Archive for Player Analysis

Well well well, MLB has a new replay system set up for every game of this year. Some people – although I would say most – are not too fond of this new system, myself included. They would say that it slows down an already slow enough game, which is true. The way the system is structured allows managers to be exploitative by confirming with their bench to see whether or not it the call should be challenged. This part of the process is what really gets me. Granted I haven’t seen too many games this year but already I miss the arguments between managers/coaches and the umpires; they were fun and made the game pretty interesting (especially when the manager of the team playing against yours got ejected). Regardless, this post is not intended to analyse the dynamics between managers and umpires but rather look at how successful the replay system has been and to examine the tendencies of the challenges. Using the twitter account @MLBReplays I examined all of the calls challenged so far this season. While the sample size is arguably small it did take quite a long time to examine various angles from the 49 calls made (as of the morning of April 9th 2014). For each replay I collected the following information which I then organized into a spreadsheet: Read the rest of this entry »

When I first began this piece, the idea was to title it “Who Has the Most Unusual Skillset in Baseball?” then to spend the majority of the time referring to several players and choosing one, based on statistical evidence, that best fit the bill. However, upon seeing what Alcides Escobar accomplished last season, good, bad, and ugly, there really was no argument to be made for anyone else.

Now, when I say unusual, what I am looking for is a player who somehow possesses incredible strengths and infuriating weaknesses at the same time.  In other words, the complete opposite of balance and well-roundedness. When it comes to Escobar, he has tremendous skills in the field, is electric on the base paths, and may very well be the worst hitter in all of baseball.

Let’s begin with Escobar’s defense. Last season, he was unquestionably one of the best defensive shortstops in baseball. Andrelton Simmons is better than everyone, we know that, but only he and Yunel Escobar bested Alcides Escobar’s UZR/150 of 12.1. Admittedly, if we turn to DRS, Alcides Escobar looks less impressive. Still, he is pegged by DRS as an excellent defender. He finished 2013 7^th among 21 qualified shortstops, right behind Troy Tulowitzki and ahead of Yunel Escobar. Overall, while he’s not Andrelton Simmons, and may not even be the best defensive shortstop not named Andrelton Simmons, almost every defensive metric rates him as a well above average to elite defensive player.

Now, in the spirit of beginning and ending with a positive, this is the time where we must address Alcides Escobar’s hitting. Escobar is the worst hitter in almost every relevant statistic. His ISO of .066 ranked second to last in the league among qualified players, only greater than Elvis Andrus, and we know what kind of power he has. His OBP of .259 was the worst in baseball. (That’s a bad batting average!) His walk rate of 3% was the second worst, superior to only A.J Pierzynski. His wOBA of .247 was easily the worst in baseball, and as a result, his wRC+ of 49 was the worst in the game as well, less than half of what is considered average and the worst mark since Caesar Izturis in 2010. This paragraph feels less and less like a paragraph and more like a checklist of offensive ineptitude. Sure, the argument can be made that Escobar will be slightly less horrible at the plate in 2014, thanks to a depressed BABIP of .264 last season, but aren’t we past that point with him? He did have a BABIP of .344 in 2012, but that was an aberration. Despite his impactful speed, in four full major league seasons, the rest of his BABIP marks are well below .290, including an identical to last season mark of .264 in 2010. Even if his BABIP were to skyrocket from his mostly uninspiring career numbers to above average, something like .300-.305 (unlikely to happen) he would still struggle mightily as a hitter given his lack of power and inability to draw walks.

Now back to a strength of Escobar’s, baserunning. While it is often more difficult to analyze the positive or negative contributions of a player on the base paths, the statistics at our disposal clearly show that Escobar is a difference maker when he reaches base. While 22 stolen bases may not seem like an incredible total, it did tie him for 18^th in the league. Also, he was never caught. Not even once! That is an awesome display of efficiency. Beyond that, there are metrics that suggest he is far better than the 18^th best base runner. Starting with UBR, which pegs him as the 14th best at 4.0. Not surprisingly, metrics that factor in base stealing look even more fondly upon his work. This includes BsR, or baserunning runs above average, where his score of 8.0 ranked him fifth in the Majors. wSB isn’t far behind, as he comes in at 6^th there, at 3.9. The last two stats speak volumes to just how crucial efficient base-stealing is relative to volume base-stealing. Depending on which statistics you value most, Escobar rates as somewhere between a top 20 base runner, to as high as the top five, making him one of the few true difference makers on the bases.

Now that we have examined each element of his game, the question becomes: Given his strengths and weaknesses, what is his value? Does his hitting negate his other contributions, or is he still a positive player? This is why I love WAR! Without it, it would be nearly impossible to even estimate the value of a player like this, given how impactful he is whenever he is on the field, for better or worse. While FanGraphs has him as having been a shade above a one win player in 2013 with a 1.1 WAR, Baseball Reference isn’t nearly as generous, where his WAR was 0.3. Neither of these numbers are particularly impressive, but the 0.3 is especially concerning.

It’s not as if, over the course of his career, he has been much more valuable, either. Based on WAR, FanGraphs views 2012 as Escobar’s best season, with a WAR of 2.1. The problem is, as covered previously, that was the season where his offensive production ballooned to near-league average level (96 wRC+) thanks in large part to a .344 BABIP, something he is highly unlikely to replicate.  It only gets worse when you realize that, while his WAR is reflective of a late game defensive replacement/pinch runner, he was far from that in 2013. He played in 158 games, and somehow managed to compile 642 plate appearances!

It seems that Escobar would fit best as a bench player in the Brendan Ryan/Nick Punto mold. This would require him to be with a team that gets impressive offensive production from the shortstop position, so as to hide his hitting flaws, but is not nearly as impressive on the defensive side, allowing him to contribute in that way. In his current role, however, where he is forced to be the everyday shortstop for a Royals team attempting to compete, he is at best a non-factor.  Isn’t it funny how that’s what we discover about a player who is the complete opposite of a non-factor in everything he does?

