. The Tigers have Miguel Cabrera, Victor Martinez, Ian Kinsler, Austin Jackson, and Torii Hunter (and sometimes Alex Avila too) who will all contribute their fair share of runs this upcoming season. Not only do they not need a one-dimensional power hitter, he just doesn’t make sense for the makeup of their lineup which now features a solid balance of on-base average, power, and speed. Mix that with the huge liability that he is on defense, and you get a player that I don’t want to play for the Detroit Tigers.

For more information from me on the Detroit Tigers, visit www.ttowntiger.com

Jeff Sullivan recently suggested that despite his reputation Tom Glavine did not pitch to a significantly more generous strike zone. Sullivan points out Glavine did not get significantly more called strikes than other pitchers, even during the peak of his career. Sullivan’s analysis piqued my interest and made me wonder if Glavine’s reputation for getting a wider strike zone helped him succeed in ways beyond called strikes.

Glavine’s reputation alone likely influenced a batter’s behavior at the plate, encouraging batters who were behind the count to swing at questionable pitches. Batters believed if they did not swing these pitches would be called strikes for Glavine (when a batter swings at a pitch out of the zone when the batter is ahead of the count that has more to do with a pitchers stuff than the batter giving the pitcher an expanded zone). So, what would we expect from a pitcher who is getting batters to expand the strike zone? You would expect batters to make poor contact, yielding a lower BABIP. The batter would most likely swing at pitches outside the zone when the batter is behind the count.

Based on this reasoning, I hypothesize that Tom Glavine will see a greater reduction in quality of contact when he gets ahead of the count than a league-average pitcher. I’m going to look at the time span from 1991 to 2002 because that was the time span Jeff looked at and because I like palindromes.

To measure quality of contact I will be looking at BACON (batting average on contact). BACON is slightly different than BABIP because BACON includes home runs. If batters are expanding the strike zone when Glavine is ahead in the count we should see the quality of contact decrease. To measure the decrease in quality of contact, I will look at the ratio of BACON when Glavine is ahead to BACON to when Glavine is behind (the lower the number the greater improvement the pitcher experiences by getting ahead in the count). I will refer to this measure as EXP (a lower EXP shows a greater decrease in quality of contact, an EXP above 100 shows an increase in quality of contact).  The graph below compares Glavine’s EXP to the league average EXP for each season during the 11-year span.

 The league-average EXP is consistent year to year, hovering around 91, which suggests batters expand the strike zone for most pitchers when batters are behind in the count. Glavine’s EXP is not always better than the league-average EXP. In ‘94 and ‘96 Glavine was actually worse when ahead in the count than when he was behind.  This is to be expected because BACON takes a while to stabilize. Looking at Glavine’s data for a single season is subject to a fair amount of random noise because you have a relatively small sample of data. One season for Glavine gives us about 170 fair balls with Glavine ahead and 280 fair balls with Glavine behind. However, over a larger sample BACON stabilizes. At around 2,000 fair balls (more than in a single season for Glavine) BACON stabilizes. For example, when looking at the league-average EXP for a full year BACON is stable — with 3,500 fair balls with the pitcher ahead of the count and 4,600 fair balls with pitcher behind the count.

To make sure we are not just attributing skill to some random variation we need to look at a larger sample for Glavine. Over the 11 year span form 1991-2002 Glavine induced weaker contact (lower BACON) than the league average both when he was ahead of the count and behind the count. This is not surprising as we would expect a good pitcher to be better than average ahead and behind the count.  What’s interesting is Glavine has better than league-average EXP  (87 vs. 92) which suggests Glavine is better at expanding the strike zone than league-average pitchers. This comes with the caveat that while we have 3,056 fair balls when Glavine is behind the count, we only have 1,853 fair balls when Glavine is ahead — just shy of the 2000 at which the measure should stabilize.  Even so, the difference between Glavine’s EXP and the league-average EXP is very convincing.

To stabilize BACON, I increased the sample by looking at all the balls put in play. I compared balls put in play when the pitcher had two strikes to balls put in play when the pitcher had fewer than two strikes, which led to EXP2: the ratio of BACON when a pitcher has two strikes, to when he has fewer than two strikes. The table bellow shows a comparison of the quality of contact in two strike counts to non-two strike counts.

Even with this larger sample size Glavine’s BACON is still lower than the league average in respective counts. More importantly, his EXP2 is still better than league average (although higher than his EXP).  Pitchers in general try to induce weaker contact when they are ahead of the count, but the data shows Glavine is doing something special to induce even weaker contact.

Is Glavine getting batters to give him a wider strike zone? We cannot definitively say what is causing this pattern in the data, but we are seeing the type of numbers we would expect to see if the batter was giving him a wider strike zone.

All splits number are from Baseball-Reference.

