Draft prep: Framing the problem

So you’re preparing for your fantasy draft. You’re caught up on FanGraphs, checked for recent injuries at Rotoworld, maybe skimmed a few headlines from your other top 11 baseball news sites. Maybe you’ve even downloaded the FanGraphs positional rankings, and are planning to keep the file open during the draft as a reality check against the pre-set rankings of the site your league uses.

But really, what do the guys at FanGraphs know? Sure, they know a lot about baseball, and statistics, and this year’s projections, and a handful of underlying stats that tend to predict future performance. But what they don’t know is whether your league uses OBP instead of AVG, or OPS, SLG, or batters’ strikeouts, or maybe holds and FIP and pitcher fielding percentage. If this is your situation, then I feel your pain. My fantasy league uses eight statistics for batters and pitchers, three each beyond the usual five. (In case you’re curious, the mysterious six are: Batter hits, K’s, & OPS; Pitcher holds, losses & complete games).

These differences matter. If your league uses OBP, Joey Votto turns from a fantasy player who’s solid in four categories (including average, where his impact is limited because he walks all the time) to a guy with a truly elite skill. Maybe it’s easy for you to account for the relative value of a Joey Votto, but how well can you project the 25th through 35th outfielders? Some might be much better or worse in your league. If you have batter strikeouts, as in my league, how do you value Mark Trumbo and his home run power against the elite contact skills of Norichika Aoki?

Generating your own rankings

One answer, and the one I opted for, is to generate rankings based on your own league’s stats. Now, this may sound a bit too work-intensive and time-consuming for most of you (especially those of you with relatively normal priorities), but in reality it wasn’t as time-consuming as I expected.*

First of all, there’s no need to reinvent the wheel. There are lots of projection systems out there that are available to the public, and some of them are quite good. I decided I would simply download all the projections listed on FanGraphs, and average them out. And then, after thinking for a little while about the costs and benefits of that approach, I decided I wouldn’t do that at all, and instead would use the results of just one projection system. But which one should I use? Luckily, that’s yet another bit of analysis we don’t need to bother with, because the Interwebs are full of crazy mathematicians who love baseball and have nothing better to do. After searching for a few articles that evaluate projection systems, like this one and this meta-one, I decided that the forecasts I trusted most (and were easiest to obtain) were Steamer for batters and FanGraphs fans for pitchers. (The high accuracy of the latter shocked me at first, but then I realized that fans assimilate the results of all the projection systems into their own player projections, departing from them only as dictated by common sense, inside scoop, and hope.)

Operationalizing the Solution

Here’s where it gets tricky. What advanced data manipulation packages and techniques are best for downloading reams of data from the FanGraphs site into your spreadsheet? Certainly there was no need for me to copy and paste the data 50 players at a time like someone living the dark ages, was there? No, of course not. And I probably never really did that.

Instead – bear with me if you’re not technically inclined – I hit the gray “Export Data” button to the upper right of my chosen projection page. This involved a lot of loading the correct page, hovering my mouse over the text, and clicking, but in the end it was worth all the work, because 5 minutes of sweat, plus a beer, had finally paid off in spreadsheets full of data.

*If you’re not interested in these details, the fun stuff is posted in a couple of tables towards the end. (I like writing, so this is likely to go on for a while.)

Z-scoring your data points

Z-scoring batter projections is easy. The problem lies in determining what set of players to use in order to calculate means and standard deviations.

This is an important question, at least to the extent that any question in fantasy baseball is important. For example, if you must use every hitter in the league, including the guys projected for 8 at-bats, you create the illusion that lots of players bat .220 or score only 4 runs, as opposed to your league’s reality in which .270 with 70 runs is pretty ordinary. For a little math fun, I compared the results generated using means and deviations 500 players deep (the equivalent of a 25-team league that rosters 20 position players) versus one with more reasonable assumptions. It caused huge increases in variance in runs and rbi’s, so a guy who drove in and scored 100 compared no better to the mean either way (~2+ standard deviations), but smaller increases in the variance in SB’s, HR’s, and OPS, which, together with the lower means, meanings this system overvalues guys who produce in these categories. Martin Prado and Torii Hunter were made sad, whereas Billy Hamilton was elevated to a demigod (or at least a top-40 hitter).

So how do you generate values that represent your player pool?

One method – and a very reasonable one – is to use the final statistics compiled by your league the previous year. With this data, it’s easy to generate per-slot averages based on last year’s performance, and to compare projected performance against it. But I did not choose this method. A more savvy number-cruncher might say that projection systems, while designed to be as accurate as possible for each player, may be systematically biased on the whole, and therefore determining the value of this year’s projections based on last year’s actual statistics is tantamount to comparing apples and oranges.