Giancarlo Stanton. What a trip this guy is. One second he is hitting home runs and the next he is running to first and coming up lame with a pulled hamstring, or a knee injury, or even an eye injury. He is an enigma that we seemingly know little about. He is hard to project into the future because of the injuries, but the one concrete thing we know about him is that he possesses monstrous power.

Recently I have come to see Stanton as similar to Ken Griffey Jr., in that he hammers the ball and could put up single season home run figures similar to Griffey’s, who hit 56 home runs in consecutive seasons. In addition, Griffey averaged 32 doubles per season, while Stanton averages 36, Griffey had a career OPS of .907, while Stanton’s is .892, and they are only .001 point apart in slugging percentage. I could go on with more statistics, but you get the point, these guys are like statistical clones. Stanton does not have the benefit of playing in the Kingdome like Griffey did, so we should even take into account the fact that Stanton currently plays half of his games in the Petco Park of the East.

Unfortunately, they are also similar in the injury department. I’m not saying Stanton will miss as many games as Griffey, but Stanton has missed 95 games due to injury since the beginning of 2012. What is even more worrisome is that he is hurting in many different regions of the body. I alluded to the numerous injuries in the opening; he has missed time for arthroscopic knee surgery, shoulder issues, and hamstring issues. The ability of each of these separate injuries to flare up again is something that should concern all fans of Stanton, as well as fantasy owners. In fact, I owned Stanton last year in my own fantasy league and we had a running joke going that we couldn’t call him “Giancarlo” (we referred to him as “Mike”) until he hit five home runs. I thought this was a very trivial joke at first, but the other owners had the last laugh because Stanton did not reach five homers until June 15^th, mainly due to injuries.

If Stanton can stay healthy, he may be this generation’s Griffey. He does not have the flair, mechanically perfect swing, or happy-go-lucky attitude that Griffey seemed to carry on and off the field, but Stanton is similar to him where it matters most — in the statistics category. As an avid baseball fan I would certainly not be opposed to watching Stanton bash 600, or even 700 homers over the next 15 years and I know every Marlins fan would thoroughly enjoy that kind of production, assuming he stays in Miami. He may not have quite the average that Griffey achieved (Stanton career: .267, Griffey career: .284) but he can certainly smash the ball at a consistent clip.

Strange as it is, I want Stanton to be like Jeremy Renner in Hurt Locker. I want him to step up to the plate and discern what puzzle the pitcher (or the insurgent) is putting in front of him and then solve the riddle and hit the ball 450 feet, like when Renner disarms a circle of six IEDs. Then, I want him to keep the bomb suit on and run around the bases so he doesn’t injure himself. In fact, he should keep the mask on so he doesn’t get an eye injury again.

I am basically asking for Stanton to break numerous batting records all while playing at half speed (or maybe in a bomb suit) so that he will stay healthy. I know that is unfeasible, but we basically have a prior tale of what will happen if he keeps getting injured. We can always just take a look back at Griffey’s career and see what Stanton’s production will be if he keeps landing on the disabled list at his current pace. But the interesting and exciting thing is that if we want to know what could’ve been if Griffey’s career hadn’t been riddled with injuries, we might get a realistic clue if Stanton can get healthy and remain that way for the years to come. Hopefully we will be able to sit back and enjoy the moments of Stanton’s career where he “disarms” pitchers and launches moon shots off the Marlins’ scoreboard.

The Chicago Cubs have gotten off to a very slow start in the 2013-14 season scoring a total of 9 runs in their first 5 games and as a result of that they are 1-4. The buzz around the city of Chicago is all about the excitement of top prospects Javier Baez, Albert Almora, and Kris Bryant tearing up minor league pitching and rapidly moving up in the Cubs System. All of these players have fantastic stats but the stats don’t truly matter until these players can be productive big league players. The problem is is that these prospects have shown day in and day out that they are ready to move on to the bigs. Almora, might not be quite there yet but Baez and Bryant have proven they are by dominating minor league pitching and posting good spring training numbers. Cubs GM Theo Epstein won’t pull the trigger on sending these guys up. Bringing these players up will significantly improve the quality of the team but many more changes will need to take place in order for the Cubs to be a team to win games on a consistent basis. Here are 3 other things that need to happen for the cubs to start their path to being successful

1. The cubs need to find a reliable, all-around, everyday 2nd baseman. There are many different solutions the their problem at 2nd but first let’s establish what the problem is. Darwin Barney has proven that he is an excellent fielding 2nd baseman but he is an absolutely horrendous hitter. In 2013, Barney posted an atrocious slash line of .208/.266/.303. Not only does this show that he rarely gets hits or gets on base, but when he does it’s mostly because singles. The Cubs have many possible solutions to this problem. One possible solution is to bring up Javier Baez and play him at short and Starlin Castro at 2nd or vice versa. Doing this might slightly weaken the 2nd base spot defensively, but drastically improve it offensively. With the Cubs pitching being surprisingly good in the first few games of 2014, their offense is a glaring problem and Baez would improve it instantaneously.

Another solution would be to slide Luis Valbuena over to 2nd and make Mike Olt the everyday 3rd baseman. Currently, Olt and Valbuena are splitting time at third which is detrimental to the team because both players have shown offensive value to the cubs. Valbuena had an excellent eye and has proven to be adept at drawing walks. He also has shown solid power as he hit 12 homeruns in 108 games in 2013. Olt has also shown the ability to hit for power as he had 5 homeruns in a very good spring training that earned him a spot on the opening day roster. Either of these solutions would be a much better fit for the Cubs then having Barney as the everyday 2nd baseman.

2. If the Cubs want to be good now, their bullpen needs to be consistent, and deeper. The bullpen has been a problem for the Cubs for a very long time. However in 2014 they might show some signs of improvement. In 2013, reliever Pedro Strop Posted a solid 2.83 ERA in 35 innings with the Cubs. In his time in Chicago, he only gave up 11 earned runs, 5 of which were in one performance. Along with solid numbers Strop possesses a 97 MPH power sinker in addition to his best pitch which is his slider. Strop will be put into a much bigger role this season and if the cubs want to succeed he will need to continue to pitch at a high level. In the offseason the cubs also signed lefty Wesley Wright and Jose Veras who in recent history have proven themselves as reliable bullpen options to their clubs. Players like Brian Schlitter and Hector Rondon will also need to step up for the Cubs. If Strop can continue pitching at a high level and the rest of the pen can consistently pitch in late innings. The Cubs will improve as a team very much.