As we look for candidates to regress in 2014, a popular choice is Houston catcher Jason Castro for it seems the Astros backstop has two targets on his back: a high strikeout rate last year of 26.5% and a high BABIP of .351. Steamer and Oliver both project a steep drop in BABIP that will drag his batting average from a solid .276 to the .250s. As Brett Talley wrote, Castro screams regression.

Or does he?

Talley points to Castro’s strikeout rate that has been topped only 61 times in the past decade, and only four times the player matched or bettered a batting average of .276. But that measure may miss the mark. No one is suggesting Castro’s strikeout rate will worsen. When it comes to batting average, the critical question, then, is whether he can come close to maintaining a high BABIP.

On that question the evidence is more promising. In the last decade, only 38 of 1,509 batters have had an infield-fly rate lower than Castro’s 1.8%. Only 47 had a line-drive rate higher than Castro’s 25.2%. Taken together, those two select groups actually have 10 matches — players who managed both a lower infield-fly rate and higher line-drive rate. Here they are along with their BABIP, batting average and strikeout rate:

Player, year, BABIP, Avg., K-rate

Joe Mauer, 2013, .383, .324, 17.5%

Joey Votto, 2011, .349, .309, 12.9%

Howie Kendrick, 2011, .349, .297, 17.3%

Matt Carpenter, 2013, .359, .318, 13.7%

Michael Young, 2007, .366, .315, 15.5%

Joey Votto, 2013, .360, .305, 19%

Adam Kennedy, 2006, .313, .273, 14.3%

Bobby Abreu, 2006, .366, .297, 20.1%

Michael Young, 2011, .367, .338, 11.3%

Chris Johnson, 2012, .354, .281, 25%

What might we gather from this evidence?

(1) All but one of the players topped .276.

(2) The skills involved seem somewhat repeatable: Votto and Young each appear twice and as a group they generally in their careers combined a high LD rate, low IFFB rate and a high BABIP.

(3) We wouldn’t expect a player who whiffs a quarter of the time to have a batting average as high as someone who strikes out half as much while putting up similar LD and IFFB rates. Castro is unlikely to approach the median average of this group of .307.

(4) Castro doesn’t need to approach the median average to avoid significant regression. He is more likely to hit closer to last year’s mark than he is to hit in the .250s.

The Red Sox have made news, signing Grady Sizemore to a Major League contract worth $750k ($6 million if all incentives are factored in).  This got me thinking about what happened to Sizemore.  He made the game of baseball seem simple with his defensive prowess, his above average power, and his lightning speed.  Then one day, his aging body realized that the kind of aggressive player that he had been would no longer work and it started giving in to the high strain that he put it under.  He had a hernia surgery as well as several knee and back surgeries between 2010 and 2013 which seemed to end his baseball career.  Then out of the blue he was picked up by the Red Sox in a deal that has high potential for both sides; the Red Sox could get a great player for cheap and Sizemore could resurrect his career.  This deal could end poorly for Sizemore, who could finally realize that his career is over either from injury or performance reasons while the Red Sox will view it as a failed experiment that doesn’t hurt them financially now or in the long term.

The signing of Grady Sizemore is an indication that they are ready to give Jacoby Ellsbury’s former job over to Jackie Bradley Jr., but it also shows that they are prepared with a backup plan in case that doesn’t pan out.  Some would say that Sizemore is hardly a backup plan as he could very well end up injured, which is absolutely true, and that an outfield of Gomes LF, Victorino CF, and Nava RF would happen in the event of Bradley turning out to be a dud.  But with Sizemore comes a tremendous amount of upside.  Five years ago he was a 30-30 player and a gold glover in the outfield.  He was healthy, he was starting to walk more and strike out less, and then everything stopped for him.  He was forced to undergo elbow surgery in 2009, an injury that had plagued him all season long, and from that point on if it wasn’t one problem then it was another.  Left knee surgery, right knee contusion, hernia surgery, back surgery, and then a right knee surgery came all in a span of three years which can leave a player asking whether or not their career is over.

The question that should also be brought to the attention about Sizemore is what his plate discipline will be like.  Sizemore’s BB/K reached its peak in 2008 with a .75 BB/K, dropped to .65 in 2009, and then plummeted to .245 in the combined 104 games in 2010 and 2011.  For most of his career, it seemed that Sizemore was above average at walking and avoiding strikeouts as his career BB/K was .53, .05 above the Major League average during that time period of .48.  Now did the drop come about as a result of the injuries that he suffered from 2009 to 2011 or did they just come as a result of him losing his ability?  The interesting thing about his BB/K having such a drastic change is that his swing percent rarely changed.  His career Swing% is 43.4% which is fairly decent considering that between 2004 and 2011, the average swing rate among players was 47.6%.  Sizemore also made contact with the baseball at an 81.1% rate over the course of his career with the contact rate dropping barely below that number in the three shortest years of his career (2004, 2010-2011).  Those were also the only years that his swinging strike percent exceeded 10%.  Perhaps what this shows is that pitchers weren’t afraid to attack him and he wound up taking a lot of called strikes.