I was more worried about lazy owners. Any league can have a couple of careless owners who are in it just for fun (the gall!), or who keep BJ Upton when he can’t even see the Mendoza line, because of that one time his cousin shook BJ’s hand at a Jay-Z concert. I know of what I speak. If your goal is to win your league, you want to base your evaluation on the best players available, rather than the happenstance of which Atlanta outfielders spent the whole year on someone’s roster.

I generated means using very precise data, plus a random stab in the dark. First, I looked up the exact number of players at each position in my league from the previous year. Then I mostly ignored this data. Although it’s true that player values vary greatly between leagues depending on how many players start, and how many are rostered, this is the sort of thing you can keep track of during the draft. Don’t draft another first baseman if you already have three of them and no shortstop, and don’t draft a first baseman just because he’s ranked ahead of a shortstop if there are another seven first basemen ranked close behind.

My league rostered only 123 regulars last year. Not a deep league. I used a lot more than 123 in my calculations in an effort to lower the means a bit, to account for the existence of catchers and second basemen. I then haphazardly created sort variables so I could bring the best 150 to 180 players to the fore, with the goal of getting a fair representation of the quality of players in my league. I tried various formulas like [(HR+1) * R * RBI * (SB +1) * AVG * OPS] (adding 1’s so as not to exclude players projected for 0 HR’s or SB’s ) and PA * wOBA. Virtually every one of them produced a good representation of the best hitters projected for regular playing time. In the end, the best way to evaluate the sort is to look at the list and see if the guys near the cutoff are fringe players who are familiar from last year’s waiver wire.

Calculating projected player values

Once you determine which players you want to include, Excel is happy to instantaneously calculate averages and standard deviations for each stat. Once you have these values, you can re-include the entire player pool, or as much of it as you wish, and the formula for each player in each category is simply (his projected value – the average projected value)/standard deviation.

The next challenge is to generate ranks from the Z-scores. The simplest way is simply to add them together (being sure to subtract ones where lower scores are better, such as pitcher walks or batter strikeouts). But here, I discovered another issue. A potential superstar who might not have a full-time job could end up ranked about the same or below a mediocre player who was guaranteed to start. If I wanted my draft rankings to make sense at a glance when I have just 90 seconds to pick a player while eating a sandwich, I needed to distinguish accumulators from guys with potential.

Ranking performance and potential

It matters whether a player is an okay guaranteed performer or a unpredictable potential star. If I find myself with no second basemen in the 22nd round, I might want to take the best guy who’s pretty much guaranteed 140 days in the starting lineup, like an Anthony Rendon or a Howie Kendrick. If my roster’s pretty much set, I might prefer a hitter who has a better chance to bust out and hit 45 home runs, like Chris Carter (unless I’m in my league, in which his 80% strikeout rate falls 37 standard deviations below the mean).

What I decided to do was generate two rankings for each batter, one based on projected totals, and one based on projections per plate appearance. Luckily, Steamer has already done the work for us by projecting everyone in both ways. For instance, Everth Cabrera is projected as the 479th-best player by wOBA, with 74 runs and 45 stolen bases. At the other extreme, Colorado’s Kris Parker is projected to be the 50th-best hitter in the league, just ahead of Dustin Pedroia, with a .279 batting average and .465 slugging percentage, despite getting only one plate appearance, and not getting a hit.

At this point, there are 2 sets of columns for each batter: 1 set of columns for his Steamer projections for each relevant stat, and 1 for the associated Z-scores. To this, I added 2 more sets of columns: 1 for per plate-appearance projections for each stat, and 1 for those associated Z-scores. (Dividing hits into plate appearances rather than at-bats feels unnatural, but that’s what you need to do if your league counts total hits.) Calculating per-PA quality is then easy, as you can just add the Z-scores (or subtract for negative statistics). But once you have projected rate statistics in your per-PA rankings, it becomes apparent that it doesn’t make sense to include the exact same values in your projected accumulated totals.

To handle this, I weighted the Z-scores for the rate stats. I multiplied the Z-score for AVG by projected AB’s/average projected AB’s, and you can do the same for OBP, using PA’s. My league uses OPS, a value generated by adding two fractions with different denominators (aka OBP & SLG), so to weight those Z-scores I multiplied them by projected (AB’s + PA’s)/average projected (AB’s + PA’s). I then added these weighted Z-scores to the other Z-scores for projected totals. The result of adding these weights is that a player who is one standard deviation above average in both AVG and OPS, and who has an average number of AB’s and PA’s, would get +2 from these categories in the variable used to rank projected totals. By the same lights, the aforementioned Kyle Parker’s AVG and OPS would essentially get no weighting at all, and have no effect at all on his projected totals, just as in real life his performance is not expected to have any effect at all on the rate stats of your team.

The Fun Stuff

And that’s about it. Once you have Z-scores, it’s very easy to rank players, to change the formulas to rank them by different systems, or to sort players by certain categories to see who stands out the most.