3. Lastly if the Cubs want to succeed Anthony Rizzo and Starlin Castro must have bounce back years. There are many things that I could criticize about these 2 players but there a few problems in their games that are in the most need of fixing. In 2013 Rizzo only hit .233 if Rizzo continues to hit in the heart of the cubs line up, a .233 average is unacceptable. If he was hitting 50 homeruns it might be a different story but .233 with only 23 HRs isn’t going to cut it. In order for the Cubs to succeed, Rizzo will either need to hit 10-15 more homers or improve is average by around 30 points.

Starlin Castro is a much bigger problem for the Cubs. Spending most of the season in the 3 spot, Castro posted a weak slash of .245/.284/.347. Castro’s numbers were only a bit better than Barney’s which makes him a big problem. In addition to his poor offensive play, Castro has been an extremely inconsistent defensive SS his entire career. There is optimism for Castro though. In Castro’s first 2 full big league seasons, he was voted to the All-Star Game and hit close to .300 in both of those seasons. Castro has shown in his career that he has the ability to hit, the question. is will he be able to have seasons reminiscent to his all-star years. Only time will tell for Castro but if he can bounce back along with Rizzo the Cubs might actually be a legitimate team.

Although many things need to happen for the Cubs to be a playoff contender, fans should be optimistic for the future. With a farm system fortified with elite prospects throughout and an improving bullpen, the cubs need their “key players” to perform at a higher level. If all of these things can happen, there might be October baseball played at Wrigley sometime in the near future.

Will Middlebrooks is a popular pick for a breakout player (at least according to the local Boston media).  Now breakouts aren’t really something you can predict, but I will not go into that whole can of worms.  On the surface Will Middlebrooks seems like an obvious choice, a young player with power, coming off a down year with no serious injury history.  The hopes for a Middlebrooks breakout upon closer inspection seem to be driven by hope and optimism rather than actual facts.

Middlebrooks’s glaring flaw last season was his sub .300 OBP (.271), which was driven in large part by his low walk rate (5.3%) and high strikeout rate (26.2%).  Believing that Middlebrooks can improve those numbers is central to any hope that he will have a breakout season.  Alex Speier  showed that it’s not unprecedented for young power hitters with sub .300 OBPs to see a large improvement in the OBP area, but it’s also not guaranteed.  Of the players Speier looked at only 18% saw their OBP increase by 30 points or more (which is what it would take to get Will over .300), so why does the Boston media believe that Middlebrooks will experience this rare transformation?

The main driving narrative behind this optimism is that Middlebrooks was over aggressive and had terrible plate discipline last year, and this allowed pitchers to dominate him. But now that he has worked on his approach at the plate during spring training everything will come together.

This “Willpower” narrative goes all the way to the top

Red Sox manager John Farrell told reporters “I think last year we saw some at-bats where maybe he was pressing a little bit, maybe trying to make up for some previous at-bats where it would cause him to be a little overaggressive or expand the strike zone, That willingness to swing, pitchers didn’t have to challenge him all that much” when explaining Middlebrooks past struggles.  We are led to believe that this former Achilles heel is no more after his successful spring training, as Middlebrooks told reporters “The one thing that sticks out to me is I’ve swung at one pitch outside of the zone this spring.”

Will Middlebrooks had a great spring training ( .353/.389/.667) but spring training stats are useless for predicting regular season success.  And, as it turns out, are far from the only problems with this “Willpower” narrative.  The idea that Will Middlebrooks was overly aggressive and had bad plate discipline is something that can be checked very easily by looking at Middlebrooks’s plate discipline stats vs the league average for last season.

Did Middlebrooks have poor plate discipline last season?

Will Middlebrooks plate discipline compared to the average major leaguer.

Checking the number reveals the surprising fact that Will Middlebrooks’s plate discipline was not terrible but surprisingly average.  He appeared to be a little bit aggressive, swinging a bit more at the first pitch but those 0.9 percentage points translated three more plate appearances with Will swinging at the first pitch hardly enough to ruin his triple slash line.  The next surprising thing that the numbers reveal is that pitchers were actually throwing Middlebrooks more strikes than the average hitter (and more compared to what he saw the previous season), so while pitcher might not have had to challenge him, they didn’t shy away from throwing him pitches in the zone.  Middlebrooks actually saw a lot more pitches in the strike zone than other power hitters.  For players with at least a 0.190 ISO and at least 350 PA only Jayson Werth saw more pitches in the strike zone .  These facts throw the whole premise of this “Willpower” out the window.

How does the image of Will Middlebrooks the aggressive hacker persist when it’s clearly untrue?

Well whenever you see such a low walk rate coupled with such a high strike out rate the easy first assumption is that the player swings at everything, this is a fare guess if didn’t have better data, but we do.  But what about some on who watched every single Middlebrooks plate appearance such as his manager, how could they have such a distorted view.  Well everything is relative, relative to an average major-leaguer Middlebrooks’s plate discipline and his approach were average but compared to other players on the Red Sox Middlebrooks was aggressive and undisciplined.  The Red Sox as a team swung at the first pitch less often than any other team in the majors.  So when not watching Middlebrooks, John Farrell was watching some of the most patient and disciplined hitters in baseball so this is an understandable bias.

The highly improbable feat of chasing only one pitch out of the strike zone over 26 plate appearances.

Now let’s look at Will’s assertion that he only chased one pitch out of the strike zone over his first 26 plate appearances (that’s the number he had prior to his quote).  This would be incredible and might even be meaningful if it were true.  We don’t have spring training plate discipline numbers so we will do a Gedankenexperiment (what Einstein called thought experiments because he was German) and assume the Will saw 100 pitches over those 26 plate appearances (lower than his career average rate and a bit below league average) and half of those were out of the strike zone (also generous considering that usually more than half of pitches are out of the strike zone and in spring pitcher are rusty and of a lower talent pool) this would give Will Middlebrooks a 2% chase rate ( chances are it would have to be lower than that for him to only chase one pitch over 26 plate appearances but we are giving him the benefit of the doubt).  This would be really impressive for a guy who normally chased around 30% of pitches (it would actually be impressive for anyone), and it’s a number that no one has ever sustained for a full season.