The other facets of his game that must be viewed at with a lot of importance are his power and speed.  I truly believe that if Sizemore can stay healthy, then we will see a resurgence of his power.  His power numbers have always been impressive, with a career ISO of .204 and career SLG of .473.  Even in 2011 when he was limited to 71 games and was coming off of microfracture surgery in his left knee, he produced an ISO of .198.  I don’t think power will be an issue for him.  The other major part of his game that will likely never return is the speed.  In those 71 games of 2011, he stole 0 bases after averaging 19 swiped bases per season and stealing at least 22 bases in 4 of his 7 seasons prior to 2011.  With the second knee surgery having occurred in 2012, my guess is that little to no speed will be found from him in 2014.

As with everything in baseball, there are the intangibles that must come into consideration when discussing the future of Grady Sizemore.  For starters, he has not set foot onto a baseball field in 2 years.  It is a possibility that he will be incredibly rusty and might struggle to perform again at the big league level.  For some players, that would be less of a concern but for a player who last played baseball in his twenties and who is now playing in his thirties (granted, it was his late twenties and it will be his early thirties), it could pose a greater challenge.  It’s possible that he could shake all rust in Spring Training and come out in April and prove all the doubters wrong although it is impossible to know for sure.

The most optimistic yet realistic scenario for Sizemore is that he comes back to the majors, is solid defensively, and puts up great power numbers for the Red Sox.  My guess is that from the knee and back surgeries, his base stealing days are over and he will not be able to cover as much ground in the outfield that someone else might.  If I was Red Sox management, I would not give him the role of backup center fielder until I knew for sure the kind of speed that he has left.  I would task Shane Victorino with that as he has remained healthy and still has the speed to cover that ground.  Victorino would play center and when he does then Sizemore would be in left field and Gomes/Nava would be in right field.  If Bradley fits in with the Red Sox plan, then Sizemore just becomes a spot starter/platoon player in left, center, and right field only to give people a break when they need it.  So to answer the question that the title of this article poses: the Red Sox are getting a wild card, a player with the potential to be a power bat off the bench or even in the everyday lineup or a player that has played his last days in the bigs.

This post is going to examine the value of the opt-out clause in both the Clayton Kershaw and Masahiro Tanaka contracts. I think this is interesting because the Yankees gave Tanaka an opt-out one year earlier, and gave that option to a commodity with a much more uncertain value.  As we will see, the opt-out clause for Tanaka is going to be a lot more costly to the Yankees than the clause was for Kershaw and the Dodgers.

Let’s start with the projections for each player. ZIPS and STEAMER don’t have anything for Tanaka, but we can make a guess based on the contract he was given that he’s at least expected to be worth a lot of wins over the next several years.  Since he’s the same age, it seems approximately fair to start with 5 wins, and reduce in the same pattern that Kershaw got.  I’ll use the values from Dave Cameron’s excellent article the other day for Clayton Kershaw, and I’ll also take the $/WAR from his projected inflation.  Excess value is the value of that player’s WAR, minus salary.

The key here is not going to be the expected value — it’s going to be the possible variation. Kershaw is expected to get 5.5 wins next year because of the ever-present risk of injury — there are probably Dodgers fans going nuts over that projection because they know that a healthy Kershaw, pitching like he can, is going to be worth closer to 7 wins.  There are certainly scenarios where he manages that, but also scenarios where he tears his rotator cuff and is worthless.  While there is a continuum of possibilities, let’s break the world into two scenarios for each pitcher, an up and a down. The only requirement is that the weighted average of each scenario has to average out to their projections.  I’ve made up some basic numbers here, and you might think they’re reasonable, you might think they’re not, but the point of this article is to illustrate how one extra year and some extra volatility can affect the value of an opt-out clause.

In each scenario, I make the downside a mirror image of the upside. For Tanaka, because he is an unproven commodity, I’ve added 2 WAR to the upside, and subtracted 2 for the downside. For Kershaw, I’ve just added/subtracted 1 for each. I gave each scenario a 50-50 chance of happening.

Let’s think about what happens in each scenario when it comes time to exercise the opt-out clause.  Shockingly, GOOD Kershaw and GOOD Tanaka each exercise the clause. We can see this reflected in the positive “excess value” column of each chart — age 29 for Tanaka and age 30 for Kershaw. They could get more on the free market, so they will. BAD Kershaw and BAD Tanaka both stick with their contracts, because they’re being paid more than market value.  Let’s re-do the charts from the teams’ perspectives, reflecting the opt-out clauses now:

Now let’s take the expected value of these two scenarios, which is in this case a simple average:

We can see that in both cases, the post-option years of the contract become negative propositions for the teams — in fact, they would have to be, by how we’ve implicitly stated the conditions under which the players opt out: if the player were expected to provide positive value to his team, he would opt out.