Two common variations on the traditional 5 stats are to include OBP instead of AVG, or to play in a points league. (For a points league, just change the Z-score weighting to reflect the point system). Here are the top players in these alternate systems using this evaluation method (I threw my own league in too, just for kicks):

(Note: I evaluated points leagues the same way as the other leagues, generating both a points total and a points/PA score for each player. I scaled the two values to give them approximately equal weight, and ranked players by the mean of the two.)

I expected Joey Votto to be a stud in OBP leagues, but in reality Joey Bats benefits more. Jason Heyward too. Meanwhile, CarGo is top 3 in every other system, but falls to the bottom half of the first round in a points league. In my own crazy league, Norichika Aoki projects as a contact-hitting top-40 stud, while Mark Trumbo’s contact deficiencies show up in strikeouts and hits, as well as AVG, and he drops to 82nd.

I also thought it would be cool to see which players project to be affected most under different scoring systems. Here are the players with the largest variation in ranks between systems (weighted to prefer higher-ranked and therefore more interesting players):

Billy Hamilton projects to be a one-category stud in any system that ranks stolen bases, but many people doubt whether he’ll be an especially good ballplayer in 2014, and the points system shares their skepticism. Carlos Santana will benefit enormously from any league using deeper measures than AVG, while Adam Dunn jumps from irrelevance to potential rosterability in OBP leagues only. A couple more notable players: Alex Rios is vastly more valuable in leagues with the standard five categories, and least valuable in points league, and Adam Jones follows a very similar, if somewhat less drastic, pattern.

And there you have it – the results of one approach to generating player values for leagues with alternative categories.

We know, in broad strokes, what seemingly happens when a pitcher moves to the bullpen. His velocity tends to improve, his “stuff” tends to look better, and his run prevention receives a boost. Can we quantify that effect? What about the reverse effect, moving from the bullpen to the rotation?

The Process

In order to attempt to quantify this effect, I looked at the 115 pitchers since 2002 who have started for at least 100 innings and relieved for at least 100 innings. There were actually 118 pitchers who fit the criteria, but the knuckleballers Dickey, Wakefield, and Sparks skewed the sample rather greatly, and were thus thrown out. It could be said that knuckleballers play a different game, with different constants (lower BABIP), and different expectations, so it is sometimes best to neglect them in a model, but that is a discussion for a different day.

Besides somewhat arbitrarily throwing three data sets to the curb, this methodology necessarily creates a sample bias, that only those pitchers who were deemed worthy of the switch for an extended period of time will show up in the results, but there is simply no way to simulate how players might have done in such a situation if teams will not actually do it. As such, the data ignores those players who were too good (or too bad) in their current roles to ever merit a switch to the other.

A secondary bias is that this sort of analysis will not specifically show what happens in a switch from the bullpen to the rotation, or vice versa, but rather what people who pitched in both roles did. In other words, we’re not really quantifying what happens during the switch, but just the split itself. It is possible that switching from the rotation to the bullpen is easier than the converse, but the data would not reveal that.

For those pitchers who satisfied the prerequisites, I aggregated their performance as relievers and as starters in order to gauge the difference, and looked at the individual data to find the summary statistics.

The Data

Peripherals

“s-r” refers to starting minus relieving, so negative values correspond to situations in which the pitchers in the sample had a higher value of that statistic while relieving, while positive values correspond to the opposite. I chose FB% to serve as a proxy for modeling the tendency of relievers to sacrifice secondary, tertiary, and quaternary pitches coming out of the bullpen. Z-contact% is meant to be a measure of “stuff” by virtue of measuring the ability to induce swings and misses on pitches in the zone.

Based on this table, we can get a rough idea of the difference between starting and relieving. It appears the group had a much higher K% and a higher BB%, along with a higher velocity and Z-contact%, supporting the assertion that, all else equal, a pitcher will be able to display better stuff while relieving, likely due to the fact that a reliever does not need to conserve energy to pitch deeper into the game. GB% and HR/FB% also improve, implying weaker contact against relievers, likely due to, again, the improved “stuff”.

Run Prevention

Run prevention is, unsurprisingly, also seemingly improved by being in the bullpen, although FIP and xFIP seem slower to “pick up on it”. That is also not surprising; both statistics would need to assume average performance in the other excluded peripherals to model ERA extremely accurately, but the “Peripherals” chart showed that such a base assumption would be untrue in this case.

Conclusions

It is tough to make conclusions from relatively small sample sizes and somewhat flawed studies like these, but there are a few rather obvious pointers. It seems rather clear that the common perception that “stuff” improves while in relief rings true. This may not be definitive evidence that moving to the bullpen would explicitly improve a player’s performance by N% in different categories, but this analysis does firmly point in the direction that there is some theoretical manner by which that effect could be ascertained.

Author’s note: This is the first article I’ve submitted to FanGraphs, so constructive criticism is welcomed. Ask in the comments below if you’d like me to run another stat and see if it meshes with the results I’ve posted here.