How rare is 2% chase rate over that short a time frame?  It’s so rare that no one even came close to it last year.  The closest was Shane Robinson, when last year in the month of June he had 27 plate appearances and only swung at 7.7% of pitches outside the strike zone, that was the lowest chase rate any player had during any month last season (assuming they had at least 20 plate appearances).

Given our prior knowledge about Will Middlebrooks and major-league hitters in general I will go out on a limb and say that I believe Middlebrooks swung at more than one pitch out of the zone.  I bet Middlebrooks believes he only swung at one pitch out of the zone, and this more than anything might point to a flawed understanding of the strike zone.  So while any player can improve by improving their plate discipline (case in point that Joey Votto can still benefit from it) its not a cure-all for baseball problems, and Will Middlebrooks’s problems extend beyond his plate discipline.

If plate discipline wasn’t the reason Middlebrooks was terrible last year then what was the problem?

Part of Middlebrooks’s problem was his abysmal .263 BABIP, this will likely be closer to league average in 2014 and is probably one of the best reasons to believe that Middlebrooks will be better than he was last year.  Unfortunately it sounds much better to say you are working on your plate discipline in spring training than to say you are hope your BABIP will regress towards the mean.  But BABIP is only part of the picture it doesn’t explain his 5.3% walk rate and 26.2% strikeout rate (the low BABIP and therefore production might have led pitcher to throw Will more strikes thus diminishing his walk rate, but this would only be a small effect).

Middlebrooks’s real problem seems to be with making contact, especially when it comes to pitches in the strike zone. He was 212th out of the 237 players with at least 350 PA last year in terms of zone contact (that means 89% of players are better than him), making contact only 81.4% of the time when he swung at a pitch in the strike zone.  This low zone contact rate is probably a large part of the reason pitchers felt comfortable throwing him so many pitches in the zone.  This issue was further compounded by the fact that when Will did make contact the ball went foul slightly more than half of the time (50.4% compared to the league average of 48.1%).  This leads to his high strike out rate.

Look at it this way:

a)      when Middlebrooks swung his chance of making contact with the ball was below average, and

b)      when he did make contact the chance of that ball going in fair territory was below average, and

c)       if that ball was put in play the chance of it being a hit was well below average.

These issues meant pitchers could throw Will lots of strikes, and if a player with average discipline sees fewer balls than average then they are going to walk less than average.

Will Middlebrooks will most likely be better than he was last season (more of a bounce-back than a breakout), and he might even have a breakout season but it will take more than improved plate discipline for that to happen.

All stats are from FanGraphs (used the regular plate discipline stats not the pitch f/x ones) with the exceptions of pitches per PA, 1^st pitch swing%, and foul ball stats which are all from baseball-reference.com

Also the quotes are from the Alex Speier article, although I believe they were given to the media in general.

Ever since Matt Holliday came into the league in 2004, he has been a model of consistency. His WAR increased after each of his first two seasons before peaking at 7.2 WAR in his fourth MLB season. Since reaching 7.2 WAR, Holliday has yet to fall below 4.5 WAR. While Holliday has yet to experience any significant declines in production, he has seen a few areas of his game begin to decline, especially in his power production. For a 34-year-old player, this is not incredibly surprising, but as a power hitter, it is a little concerning. With Holliday heading into his age-34 season, it is important to question whether he is still the model of consistency that he has been since reaching the MLB. For the 2014 campaign, the ZiPS Projection System sees Holliday declining a career high 1.4 wins all the way down to 3.1 WAR. This is still a very respectable total, but it is a quick drop for such a steady performer and could indicate further drops in production.

As I mentioned above, Holliday’s power production has been on a steady decline. His SLG% has declined for 3 straight seasons and settled in at .490 in 2013, which is his lowest SLG% since his rookie campaign in 2004. Holliday’s Isolated Power has dipped each of the past two seasons and even reached a career low of .190 in 2013. Both these numbers are very impressive, especially since they are at or near his career lows; however, they still represent an alarming trend with his power production. As would be expected with a lower SLG% and ISO, Holliday’s HR/FB% has declined for two straight seasons falling to 15%. While Holliday has never been considered a plus fielder, his UZR/150 has declined each of the last 3 seasons all the way down to -7.0. With all these statistics declining, Holliday’s WAR has dropped each of the past three seasons.

While Holliday has seen some dip in his power production, many other areas of his game have improved or stayed relatively constant. Also, despite his SLG and ISO declining, Holliday has still topped 20 homers in each of the past 8 seasons. He has also had a very healthy BB% since 2008, as it has remained above 10% each season and reached 11.5% in 2013, just under his career high of 11.9%. Even more impressive than his steady walk rate is that he lowered his K% to 14.3% in 2013, which was just above his career best K% of 13.8%. Altogether, Holliday was able to set a career best BB/K ratio of .80 in 2013.

In recent years Holliday has maintained both a high Batting Average and a high On-Base Percentage. Holliday has remained such a strong contributor at the plate, despite his worsening power, in large part because his OBP has remained extremely high. OBP is something that usually ages very well, which is encouraging for Holliday because so much of his offensive value hinges on his ability to reach base. In each of the last 7 seasons, Holliday’s wRC+ has been over 140 and was even 148 in 2013. For reference, 100 wRC+ is considered average, so 140 is excellent. There is no doubt that Holliday has remained an outstanding hitter over the past few years, but the real question is whether he will see a significant drop in production as he enters his age-34 season.