So how much is the option worth? Ignoring the $20 million posting fee, the Tanaka contract, sans opt-out, was expected to produce $63.9M in excess value for the Yankees. With the option, the expected excess value drops down to $26.1M.  That’s a drop of $37.8M. This could be thought of as the extra money Tanaka puts into his pocket from years 5 onward, if he comes into the league and becomes Justin Verlander.  Kershaw, on the other hand, would be expected to generate $32.3M for the Dodgers, without the opt-out. Now his contract is only worth $19.1M to them. That’s a reduction in value, but because we’ve made him less uncertain, and because the option occurs after year 5, not year 4, the reduction is only $13.2M.  So the extra year and the double variability make Tanaka’s option worth $24.6M more than Kershaw’s.

Again, this depends largely on the choices I’ve made for the range of possible outcomes, and I’ve kind of picked Tanaka’s projection out of thin air (since the excess value of the contract with the opt-out is only $6.1M, considering the $20M posting fee, I would argue that I’m not that far off). I could have made more possible outcomes, or maybe even defined a probability distribution function and integrated over that, if I knew how to do that sort of thing. The only lesson we’re going to be able to take from this is how one year and some extra variability affect the value of the opt-out clause.

Something very strange happened this offseason: the Yankees were outbid for a player they have a clear need for (although all teams need players of this caliber). This player is the best second basemen, and one of the top 10 position players, in all of baseball. Of course this player is Robinson Cano, perennial All-Star, Silver Slugger, Gold-Glover and MVP candidate. I do not need to tell you that Robinson Cano is a great baseball player. But I thought it would be interesting, as a matter of reflection to appreciate Cano’s talent/ be slightly depressed watching him rack up his numbers in Seattle, to rank the best second basemen in Yankee history and to determine where Cano fits in.

First, I think it is important to put the five players to be discussed in some historical context. When one thinks about the great “Yankee positions,” second base does not particularly stand out, at least to me. Like most Yankee fans (I imagine), I immediately think of center field (Mantle, DiMaggio), catcher (Berra, Dickey, Posada, Munson), first base (Gehrig) and right field (Ruth). But is this justified? Lets look at the top five fWAR (FanGraphs’ WAR) totals for each position in Yankee history:

*NOTES: (1) Babe Ruth was counted as a right fielder (2) Stats courtesy of FanGraphs.

As we can see, second base places 5^th behind the four positions I think Yankee fans most associate with greatness. However, no other team in history has had at least five second basemen accumulate at least 37.1 fWAR, and only one team’s top five (the Reds) beat the Yankees’ top five in total fWAR, albeit barely (220.3 to 216.7). Of course not all teams have been around as long as the Yankees have (and some have been around longer) but you get the idea. Suffice to say, second base has been an excellent position in the history of an organization that has had several excellent positions. So while second base places right around where we would expect in terms of other Yankee positions, it is important to reiterate that (1) the four Yankee positions ahead of second basemen on the aforementioned list are insanely good and include some of the greatest players of all time, and (2) the top five Yankee second basemen, compared to other teams’ top second basemen, are among the best ever.

That being said, here are some stats for my top five Yankee second basemen of all time, in no particular order:

*NOTES: (1) Stats courtesy of FanGraphs; (2) These stats are what each player accumulated as a Yankee only.

Like I said before, this is more or less as good a list of top-five second basemen that any team has. Every player on this list was an above-average hitter that played exceptional defense (except for Cano). The one glaring weakness, with the exception of Randolph, is baserunning. This strikes me as a bit odd because second basemen are typically solid in this aspect of the game. Even still, these are five very, very good ballplayers. Now to the top five:

5. Gil McDougald

Gil McDougald’s inclusion on this list is somewhat dicey because he played all over the infield save for first base (he appeared in 599 games at second, 508 at third, and 284 at short as a Yankee). McDougald is included because 1) he did in fact play most of his games at second, and 2) in my opinion, he is one of the most underrated players in Yankee history. The Rookie of the Year in 1951 (his best season with the bat with a 142 wRC+) McDougald was a five-time All Star and a member of the five Yankee World Series championship teams. A player with his versatility is extremely valuable to any team and the fact that he was making his contributions to an organization in the midst of the greatest dynasty in sports history (1949-1964) is all the more impressive. Throw in his above-average bat and you have one great ballplayer. McDougald does not rank 1^st in any of the aforementioned categories but he is the definition of a “jack of all trades” player: he played multiple positions and did everything well.

4. Willie Randolph

Millennials like myself remember Randolph mostly (and quite fondly) from his time as the Yankee third-base coach during the most recent dynasty years (and less fondly as the manager of the Mets), but he had a fantastic playing career in pinstripes as well. Representing the Yankees in four All-Star games (including in 1977, the Yankees’ first World Series title since 1962), Randolph had the reputation as a defensive wizard. The statistics back that assertion up nicely, as his 143.9 Def rating is best among second basemen in franchise history (and his career Def rating of 168.2 is ninth all time among second basemen). Randolph is easily the best baserunner of the five, with a 17.6 BsR (no other player is above -4.5). Randolph was no slouch with the bat either, although his power pales in comparison to the other four players on the list. However, it is known that on-base ability is more valuable than power, and Randolph’s .374 career OBP ranks second. McDougald and Randolph are strikingly similar players (even their fWAR/game is an identical .030) but I decided to rank Randolph higher due to his superior on-base ability.