As I usually do, I was checking through the headlines on mlb.com and I happened to notice that Kirk Gibson has not made a decision for who will be closing for his team. This should be one of the bigger questions leading up to the regular season as the Diamondbacks have several options when it comes to closers.

Honorable Mention: Josh Collmenter
He is a pitcher who has quietly been one of the best relief pitchers for the Arizona Diamondbacks of late. He is a three pitch pitcher with an 88 mph fastball, a 70 mph curveball, and a 78 mph changeup. With that slow speed, one would expect him to be a more pitch to contact kind of pitcher and let the defense take care of him. But he posted a career low 32.7% groundball rate which is low for many pitchers. However, he also does not give up that many homers, giving up an average of .78 HR/9 last season. He struck out 8.32 batters per nine innings last season while walking 3.23 batters per nine last year.

Where Collmenter’s value is on the Diamondbacks is as a long relief, spot starter pitcher for them. He pitched in 49 games last season and threw a total of 92 innings meaning that he threw nearly 2 innings per appearance. In his career in the minors, he pitched all of his outings as a starter with the exception of 2 games in his first year in low A ball in 2007. Closer could be a good spot for him with the strikeout rate but I would like to keep him in the bullpen for if the starter can only throw 2 innings or less.

3. Brad Ziegler
It is no secret that Brad Ziegler is very good at getting groundball outs, that is what makes him successful. He doesn’t really throw an actual sinker per se, but his fastball essentially plays the role as sinker. The submarine arm action that Ziegler throws with has the pitch rising up briefly before dipping down just before it gets to the plate (as shown in the gif below).

By using this heavy sinking action on the fastball, he has produced a career 66.1% ground ball rate (which has been raised to a 72.9% rate since the start of the 2012 season) and in front of a great fielding team like the Diamondbacks (team UZR/150 of 8.1, good for second highest in the Majors), that leads to success. But this is why he should be used more of as a relief ace as opposed to closer. If the starter leaves the game in the seventh inning with people on base, I want a pitcher to come in who can get the ground ball double play. Neither Putz nor Reed are as good at getting groundball outs and only Putz has a higher LOB% (90.9% for Putz as opposed to Ziegler’s 80.7). If Ziegler is put into the role of closer, then he would be less likely to be put into a situation where a groundball is needed as the manager would want to hold on to him until the ninth inning.

2. J.J. Putz
J.J. Putz has a very realistic chance of claiming the role of closer at the start of the season. If not for injuries, Putz would have maintained the role of closer last year but an elbow and finger injury during the season limited his playing time to only 34.1 innings and when he returned from them he was more of a situational right handed pitcher. But since the start of the 2012 season, no pitcher on the Diamondbacks has more saves than Putz’s 38 saves leading many to believe that he could be a front runner for the closer spot based on experience alone. He’s been solid for them in the past, but a steady decrease in pitch velocity and an increase in home run rate over the past 3 years should be somewhat concerning for the Diamondbacks. His fastball velocity is still above 90 mph (91.7 mph in 2013 and 92.8 mph in 2012) and the home run to fly ball rate is still not too high (having been only about 14.8% in 2013 and 8.7% in 2012 but that is a concerning increase from the 6.0% HR/FB rate in 2011).

One thing interesting to think about with regards to J.J. Putz is what effect his injuries had on his performance last year. In most areas, Putz experienced a dramatic increase in essentially all statistics but one of the more significant increases occurring in SIERA where he went from 2.29 in 2012 to 3.24 in 2013 and his walk rate increased from 1.82 BB/9 to 4.46 BB/9. It is tough to tell whether or not these inflated statistics are just as a result of injuries or if they are as a result of just wearing down from age. After all, we can’t forget that Putz is now 37 so he does not have age on his side any more. I don’t see him being as bad as his stats from 2013 indicate but it is certainly something to think about.

1. Addison Reed
One pitcher who definitely has age on his side is Addison Reed; the pitcher who I believe should be given the role of closer without question. He proved that he is one of the best young pitchers in the game and he showed this while playing for a terrible defensive team like the White Sox. I believe that his ERA is definitely misleading as a 3.79 ERA makes him seem worse than he is. Reed strikes out 9.08 batters per nine innings, limits the walks with only a 2.90 BB/9, and a HR/9 of .76 which is comfortable in the closer’s role. Those are the kind of numbers that someone in the position of closer should have and with his young age of 25, there is definitely room for improvement. His other numbers like his xFIP of 3.77 in 2013 and his SIERA of 3.19 in 2013 would indicate that he is definitely going to get better.

There are other things to like about Reed aside from his statistics and potential. Last year, he threw the four seam fastball for 92.7 mph, the two seam fastball 93.5 mph, the slider at 83.8 mph, and the changeup at 83.7 mph. The 8.9 mph difference between his fastball and slider are very deceiving to a right handed batter because of the movement away from the batter and the 8.8 mph difference between his fastball and changeup creates a devastating effect on left handed batters as is evidenced by the .266 wOBA vs. L last season with the 37 strikeouts.