While his overall production has remained impressive, it is important to look at his contact rates and balls in play data in order to determine if this production is likely to continue. Throughout his career, Holliday has had an incredibly high Batting Average on Balls In Play (BABIP), with his career BABIP at .343. However, his BABIP dropped to a career low of .322 in 2013. Despite his BABIP falling from the previous season, he was still able to increase his batting average, which suggests he can continue to hit for a strong average even if his BABIP falls a little more. While his SLG and BABIP were down last year, Holliday actually increased his LD% above his career average, but also saw his Infield Flyball% (IFFB%) spike to 13.6%. Another encouraging sign with his LD% increasing was the fact that he also increased his Contact% to 81%, which marked a career high. His high contact rate no doubt helped him cut his K%, which will be important moving forward.

As Holliday continues to age into his mid-30’s, it will be interesting if he can remain the model of consistency that he has been for his entire career. It is clear that Holliday cannot sustain his current level of success for the remainder of his career, but little evidence suggests that 2014 will be the first year he experiences a significant drop in production. His lessening power is not a major concern to his overall game as long as he is able to maintain his high OBP skills and low K%. Turning back to the ZiPS projection of a 3.1 WAR, I do not see Holliday’s production taking that big of a hit, as their projection also calls for a .029 drop in OBP, which seems unlikely given his consistency in being able to get on base and the fact that OBP tends to age well. I expect Holliday to continue his slow decline, but I still see him posting a WAR above 4.0 and an OBP north of .375, especially if he can maintain a BB% in the double digits.

I’m entering my fourth season of fantasy baseball this year and in my quest for my first championship I stepped up my preseason work to include making my own projections for players and creating my own dollar value system for my league’s custom scoring (6×6, standard with OPS and K/9 added). When making projections for players this year, I looked at their last three seasons in the Majors and used their Steamer and ZiPS projections to make sure I was in the same universe or had solid reasons for my different projection. I made projections for about 300 hitters and 200 pitchers, which I feel are grounded in reality and will give me an edge in my fantasy endeavors this year.

However, while I’m pleased with my projections and it’s definitely better than when I first started playing and just knew Yankees and other AL East players, my projections are still very limiting. One of the main problems is that I’m producing a single stat line for each player. It’s based on what they’ve done previously, how they’re trending, and how I and other systems think they’re mostly likely to produce in 2014, but it’s still just a single projection. More advanced projection systems, like PECOTA, compare a given player to thousands of other Major Leaguers to find comparable careers and produce various projections and each projections probability of occurring.

Projection systems like this recognize the inherent uncertainty of projecting future baseball performance and instead of giving one stat line, give us a range of outcomes with their likelihood and produce more accurate results. Now, I am just dipping my toe in the water of finding comparable players and making projections based on that but I wanted to see how this type of system would change my valuation two outfielders who will turn 27 this season, Justin Upton and Jay Bruce. Bruce will turn 27 in April and Upton turns 27 in August. They’ve both been big fantasy contributors in the past, Bruce is more consistent in his production while Upton has been streakier, with hot and cool months and peaks and valleys of home run and stolen base totals. I’ve put my projections for them below with a dollar value based on a 12 team league with 22 roster spots and a 70-30 hitters-pitchers split.

I’m projecting them to produce similar value, but Bruce definitely has an edge. To find comparable players to Bruce and Upton, I looked at all MLB season from 1961 through 2013 (61 being an arbitrary start date based on how much data my laptop could sort through and organize with John Henrying it’s CPU). I narrowed down to players with similar home run and stolen base totals in their age 23 to 26 seasons, along with average, OPS, strikeout and walk percentages, and playing time in an attempt to find a list of similar hitters.

For Jay Bruce I found 19 comps and I found 26 for Upton, there’s a link to the google doc with the full list below which I recommend checking out, it’s not included here so I can save some space. Now that I have the comparable players, I want to see how the performed in their age 27 season to give me a range of outcomes for both Bruce and Upton. I’ve included some bullet points here, again with the full spreadsheet linked at the end.

Mean and Median Value of Comparable Players’ Age 27 Season

• The average dollar value of Upton comparables was $27.17 and the median value was $31.49.
• The average of Bruce comparables was $21.39 and the median value was $19.51.

Best Case Scenario

• The best case scenario for Upton would be to follow Bobby Bonds’ age 27 season, where he put together his power and speed (39 HRs and 43 SBs) and bumped his average up to .283 from .260 in the previous year. I don’t think the HR total is out of the question, definitely hard and more than I’m predicting, and I think the average is within reach, but Bonds was regularly stealing 40 bases a year at this point which Upton is clearly not.
• The best case scenario for Bruce would be to follow Dale Murphy’s age 27 season. Murphy hit .302 that year, with 36 HRs, scoring 130 times and driving in 121 RBIs. While a .300 average may seem unfathomable for Bruce, Murphy hit .281 the year before and .247 the year before that. What makes this situation most unlikely, is that Murphy had a little more speed than Bruce (most seasons stealing bases totaling in the high single digits or low double digits) but he swiped 30 when he was 27, probably out of Bruce’s reach.

More Realistic Good Scenarios

• While I don’t expect Upton to reach Bobby Bonds level, it’s not hard to imagine him producing a line similar to Reggie Jackson’s 1973 when Jackson was 27. From 1970 to 1972, Jackson’s home run highs and lows by season were 23 to 32, his stolen bases ranged from 26 to 9, and his average fluctuated from .237 to .277.  There’s the volatile situation that we’ve grown accustomed to seeing from Upton. In 1973, Jackson put it together and hit 32 dingers, stole 22 bags, and hit .290.  Upton has already produced remarkably similar lines (2011 – 31HR/21SB/.289 avg) and could put it together for 2014.
• Jay Bruce isn’t going to steal 30 bases but he easily follow the 27 year old season of a former Cincinnati Red, Adam Dunn. Dunn was reliably hitting 40 home runs a year at this point (seriously, four straight season with exactly 40) and while Bruce has yet to reach the 40 mark, it’s not outside the realm of possibilities. The big difference with Dunn’s age 27 season from his other years is that he got his average up to .260 (bookended with .230 seasons), stole 9 bases, and had over 100 runs and RBIs. With Bruce entering his power prime, I think 40 homers is definitely possible, if still unlikely, and hitting .260 is definitely in his wheel house.