3. Robinson Cano

The inspiration for this post, Robinson Cano checks in as the third-greatest second baseman in Yankee history. A five-time All-Star and five-time Silver Slugger, Cano’s Yankee career began somewhat randomly during the teams’ terrible start to the 2005 season, and he never looked back.  His 126 wRC+ is tops on the list. He also leads in home runs, batting average, and slugging. However, his Def rating of -10.4 is easily the worst on the list (acknowledging that defensive metrics are far less reliable than offensive and base running metrics). Cano has been one of the very best players in baseball the past several years. Neither McDougald nor Randolph could claim such during their playing days. Cano has been top-five in all of baseball in bWAR (Baseball-Reference WAR) in four different seasons, whereas McDougald has two such seasons, and Randolph none. Had Cano signed with the Yankees this offseason, he most likely would have ended up #1 on this list.

2. Tony Lazzeri

Hall of famer Tony Lazzeri checks in at #2. In his 12 seasons as a Yankee from 1926-1937, Lazzeri played less than 123 games only once, hit at least 10 home runs in every season but two (in those two seasons, 1930 and 1931, he hit 9 and 8 home runs, respectively) and had a wRC+ greater than 100 in 11 straight seasons. He also accumulated at least 2 fWAR every year he was with the Yankees. Suffice to say, Lazzeri was a very consistent ballplayer on same great Yankee clubs (including arguably the great of all time, the 1927 squad). His 48.4 WAR is second on the list. Unlike Cano, Lazzeri was not one of the best players in all of baseball during his playing career, but was simply with the Yankees longer and his counting stats reflect as much, giving him a slight edge over Cano.

1. Joe Gordon

Completely disregarding my reasoning for ranking Lazzeri ahead of Cano, I decided to rank Joe Gordon, another of the most underrated Yankees of all time, as the best second baseman in the teams’ history. He, like many big leaguers in the 1940s, missed time (in Gordons’ case, the 1944 and 1945 seasons) to serve in WWII. In 1942 and 1943, Gordon put up 8.8 fWAR and 6.8 fWAR, respectively, and save for a 2.1fWAR season in 1946, bounced right back and put up 6.9 fWAR in 1947 and 7.1 fWAR in 1948. The point of all of this is that Gordon would have, in all likelihood, continued to dominate in the two seasons he missed, but we’ll never know.

Even though his time in pinstripes, and in baseball for that matter, was shorter than it could have been, Gordon did not disappoint when he was on the field. A Yankee for seven seasons, he was an All-Star in six of them (although his 1946 selection is a bit odd. Check out his numbers that year). In those seven seasons he accumulated 40.1 fWAR, an average of 5.7 fWAR per season. This is easily the highest per-season average of any player on this list (Cano is second at 4.1 with the other three each at 4.0). On a fWAR/game basis, Gordon’s .040 is well ahead of the others (McDougald and Randolph are tied for second at .030). He, like Cano, could claim to be one of the best ballplayers of his time, having placed in the top 10 in overall bWAR five times as a member of the Yankees. Gordon was an elite defender, rating second all-time in Def for a second baseman. Randolph barely has him beat in terms of what they did as Yankees, but Gordon’s per-season average of 20.0 Def easily eclipses Randolph’s 11.1. Couple his historic defensive abilities with his great bat (his 121 wRC+ trails only Cano) and you have a fantastic ballplayer and the best second baseman in the teams’ storied history.

So there is my top five Yankee second basemen of all time. What sets Gordon apart from the rest are his per-season averages, but if you place a higher value on longer-term consistency I suppose Lazzeri would be your guy. But no other player did more in a shorter amount of time than Gordon, hence my ranking of him as #1. Honestly, I could be talked into changing this list around in a number of different ways (exlcuding McDougald and including Stirnweiss and flipping Lazzeri and Gordon just to name a couple) but I think the purpose of a post like this is to try and initiate some interesting debate while admiring the careers of past Yankee greats. Like I previously stated, I think second base is an under-appreciated Yankee position, but the organization has had some truly great second basemen in its history.

In spite of the ridiculous scrutiny regarding his 2013 season, Joey Votto is one of the best hitters in baseball. He also has a large contract that begins in 2014. Big contracts have seemingly brought bad baseball voodoo to some of baseball’s best (injury to Pujols noted). As Votto begins his mega-deal, both ZiPS and Steamer show him declining by over a win in WAR in 2014.  Because of how good he has been for the last four years, I found this projected decline somewhat surprising. I decided to dive into the numbers and found some really interesting things.