The Diamondbacks are in an enviable position with having multiple options that they could plug into closer. With the young and fragile rotation (Corbin has already shown that young starters are good but not invincible) that the Diamondbacks have, I think that Collmenter will have to avoid getting locked into the closer spot as he may be needed to make a few starts. Ziegler was good for the Diamondbacks last season but don’t expect to see him in the closer’s role as a pitcher of his caliber needs to be free to pitch at any time during the course of a game. But honestly when it comes down to the choice, the gap between Reed and the other options is substantial enough that there really should not be much debate.

Who can the Angels rely on in the back of the rotation?

The strength of the 2014 Angels will be their offense, but the team does have a lot of money and development invested in their rotation and they need to get good outings out of that rotation to support the offense and win games. Jered Weaver has been injured throughout the past few years, but it usually solid when he is in the rotation and is a quality start machine. CJ Wilson may not be perceived as an elite pitcher but since moving into the rotation for the Rangers in 2010, he averages 15 wins a season with a 3.37 ERA and 210 innings pitched. Both Weaver and Wilson could be major factors in a playoff run and would be relatively comparable to the top two pitchers for most AL playoff competitors. Behind Wilson and Weaver in the rotation, though, are young unproven pitchers that really need to grow up very quickly if the team wants to make noise in 2014.

Garrett Richards already has 230 innings of big league experience coming into 2014 and the 26 year old former top 100 prospect has shown some progress in his major league tenure. He has seen his ERA, WHIP, and walk rate lower since 2011 as his strikeout rate rose. That being said, Richards did have low expectations set in 2011 and 2012 where he had a 1.57 WHIP and a 1.37 K: BB rate; Richards needs to harness his fastball and play off of his three off-speed pitches. He has a lot of good tools, with a fastball in the mid-90s and a very solid slider and curveball. His changeup is not advanced, but it is a work in progress and Richards uses it very sparingly for good reason.

Richards must also work ahead in the count more; his first pitch strike percentage was only 53.6% in 2013 and if that rises, Richards will continue to clean up his control issues. His walk percentage returned to the 7.1% that was only matched when he was in the lower levels of the minor leagues and the same goes for his 16.3% strikeout percentage. Richards might be the wildcard of the Angels rotation; he could be the third strong pitcher in the rotation and could be struggling to maintain a spot in the rotation. He needs to continue to develop his curveball and let his 94 mph fastball play off of those two solid breaking balls and, if he does, it would not be crazy to see Richards get 150-175 strikeouts in a full season.

Hector Santiago was acquired with Tyler Skaggs by the Angels in the three team trade that sent Mark Trumbo to Arizona. This was after two solid seasons with the White Sox that gave the Angels a good view into how the 26 year old could contribute. A crafty lefty with a bit of an unorthodox delivery, Santiago is a true throwback pitcher in that he will beat you with variety rather than one or two strong pitches. According to pitch data accumulated by Pitch FX, Santiago threw five pitches at least 5% of the time (four seam fastball, cutter, sinker, changeup, curveball) and also worked in a screwball and slider. Although he still threw mostly fastballs and changeups, he threw three different types of fastballs and his varying arm angles tended to confuse batters.

These different offerings do have a bit of a drawback; the fact that Santiago rarely dominates with one pitch leads to a walk rate of 11.5% for his career; he does strikeout 22.2% of batters with a 1.93 K:BB ratio for his career, but the Angels have to hope that can be a bit better as he progresses. Since the variety of offerings has led to success in the big leagues, he has a 3.41 ERA in 222 2/3 innings split between the bullpen and the rotation, Santiago needs to find a way to keep his pitches strong. When looking at the pitch trends, Santiago has varied what pitches he throws quite frequently, as there is not really a good method of predicting his trends for the future. This creates a tough situation for batters, but sometimes it could create an even tougher situation for Santiago; if his pitches are not sharp over a long stretch, he may really struggle since he never specifically works on a solitary pitch in an outing.

Tyler Skaggs may even be more volatile than Richards in regards to his position with the 2014 Angels; his spot is the least stable in the rotation and he only has 68 very shaky innings pitched in his young MLB career. That being said, Skaggs is the top prospect for the Angels and will be a big part of the future of the Angels. A former first round pick by the Angels, Skaggs was traded to Arizona for Dan Haren and then traded back to Los Angeles in the aforementioned Mark Trumbo trade. While in Arizona, Skaggs developed a reputation as an elite minor league pitcher with bad major league results; a lot of those bad results derive from the fact that Skaggs is a soft throwing pitcher that has yet to really master what will be an incredible curveball.