Outside of Injury, Worst Case Scenario

• For Upton, if he stays healthy the worst case scenario is following former Phillies 2B, Juan Samuel. Samuel had between .264 and .272 the four previous season, with home run totals as high as 28 but reliably in the high teens, and had stolen at least 30 bases each year. At age 27 though, his average fell to .240, he only hit 12 home runs (and never exceeded 13 again), and while he could rely on his speed and stole 30 bases he failed to produce 70 runs or RBIs. Not the most likely situation for Upton, but I could envision it with less stolen bases.
• For Bruce, the floor doesn’t get that low. If he reaches 500 Abs the worst comparable is Torii Hunter’s age 27 season where he only hit .250 and stole 6 bags, but still hit 26 homers and drove in 100 RBIs. Given Bruce’s consistency and the consistency of his comparables, I’d expect a high floor.

The Merciful Conclusion

 I know this took up a lot of room and we’re all happy this is almost over, but what does this mean. First, this is pretty rudimentary with no set formula for finding comparable players, I did my best but they’re definitely not one to one matches and should be taken with a grain of salt. However, I think this helps articulate a fundamental difference between Jay Bruce and Justin Upton. Bruce is a high floor, more limited ceiling guy and I’ve got more confidence that his 2014 will fall close to my projections. I know I’m buying about a .260 average, with a couple of stolen bases, mid 30s home runs with a little wiggle room, in a good lineup.

Justin Upton is a lotto ticket guy. I’m sticking with my projection for his season which falls between the extremes, but if he repeats his 2011 or puts together his tools that he has demonstrated at different points of his career, he could finish right behind Mike Trout among fantasy outfielders. At the same time, I could see him producing a line like his big brother BJ did last year, okay maybe not that bad, but definitely not worth his draft price. Who you take depends on what path you want to believe and who you already have on your team, but I think laying out these options and using player comparables definitely adds to fantasy projections and will be a staple I’ll use next year.

As promised, here’s the link to the full list of comparable players used for this article: https://docs.google.com/spreadsheet/ccc?key=0AmP-CH5MqzENdFZSZ0xhQVZiYWxNSVQxYzBsOFh3YkE#gid=0

The MLB season is quickly approaching, and I am running out of ways to entertain myself until real baseball starts again.  One way that I attempted to do so today was to prepare a guide about strengths and weaknesses of offenses by team.  I just worked with the AL because I didn’t feel like adjusting the data for DH and non-DH teams to be in the same pool.  Using FanGraphs’ infallible Depth Charts feature, I gathered every American League team’s projected totals for AVG, OBP, SLG, and FLD, in order to see some basic tendencies for each team coming into the 2014 season.  I plugged some numbers into 4 variables which I thought would give a better-than-nothing estimate of how a team’s offensive roster was set up. Here are the stats I used to define each attribute:

Contact: AVG

Discipline: OBP – AVG

Power: SLG – AVG

Fielding: FLD

These variables are about as perfect as they are creative (which is to say, not very).  However, this was intended to be a fairly simple exercise.  For each variable, I ranked all the teams and assigned a value between -7 and 7.  The best team in the AL received a 7, second best a 6, and so on.  A score of 0 is average and -7 is the worst.  Here are the results:

As an inexperienced embedding artist, I feel obligated to include this link, which should work if the above chart is not working in this window.

Immediately, one thing popped out at me. The Royals are 1st in Contact. They also are 1st in Fielding. This is good, since they project to be dead last in Discipline and Power. These facts going together really is odd. For the most part, teams fit into more general molds. The White Sox and Twins are below average in everything. The Yankees, Red Sox, and Rangers, are below average at nothing. The Rays and A’s are, to no one’s surprise, copying each other with good Discipline and Defense.

In fact, outside of the Royals, there isn’t another team who is 1st or 15th in any 2 categories, and Kansas City did it in all 4. To figure out how they got here, let’s look at some of the ways they stick out from the rest of the league.

In 2013, the American League had a 19.8% strikeout rate. Of all the Royals’ projected starters in 2014, Lorenzo Cain had the highest 2013 K% at 20.4%. Alex Gordon sat at 20.1%, and you won’t find anyone else above 16.1%. Not satisfied with an overall team strikeout rate about 3 points lower than the league average in 2013, the Royals went out and acquired Omar Infante and Nori Aoki this offseason, whose respective rates of 9.1% and 5.9% ranked 8th and 1st among all hitters with 400+ PA last year. It’s obvious why the Royals batting average is supposed to be 8 points higher than the 3rd best in the league. They put the ball in play.

Unfortunately for them, putting it in play is about as much as they can do. They’re the least likely team in the AL to be clogging up bases with walks, and they’re the least capable team to drive in runs with power.

In 2013, the American League had an average Isolated Power of .149. Alex Gordon led the Royals with his .156 mark. And that was it for the above average power hitters. Even Designated Hitter Billy Butler couldn’t muster up anything better than a .124. The team’s ISO was .119, which won’t be affected dramatically by the arrival of Aoki and Infante, whose ISO’s averaged out to .108, but who replace weak-hitting positions for the Royals.

Oh, and for discipline: they don’t walk. They don’t like it. GM Dayton Moore got in trouble for saying something dumb about it, and the data suggest Manager Ned Yost may not have been aware they existed when he played. To the Royals’ credit, they did acquire Aoki, whose 8.2% rate last year was ever so slightly higher than the AL average of 8.1%. Omar Infante’s rate was just above 4, though, and their 6.9% team rate probably won’t be much better this year.

Lastly, fielding. Kansas City could flat out field, winning 3 Gold Gloves, and saving a mind-blowing 80 runs according to UZR. That number, more than double (!!!) anyone else in the AL in 2013, was the 2nd highest UZR ever in the AL, trailing only the 2009 Mariners. Those 80 runs are almost sure to decrease in 2014, but there’s little reason to argue that any other team in the AL will be expected to save more runs with the glove this year.