Votto has had four straight years of excellence. Since 2010, he has the third-best WAR among position players (25.1), the second-best wRC+ (164), the second-best wOBA (418) and the best OBP (434). Votto is at least in the conversation as the best hitter in baseball over this four-year stretch. But for some more perspective, let’s look at his last four years in detail.

Quite impressive. Votto has earned over six WAR every year except 2012, the year he injured his knee and played in only 111 games. He played many of those games injured as well. The only reasonable complaints are that Votto’s power dropped some in 2013, and his defense was poor (decent for a first baseman). The extent to which Votto’s knee surgery affected his power in 2013 remains to be seen, but it isn’t like his power numbers fell off a cliff.  So what do our beloved projection systems say about Votto’s age-30 season in 2014? They say he will be good but not quite as elite as he has been.

The encouraging part for Reds fans is that both Steamer and ZiPS think Votto’s power will tick up a little. The hope is that Votto’s knee will be healed, and he will return to the doubles machine he once was, with a few more home runs as well. But Votto is also entering his age-30 season. His best power days may very well be behind him. Or maybe not. I’ll get to that shortly.

The other numbers are similar to the four previous years with one noticeable difference. Both projection systems predict Votto’s batting average to drop below 300 for the first time since his rookie season in 2008, where he struggled to a 297 average.  The cause of this decline in batting average is our old friend BABIP. ZiPS has Votto’s BABIP dropping to 334 even though Votto has averaged a 368.5 BABIP for the last four years. BABIP can fluctuate wildly from year to year,  but Votto has shown the ability to maintain a high BABIP throughout his career. We can expect him to do a little better than these projections. If every 10 points of BABIP equals about 0.3 in WAR, Votto is likely to gain between half a win and one full win.

But the equation 10 points of BABIP=0.3 WAR is with all other stats being equal. If Votto’s BABIP is higher than these projections, he is likely to also have some more extra-base hits, including a couple more home runs. This added power would raise his value even more. Both projection systems already have his power rising from last year. Votto could have a few years of solid power left, especially if his knee is fully healthy.

This puts Votto around six-WAR territory. The other important factor will be his defense. Votto’s defense was poor in 2013 compared to his previous two seasons. He was a top-five defensive first baseman in 2011 according to FanGraphs’ Def and would have been top-three in 2012 had he played enough games to qualify. To remain a six-WAR player, Votto will likely need to return to an above-average defensive first baseman. Steamer has his defense at about the same level as 2013. I do not believe ZiPS Def adjusts for position, but it appears they think he will be average to slightly above-average defensively for a first baseman.

The Reds have much bigger problems than their superstar first baseman. They lack the ability to get on base consistently. They have serious question marks in left field and center field. The reality is that the Reds are a borderline playoff team right now and need Votto to be an elite player to have a legitimate chance of returning to the postseason. After looking at the numbers and with the prospect of a fully healthy knee, It is easy to see Votto continuing his run of excellence.

Yoenis Cespedes struggled at the plate this year for reasons unknown to most. Analyzing why he struggled in 2013 versus why he was deemed excellent in 2012 all comes down to sabermetrics. Cespedes’ biggest enemy was actually… himself. Through research and statistics, Cespedes swings at too many inside pitches in an attempt to hit more home runs. The pressure from his overshadowed rookie season may have come back to haunt him this past year. His batting average dropped from .292 to .240 and his OPS fell from .861 to .737 all because of a few changes Cespedes made at the plate. The statistics easily point out the causes for Cespedes’ struggles and how he might be able to fix them for next season. Even though it may seem that Cespedes was a much worse batter in 2013, that is not the entire case. He actually was much better at making contact with pitches thrown to the outside of the strike zone, boasting an increase from 59.5 % to 63.7 %.

   1.  Swinging at Inside Pitches Too Often & Taking Too Many Strikes
Cespedes took a swing at way too many pitches inside the strike zone this season. A number that increased from 65.3 % to 71.8 % from 2012 to 2013. In comparison, when Adrian Beltre took a swing at 71.6 % of inside pitches in 2005, he hit .255 with just a .716 OPS. In addition, when swinging at such a high amount of inside pitches, Cespedes’ hit a lower percentage of them as well — going from 84.0 % in 2012 to 80.4 % in 2013. As a result of his tendency to swing more often at inside pitches, he saw an increase of strikes by 2.5 % (1233 of 1979 in 2012 to 1407 of 2169 in 2013). More strikes lead to more strikeouts and a lower batting average. His strikeout rate increased from 18.9 % to 23.9 % just over the course of a single season.

Swinging at the amount of inside pitches that he did, power pitchers took full advantage of his swing, resulting in a .196 batting average. Against finesse pitchers, Cespedes averaged a .263 batting average. (power pitchers are defined as the top third of pitchers when combining the amount of strikeouts and walks. finesse pitchers are defined as the bottom third) When Cespedes fell behind in the count, he proved to be an easy out; with two strikes and any amount of balls, he batted a horrifying .130. Also, Cespedes is often too eager to swing at the first pitch of a plate appearance when he does not have a trace on the pitcher’s style or location. Swinging at the first pitch resulted in a .209 batting average whilst taking the first pitch resulted in a .252 batting average.