Between the latter part of 2010 and the end of the 2012 season, Skaggs posted a 2.85 ERA with a 1.15 WHIP and a 3.7 K: BB ratio between low-A and Triple-A. He did have a rough patch in Triple-A this year, but maintained a similar K: BB ratio from Triple-A in 2012; he allowed more hits in 2013 but also struck out more batters. Essentially, the Diamondbacks look at Skaggs as someone that could develop into Cole Hamels, just with the curveball being the dominant pitch for Skaggs. As seen with Hamels, having velocity in the high-80s or low-90s can work if you have great off-speed pitches and Skaggs needs to develop his changeup along with making his curveball take that next level to being one of the premier pitches in baseball. He has the potential to be a top of the rotation pitcher and the Angels were wise to re-acquire him from Arizona.

A team like the Angels that is trying to compete for the playoffs would be fine if one of these pitchers were trying to get their footing in the majors, but the fact that all three are trying to get acclimated to a playoff competitor may be what does the Angels in during the 2014 season.  There is a lot of upside with Richards and Skaggs, though, so if they turn into the middle to top rotation pitchers that scouts see them as, the Angels may indeed be a 90 win team on the way to the playoffs.

When will the Angels try to rebuild their farm system?

A tough thing to do is to rebuild a farm system when the top prospect in baseball was once a part of that farm system. Mike Trout is arguably the best player in baseball but the Angels could have never expected him to be this good this quickly; for this reason, the rest of the Angels minor league talent looks underwhelming compared to the 22 year old superstar. There is a chance, and this is pure conjecture, that Randall Grichuk may have been a part of the trade that brought David Freese to Los Angeles so that he did not have to be known as the “other” Angels first round pick from 2009. As with anything, the Angels need to rebuild this system so that the team continues to be strong into the future.

Kaleb Cowart was the top prospect in the Angels organization after Trout graduated but a weak 2013 season in Double-A Arkansas gives people reason to worry about the future of the third baseman; in fact, the Angels were so cautious about Cowart’s future that they acquired David Freese this offseason. A tall and lanky first round pick out of high school in Georgia, Cowart had a very strong 2012 between Low-A Cedar Rapids and High-A Inland Empire, even going over 100 RBI (103) for the season. His defense was outstanding between the two leagues and his plate discipline improved with the jump to High-A. The move to Double-A was rough for Cowart; his fielding took a step back, his power disappeared, and his OPS was .580. As with any prospect, the Angels will continue to give him opportunity, but the 22 year old Cowart is not in a position considering that he has only mustered one single in seven spring training at bats. Cowart needs to show that he can hit or he will be a career minor leaguer and a first round pick bust.

CJ Cron is the opposite of Cowart; he is big and bulky and hits like he is big and bulky. The first baseman is basically a clone of Mark Trumbo; they both are 6’4, 235 pounds and hit a ton of home runs with very little plate discipline. Considering that the Angels traded Trumbo this offseason and have spent years waiting on him to develop, the Angels may not be too excited for the prospect of a Trumbo clone. The main difference between the two is that Cron is a bit better of an athlete and fielder; this may not be a factor with the team considering him as a designated hitter option, but he has worked on his fielding to become a serviceable first baseman if the team sees him as a fit at first. Cron also struggled at Double-A Arkansas this year, with his OPS dropping nearly 100 points to .743 and going from 27 home runs in Inland Empire to only 14 in Arkansas. Cron maintained his doubles power with 36 and there is every reason to believe that he becomes a 25 home run hitter in the majors. Cron is very durable and finds ways to get on base even with a low walk rate, two traits that should never be ignored in evaluating the viability of a prospect. There is a very good chance that Cron gets a spell in the majors by 2015 or, if his spring training success continues, even 2014 if he continues to develop.

Taylor Lindsay was the lone prospect of the three examined that did not seen his success considerably regress in Arkansas. In fact, Lindsay saw his walk rate rise and posted 17 home runs which is quite impressive from a 6 foot, 195 lb second baseman. A near sure thing to begin the season in Salt Lake, Lindsay is an injury or Howie Kendrick trade away from being the starting second baseman for the Angels. That being said, he is not a finished product. Many pundits like the 45 extra base hits and continued progress in his approach at the plate, but Lindsay still made a few too many errors for a second baseman, does not have great range, and is a non-factor on the bases. Those are things that must be worked on in Triple-A before he makes the leap to the majors. His offensive output from 2013 should not be seen as a fluke and Lindsay can hit enough to be a decent major leaguer. There is a lot to like from Lindsay and the Angels may even give him an opportunity to play a bit in the majors if he makes strides in Triple-A.

Los Angeles has done a very good job of developing big league talent and these three players may very soon be a part of this development. Fortunately the Angels have enough talent on the major league roster for these players to be given enough time to properly develop, but, especially in Lindsay’s case, these players could be a productive part of the Angels roster in 2014.

How will the change of scenery affect David Freese?