Overall, the Royals offense could be nuts in 2014. They won’t strike out, and will put the ball in play. There won’t be many other ways they get on, and they won’t be hitting the ball out of the park much. If last year is any indication, they should save some runs for their pitchers when they’re out in the field. No matter how they turn out this year, there’s one thing to remember. If you’re watching a team effort from Kansas City, there’s a decent chance that no one in the rest of the league is doing it better. There’s also just as good a possibility that everyone is.

Let’s face it, people love the home run. It’s why players like Mark Reynolds can find jobs. These days, we aren’t surprised when we see a couple of home runs in one game. It wasn’t always like this, however. Home runs used to be a rarity among baseball events. In the early 20th century, it wasn’t uncommon for a player to lead his league in baseball by hitting 10-15 home runs. This brings me to the question: how has the home run actually changed? Not in terms of its frequency, but in terms of its value. More specifically, its value in runs. To approach a solution to this question without arduously parsing through hundreds of event files, we must find a way to mathematically frame the game of baseball in a way that encourages simplicity but doesn’t lose the most familiar parts of the game.

Markov Chains

The first batter of the game steps to the plate and sees no runners on base with none out. He pops up. The second batter steps to the plate and sees the immediate result of the last at bat: an out. The second batter walks. The third batter then sees the immediate result of the second batter’s at bat: a runner on first base. The stream of batters stepping to the plate and being placed into a state resulting from the previous batter’s at bat exemplifies the nature of a Markov Chain. When a batter steps into the batter’s box, his current state (whether it be an out situation, a base situation, or a base-out situation) is only dependent on the previous batter’s state. This is known as the Markov Property. Using this structure, we can simulate any baseball game we’d like. However, to keep our calculations simple, we should introduce some new rules.

The Rules of the Game

1. A batter can only attain a BB, HBP, 1B, 2B, 3B, or HR.
2. Outs only occur via a batter getting himself out.
3. Anything other than the events from 1) is assumed to be an out.
4. When a batter gets a hit, the runners on base advance by as many bases attained by the batter (e.g. a double with a runner on second will score the runner on second).

These are the rules of the game. There are no stolen bases, no scoring from second on a single, and no double plays. We have stripped the game down to only its essentials, while implementing certain changes for our own convenience. For our purposes, we don’t care about Mike Trout’s 33 stolen bases, only the fact that he mainly attains his bases through the events we allow.

The Out Chain

We assume that the probability of a batter getting a single at any point during a season is the number of singles he gets for the season divided by his plate appearances. We do this for the probabilities of all our desired events. By doing this, we can construct a simple Markov Chain where players step to the plate and find themselves batting with 0, 1, or 2 outs. We find that this chain is irreducible, meaning that each state (0, 1, or 2 outs) eventually leads to every other state. This, and the fact that we are dealing with a finite number of states, leads us to the existence of a probability distribution on our state space of outs. It so happens to be that when a batter starts his at bat, he does so with an equal probability of seeing 0, 1, or 2 outs, i.e. the probabilities of a batter seeing 0, 1, or 2 outs when he comes to the plate are all 1/3. The knowledge that outs are uniformly distributed over our game allows us to construct probabilities for a more complicated chain that should shed light on our original question.

The Base Chain

We now place our focus on the stream of batters who see a certain base situation when they step to the plate. The transitions of base situations are dependent on the out situation, as can be seen when a batter bats hits with 1 out versus 2 outs. Batting with 1 out, if the player makes another out, then the base situation stays the same for the subsequent batter. If he does this with 2 outs, however, then the inning is over and the base situation reverts to the state where no one is on base in the next inning. Fortunately, we know that the probability of a batter seeing any number of outs when he steps to the plate is 1/3. In a similar manner to the Out Chain, we find that every state in the Base Chain leads to every other state. The “runners on the corners” state eventually leads to the “bases loaded” state, which eventually leads to the “bases empty” state, and so on. Since there are finitely many base situations, we are led to a stationary probability distribution on the state space of base situations. That is to say, there is a probability associated with a runner stepping to the plate and seeing the bases empty, and another for seeing a runner on first, etc.

Results

Using this method, a player in our universe who stepped to the plate in 2013 saw the bases empty with an approximate probability of .467. That same batter saw the bases full with a probability of .103 and one runner on first with probability .210. If a team managed to load the bases, they’d find that they generally had to wait about 10 more plate appearances before they next loaded the bases. If they put runners on the corners, they generally had to wait 42 more plate appearances before they did so again. All of this leads us to some of our final conclusions. In the context of our rules, the expected number of runners on base in 2013 was .908, meaning that the expected value of a home run was 1.908 runs. This method generates home run values that are always between 1.8 and 2.2 runs. The following is a table of all of the expected home run values this method generates from the seasons of the last 25 years:

In the last 25 years, we predict that a home run had the greatest value in 1999, at 1.972 runs. This is a reflection of the heavily offensive environment of the season, when big bats such as Sammy Sosa, Mark McGwire, and Barry Bonds were getting on base at staggering rates. The following is a graph of all of the home run values the system predicts from 1884 through 2013:

We see that this system predicts home runs to have been of more value from around 1889 to 1902, when the home run hovers at around 2.00-2.15 runs. While most players of this generation weren’t hitting home runs, they were certainly getting on base often. In 1894, 38 players had on base percentages greater than or equal to .400, compared to 7 players in 2013. When on base percentages are higher, more people are on base, and this increases the expected value of the home run. Under our restrictions, however, the home run hasn’t been worth 2.00 runs since 1950 and these days it fluctuates between 1.90 and 1.93 runs. While these estimates are all under the umbrella of rules and assumptions, this framework allows us to more easily generalize the game of baseball while preserving its most important aspects. It’s this framework that gives us the power of estimating that, while Chris Davis‘ 53 home runs were probably worth 101 runs in 2013, they may have been worth 114 in 1894.

While watching the playoffs last October, I realized that I had never seen rookies play such a prominent role in the postseason before.  Pitchers like Michael Wacha, Gerrit Cole, Hyun-Jin Ryu, and Sonny Gray propelled their teams into contention during the regular season, and took the hill in multiple elimination games.  The inimitable Yasiel Puig had a similar impact on the Dodgers’ fortunes in 2013.