2.  Pulling Too Hard for Home Runs
Cespedes certainly tried to hit as many home runs as possible this season; he did pass the previous year’s number of 23 by three and his power assuredly grew. As evidenced by his spectacle at the home run derby, Cespedes possesses a strength like few others in the MLB. However, he often tried too hard to get the ball over the wall, resulting in an increase in fly ball rate from 39.9 % in 2012 to 45.6 % in 2013. The pressure to improve from critics and fans alike might have pushed Cespedes into trying to hit more home runs than he possibly could. Given his time on the DL due to nagging hand injuries, it surprised most that he even hit this many home runs — either because of lost time or wrist pain.

                                                             The power is definitely still there

 3.  BABIP (Batting Average on Balls In Play)
Cespedes was also just plain unlucky in 2013. BABIP measures the percent of batted balls that end up as hits — either because of defense, luck, or positioning. Basically two-thirds uncontrollable to the batter and one-third placement of the bat. Cespedes ended the 2013 season with a .274 BABIP; whereas the standard and league average nowadays hovers around .300. In 2012, he finished with a .326 BABIP — a lot luckier than this past year. The second reason (pulling for home runs) most likely factors a moderate amount into the regression too. Unfortunately, the causes of BABIP can disguise a player’s true skill level behind solid defense, timing, and bad luck.

The real Yoenis Cespedes is most likely somewhere in between his two major-league seasons but much closer to his rookie season than 2013. Yoenis Cespedes thrived in the spotlight but collapsed under pressure in 2013. His statistics in the 2013 playoffs alone describe his love of the spotlight (.381/.409/.667). Not only does he play well in the playoffs, but he also crushed everyone else in the home run derby this year. Expect Cespedes to be a big bounce-back candidate in 2014 after he can look at why he struggled at the plate. Upon arriving in America from Cuba as a free agent, Cespedes was hailed as a five-tool player and “arguably the best all-around player to come out of Cuba in a generation.” Don’t give up hope on the Athletics’ outfielder just yet.

For more articles like this, visit my baseball analysis and news website: The Wild Pitch

All statistics courtesy of baseball-reference and FanGraphs:
http://www.baseball-reference.com/players/c/cespeyo01.shtml
http://www.fangraphs.com/statss.aspx?playerid=13110&position=OF

Foreword

Two years ago, I began developing a system for evaluating the performance of minor-league pitchers relative to their minor-league level/league peers. My goals were to use only game data that could be extracted from the MLB Advanced Media Gameday archives for every level of the minors (ruling out any of the pitch-outcome data that is available for AA and AAA games), to ignore whether batted balls went for hits or home runs, and to ignore runs allowed. In brief, the challenge amounts to using whatever else information can be compiled from the game-specific dataset to arrive at the best approximation of the pitcher’s true performance, as judged independent of those factors which tend to fall outside their control (defense, park effects, etc.). What eventually follows are the results of applying the latest iteration of this “Fielding and Ballpark Independent Outcomes” method to 2013’s American League starting-biased pitchers.

Basic Steps of Applying the Method to a League

1. Download the relevant details of every plate appearance (PA) from the league’s season into a spreadsheet/database
2. Derive a 24-outs-baserunners-state run expectancy matrix à la Tango in The Book
3. Quantify how each PA of the season impacted the inning’s run expectancy
4. Exclude all bunts and foulouts, plus every PA taken by a pitcher
5. Reweight the proportion of line drives (LD), outfielder fly balls (OFFB), ground balls (GB), and infielder flyballs (IFFB) by ballpark to offset any stadium- or stringer-related anomalies in play event classifications
6. Referencing the run-expectancy value determined for each PA in Step 3, the corresponding basic description of the play (BB vs HBP vs K vs GB vs IFFB vs OFFB vs LD), and the 2 coordinates indicating where the batted ball was fielded (if there was one), quantify what each of the following 12 general PA event types were worth in terms of runs, on average, for the season: 1) walk or hit-by-pitch, 2) strikeout, 3) IFFB, 4) GB to batter’s pull-field-third of the diamond, 5) GB to batter’s center-field-third, 6) GB to batter’s opposite-field-third, 7) LD to pull-third, 8) LD to center-third, 9) LD to opposite-third, 10) OFFB to pull-third, 11) OFFB to center-third, and 12) OFFB to opposite-third.
7. For each pitcher in the study sample, tally up the number of each of the 12 event types that they allowed and in each instance charge them with the exact number of runs determined in Step 6 for the corresponding event type; divide the resulting sum by the total number of events to arrive at a single number for each pitcher that quantifies how a PA against them that season should have affected the inning’s run expectancy, on average (the more negative this number the better the pitcher should have performed on the year)
8. Quantify how high or low the pitcher rated on the value in Step 7 versus the mean of the sample on a standard deviation (SD) basis

What were the 12 Event Types Worth in 2013?