David Freese was a product of the St. Louis Cardinals fantastic development but a rough 2013 season made him expendable; the Angels had a very weak situation at third base and an extra outfielder, so Freese was traded to Los Angeles for Peter Bourjos. Freese is seen by some as a product of his environment in St. Louis and that his bad 2013 and move to Los Angeles will depress his talent. The Angels hope that these people are wrong and a new team is a new opportunity for Freese.

Freese was an early round pick by the Padres out of community college and Freese produced right away with the Padres’ minor league affiliates and was a major part of the 2007 offseason trade that sent Jim Edmonds to San Diego from the Cardinals. After solid seasons in 2008 and the beginning of 2009, Freese was up in St. Louis with the major league team. After he broke his ankle in both 2009 and 2010, Freese broke out with the 2011 Cardinals and was the MVP of the 2011 World Series. In 2012, Freese again was solid as he had an OPS of .839, turned had a career high in HR/FB percentage, and played a very solid defensive third base. Defense and inconsistency led to a poor 2013 for Freese, the worst of his entire professional career, and the Cardinals decided that prospect Kolten Wong at second base and Matt Carpenter at third was a better direction for the team. The Angels are relying on Freese returning to his past offensive output to strengthen their team.

Before we look forward to 2014, a deconstruction of Freese’s worst season must be done to see how he can fix the issues that arose. He did post a solid strikeout and walk percentage in 2013, in fact striking out at the lowest rate of his MLB career. His BABIP was 30 points lower than it had been in any other season, a huge indicator that 2013 may be an outlier. Although the BABIP may be attributed to luck, the 55 point drop in isolated power shows that Freese did not hit the ball with the authority of 2012. The contention that Freese was not as potent is only further supported by the fact that his line drive rate was down and his ground ball percentage was up. A lot of Freese’s other advanced statistics show that he was swinging at good pitches and actually made more contact in 2013 than 2012.

The fact that Freese had weak contact is what hurt him; this could have been because of injury and the Angels have to hope that his Isolated Power returns back to the mid-.100s rather than the low-.100s of 2013. Freese was also a strong fielder prior to 2013 and injuries may he also been the reason that he fell off a bit last year; his range was limited and was a negative factor for the Cardinals at third. A healthy Freese in a strong offensive lineup should be close to 15-20 home runs and 80-85 RBI, as well as returning to being a solid defensive player.

What do the Angels need to do for Josh Hamilton and Albert Pujols to get on the right track?

Albert Pujols and Josh Hamilton are both former MVPs and, in Pujols’ case, legends of the game. The 2013 season was a lost one for both players and the Angels could have never expected that these two great players would be such liabilities for the team. There are big issues for each player and their careers are really at a crossroads; both may need to change their approach at the plate to achieve their past successes.

Josh Hamilton was a safe bet for nearly 30 home runs and 100 RBI while in Texas; albeit with injury issues, Hamilton was one of the better sluggers in baseball. The issue with Hamilton was that he got hurt too much and tailed off a bit at the end of the season; there were very few issues about Hamilton’s production over a full season and coming to Los Angeles where there were established superstars in Mike Trout and Albert Pujols should have created a situation where Hamilton could be a 125 RBI producer. In 2013, Hamilton stayed healthy but was one of the biggest disappointments of the season. The former MVP only posted a .307 OBP and had 21 home runs and 79 RBI in the 151 games he played; his 151 game averages for his career are a .363 OBP with 33 home runs and 113 RBI.

There have been peaks and valleys in Hamilton’s career, but the valleys have not been this low statistically in a full season. This is a bit surprising for Hamilton because 2012 was the best year of his career and, had Oakland not caught Texas to win the division, Hamilton would have been just as good of an MVP candidate as Miguel Cabrera or Mike Trout. He may have struck out at a career high percentage in 2012, but he also had the highest walk rate, isolated power, and hit a ton of fly balls (41.1%) that lead to home runs (25.6 % HR/FB). Further analysis paints an odd picture for Hamilton and might be the reason that he rebounds in 2014. Hamilton was unsuccessful on balls outside of the zone during 2012 and in 2013, Hamilton swung at less pitches outside of the zone and was more successful on those swings.

As a hitter with a swing that lends to contact on pitches outside of the zone, it would be good for Hamilton to continue to be more selective and work on regaining good contact on bad pitches. Although he was successful with poor contact rates in 2012, Hamilton needs to get back to mid-70% contact rates that he had in the 2007-2011 seasons; he was at a 70.3% in 2013, a jump from 64.7% in 2012. Hamilton should be able to regain 30 home run production by working more on the above mentioned issues and the Angels will be glad to have a strong force in the middle of their lineup.

Albert Pujols might have had the best 11 season start to a career in St. Louis; he averaged 40 home runs per season with 121 RBI and a ridiculous 1.037 OPS. The Angels jumped at Pujols when he was a free agent in the 2011 offseason and gave him $250 million to bring that kind of production to Los Angeles: this has not been the case and Pujols looked very weak in 2013. The writing has been on the wall a bit for Pujols to regress, even if it is rough to think that such a talented player would become only a role player. Pujols has seen a decrease in OPS in every season since 2008 and has not hit .300 since 2010. It is a bit unfair to criticize a .331 hitter for lowering his career average to .321 as he has gotten older, but the fact remains that Pujols will never be the player he once was.