This observation led me to investigate rookie performance during the 2013 regular season.  Were rookies contributing to the success of their teams more so than in the past?  Were rookie pitchers outperforming rookie hitters?  How about rookies on playoff teams versus non-playoff teams?

Using WAR data from Baseball Reference (sorry, guys) I measured rookies’ contribution to overall team success in 2000-2013, defined as rookie WAR divided by their team’s WAR.  A few definitions before jumping in to the findings:

• Rookies are players who have accumulated less than 130 AB (or 50 IP) and less than 45 days on an active roster prior to their rookie season
• For consistency across time, teams that won the second wild-card slot in 2012 and 2013 are not considered playoff teams (u mad, Reds and Indians fans?)
• Rookie pitcher WAR = amount of WAR created by a team’s rookie pitchers
• Rookie pitcher share of WAR = % of a team’s WAR created by rookie pitchers
• Rookie batter WAR = amount of WAR created by a team’s rookie batters
• Rookie batter share of WAR = % of a team’s WAR created by rookie batters
• Rookie total WAR = Rookie batter WAR + Rookie pitcher WAR
• Rookie share of total WAR = Rookie pitcher share of WAR + Rookie batter share of WAR

In chart 1, rookie share of total WAR for the average team in 2013 (11.3%) is above the long-run average of 8%, and was only exceeded in 2006 (12.7%).  But there was no discernible difference in rookie share of total WAR between the average playoff team (10.9%) and non-playoff team (11.4%) last season.  So far, it would appear as though I need to adjust my TV.

The data becomes more interesting when the average team’s rookie share of total WAR is decomposed into pitcher and batters’ contributions (chart 2).  There is a rapid rise in rookie pitcher share of WAR between 2010 and 2013, peaking last season at 6.7% of the average team’s WAR.  This increase was so strong, it more than made up for a decrease in rookie batter share of WAR during the same timeframe, from 6.5% in 2010 to 4.6% last season.

These trends become starker when the analysis is limited to playoff teams (chart 3).  On the average playoff team in 2013, rookies provided 10.9% of WAR, a step down from the high reached in 2012.  But there is still a huge rise in rookie pitcher share of WAR between 2010 and 2013, to 8.7% last season, and a concurrent decrease in rookie batter share of WAR, to 2.2%.  In other words, 80% of the average 2013 playoff team’s rookie total WAR was generated by pitchers.  If not for a certain Cuban-American hero with a penchant for bat-flipping, that share would have been even higher.

But some evidence, as well as anecdotal observation, suggests that pitchers in general have become more dominant over the past few seasons.  Is this trend, observed so far among rookies, true of all pitchers?  Over the past fourteen seasons, the average team has generated between 36-44% of WAR from pitchers (chart 4).  This share has been consistent over time, and has edged up only slightly during the past few seasons.  This suggests that rookie pitchers, especially those on playoff teams, really did excel in 2013.

Now, let’s look at just how good the rookie pitchers on playoff teams were last season (chart 5).  Together, the 54 rookie pitchers on 2013 playoff teams generated 29.6 WAR, which is slightly higher than last year’s total (29.1 WAR) and much higher than the long-run average (16.0 WAR).  What’s even more impressive is that last season, 57% of all 30 teams’ rookie pitcher WAR was generated by the rookie pitchers on playoff teams, a higher share than in any other season since 2000.  Cumulatively, 54 rookie pitchers on 8 teams outperformed 151 rookies on 22 teams.  Not bad.

But wait…there’s more.  By focusing on the best rookies on playoff teams (arbitrarily defined here as those who generated 1+ WAR), we see that there were 20 such players last season (chart 6).  Of that number, 16 were pitchers, like Shelby Miller, Hyun-Jin Ryu, and Julio Teheran.  Five of those pitchers were on the Cardinals (Miller, Siegrist, Wacha, Rosenthal, and Maness.)  The concentration of top rookie pitchers on playoff teams last year is the highest in at least fourteen seasons.

My initial observation, “Wow, there are lots of rookie pitchers killing it in the 2013 playoffs!” looks to be borne out in the data.  This raises two other interesting questions:

1.  For any of last year’s playoff teams, did rookie pitchers provide enough value to get their team into the playoffs?

2.  Is the rookie pitcher observation a one-time anomaly, or indicative of a larger trend?

The first question is relatively easy to answer.  We can compare each playoff team’s rookie pitcher WAR (essentially, how many more games the team won because of rookie pitchers) to the number of additional games each playoff team could have lost and still made the playoffs without tying a second-place team (let’s call this the buffer). 

For four out of eight playoff teams (again, I exclude the second wild-cards), rookie pitcher WAR is higher than the buffer (chart 7).  But since Detroit and Tampa made the playoffs by one game, and since Pittsburgh’s rookie pitcher WAR is less than one game higher than the buffer, it’s hard to argue that rookie pitchers definitively moved the needle for them. Andy Dirks or Yunel Escobar could have just as easily gotten their teams over the hump, since they also created more than 1 WAR.

The Cardinals are the one team whose rookie pitchers probably got them into the playoffs.  They got 9.7 extra wins from their rookie pitchers (almost 23% of the entire team’s WAR), and made the playoffs by 6 games.

The second question is harder to answer, since the 2014 season hasn’t started yet.  There’s no clear reason why rookie pitchers on playoff teams would suddenly start playing extremely well, especially since it doesn’t look like they’re causing their teams to make the playoffs.  The likeliest explanation is that the top teams in the league happened to have outstanding rookie pitchers last year.  Sometimes, “stuff” happens.

But if you want to prove me wrong, and show that last year’s playoff teams have developed great farm systems capable of producing more top rookie pitchers, pay close attention to what Jameson Taillon (Pirates), Carlos Martinez (Cardinals), Jake Odorizzi (Rays), and Allen Webster (Red Sox) bring to the table in 2014.  All four pitchers are on Baseball America’s list of top 100 prospects, are on last year’s playoff teams, and are projected to crack the majors this season.  If they get off to a hot start, and if they help their teams return to the playoffs, I might have to revisit my conclusion next winter.