The table below shows how the studied event types impacted run expectancy in AL Parks during 2013, on average. The 2-D direction of the batted ball does tend to be rather consequential for LD and even more so for OFFB.

So as far as Step 7 described above goes, each pitcher in what follows will be charged +0.29 runs for every BB and HBP, -0.26 runs for every K, … and -0.08 runs for every OFFB to the Opposite-Field-Third, with that sum ultimately divided by the total number of PA events to arrive at a single number that quantifies what an average PA against the pitcher in 2013 was worth in terms of runs (per run expectancies). Think of that as the equation being used to evaluate each pitcher’s performance.

Study Sample

The 101 pitchers who faced more than 200 batters as an American Leaguer in 2013 while averaging more than 10 batters faced per game. Data they accumulated as relievers is included in the analysis. Data they accumulated as National Leaguers is not. As before, any PA that resulted in a bunt or foulout or that was taken by a pitcher was excluded.

Scores Computed

The overall rating number described in Step 8 above is termed Performance Score. Steps 7 and 8 can be repeated with the non-batted-ball events (BB,HBP,K) stricken from the numerator and denominator at Step 7, and this result is termed Batted Ball Subscore (in short, how should the pitcher have rated versus their peers on batted balls?). To further understand how the pitcher achieved their Performance Score, a Control Subscore (how many SDs high or low was the pitcher’s BB+HBP% versus the study population’s mean?) and a Strikeout Subscore (how many SDs high or low was the pitcher’s K% ?) are computed. An Age Score is also calculated that quantifies how young the pitcher was versus the population’s mean age, per SDs. Given the method’s minor-league origins, the scores are typically expressed on a 20-to-80 style scouting scale where 50 is league-average, scores above 50 bettered league-average, and any 10 points equates to 1 SD (percentiles will be listed for those who prefer them).

2013 American League Starting Pitcher Results

In the tables to follow, green text indicates a value that beat league-average by at least 1 SD (“very good”) while red text indicates a value that trailed league-average by at least 1 SD. Asterisks indicate left-handed throwers.

Sorting by Performance Score

Here are the Top 33 2013 AL SP per the Performance Score measure. Scherzer edged Darvish for the #1 spot as the top of the list somewhat mimicked the BBWAA’s Cy Young vote.

Detroit and Cleveland each landed five in the Top 33 while Boston, Oakland, and Tampa Bay each placed four. Perhaps not coincidentally, those clubs were also the playoff teams.

And below are the Middle 34 by Performance Score.

And below are the Bottom 34 by Performance Score.

Pedro Hernandez took last place by a comfortable margin as five other Twins joined him on this dubious list of 34. To further corner the market on these sorts of arms, the club has since inked another of the 34 to a three-year free-agent contract.

Sorting by Batted Ball Subscore

Given the system’s unique weighting of batted-ball types by direction, let us examine how the pitchers grade out on this metric. Below are the Top 20 sorted by Batted Ball Subscore. Masterson nosed out Deduno for top honors. Here, the Twins fare better as three besides Deduno crack the Top 20.

 One unique angle of this approach is that a pitcher can be a relatively strong batted-balls performer without being a noteworthy groundball-inducer if their outfield flyballs, line drives, and groundballs are skewed optimally to the least dangerous zones of the field per the batter’s handedness. Colon serves as a prime example of such a pitcher.

Below are the laggards who comprise the Bottom 20.

Garza’s 29 number as an American Leaguer is somewhat scary for the sort of money he’s likely to command as a free agent (he’d earn about a 35 Batted Ball Subscore if the Cubs NL data were factored in). Salazar’s numbers show how a very high rate of strikeouts and good control can successfully offset a dangerous distribution of batted balls by type and direction.

Admittedly, there is a third dimension to each of these batted balls (launch angle off the bat relative to the plane of the field) that would stand to further improve the batted-balls assessment if such information were available.

Other Directions

A variety of things can be done with these numbers, such as breaking them down further into LHB values and RHB values, identifying comparable pitchers who share similar subscores (MLBers to MLBers, MiLBers to MLBers), studying how these values evolve as the minor leaguer rises through the farm towards the majors and their predictive value as to future MLB performance, and so on. And then there’s also the reverse analysis — evaluating hitter performance under a similar lens.

On Tap

Perhaps the most intriguing research question that application of this system raises is, “Would advanced metrics familiarly used to grade pitcher performance yield better results if their equations included batted-ball directional terms?” As a first attempt to test those waters, I plan to follow this up with a post that shows how these results compare to those obtained by variants of more familiar advanced statistical-evaluation methods (SIERA, FIP, etc.). In the interim, I welcome whatever comments, criticisms, and suggestions this readership has to offer.