What made Pujols so great was that he was able to combine a high lofty swing that led to home runs with fantastic plate disciple and pitch selection. Pujols’ bat has slowed down rapidly and pitchers have not only made Pujols swing more, but make sure that that these swings were on pitches outside of the strike zone that he misses; Pujols has seen his swinging strike rate double from 3.8% in 2008 to 7.6% in 2013. Pitchers still cannot beat Pujols on pitches that are in the strike zone (91.1% Z-Contact) but his overall contact rate has slipped from 90.1% in 2008 to 82.9% in 2013. Pujols is an all-time great and frequently greats are able to reinvent themselves so there is still a chance for a solid season out of Pujols. Even in a relatively weak 2012 season, Pujols had 105 RBI and 50 doubles. Pujols needs to be more patient and not chase the poor pitches like he did in 2013. If Pujols is able to raise his BABIP with better swings and pitch selection, an average in the .280-.290 range with 55 2B+HR and nearly 100 RBI is quite attainable.

There is a better chance that Hamilton regains his 2008-2012 form than that of Pujols’ prime, but his strikeout and free swinging problems will continue to linger unless he changes his approach. The bar was set so high for Pujols and he will never get back to that level, but he could still be a productive player for the Angels and an example for the younger players.

Why are the Angels going to win 85 games?

The Angels are in a spot very similar to the Rangers, hence the prediction that leads to them being equal in win total. There is a lot of offensive talent on this team but the pitching is just not strong enough to weather the storm in a loaded American League. CJ Wilson and Jered Weaver should each be solid at the top of the rotation and Tyler Skaggs will be solid someday, but unless the Angels make a move to improve on the 2014 staff, the team is not playoff bound. Albert Pujols and Josh Hamilton may never regain their MVP pasts, but each should rebound from the rough 2013 seasons. Mike Trout will continue his MVP pace and the team will stay in the wild card race most of the season.

5 You Know:

1. Mike Trout

2. Albert Pujols

3. Jered Weaver

4. CJ Wilson

5. Josh Hamilton

5 You Will Know:

1. CJ Cron

2. Cam Bedrosian

3. Kaleb Cowart

4. RJ Alvarez

5. Taylor Lindsay

5 You Should Remember:

1. Hunter Green

2. Ricardo Sanchez

3. Mark Sappington

4. Jose Rondon

5. Alex Yarborough

One of the offseason’s most talked-about moves was the trade that sent Prince Fielder to the Texas Rangers in exchange for Ian Kinsler and gobs of cash. While universally (and rightfully so) viewed as primarily a salary dump for GM Dave Dombrowski and the Tigers camp, the Rangers have gained a strong bat to place in the middle of their batting order alongside Adrian Beltre and Alex Rios.

Yet unlike the much-theorized David Price trade, the Fielder deal was not a pure salary dump. Fielder stumbled mightily in his production in 2013. In 2012, he posted a robust .313/.412/.528 traditional slash line, with an impressive .940 OPS and 153 wRC+. According to Baseball-Reference’s oWAR calculations, 2012 was Fielder’s third-most valuable year at the plate with a 5.4 mark. All of this stands in stark contrast to Fielder’s 2013.

Last year Fielder posted a much more pedestrian .279/.362/.457, .819 OPS, 125 wRC+ and 2.9 oWAR. While of course those are still above-average numbers, when attached to the name Prince Fielder and his ubercontract, Dave Dombrowski clearly had reason for concern. However, off-the-field issues are widely believed to have contributed to the dip in Fielder’s production, and natural regression may have also contributed to the fall from Fielder’s career-high traditional slash line. Fielder also enjoyed a career-high .321 BABIP in 2012, with his 2013 mark of .307 more in line with his normal marks.

So, the question presents itself; what exactly does Texas GM Jon Daniels have on his hands in the 2014 model year Fielder? There are a number of factors contributing to this answer. Firstly, while the batters ahead of him do not contribute to his slash line, they certainly do help counting stats such as RBIs. While RBIs are naturally an utterly useless stat when evaluating individual performance, men getting on base allow a hitter to create runs, and as runs are ultimately what win games, putting men on ahead of big bats such as Fielder is part of what goes into good team creation. Therefore, I will examine the clip at which we can expect there to be runners on base when Fielder bats for Texas as opposed to his stint in Detroit.

Secondly, I will also examine the impact Arlington itself will have on Fielder’s bat. Arlington has traditionally been a much more hitter-friendly location than Detroit. But how much exactly will Texas raise Fielder’s numbers?

The top of the 2013 Tigers lineup consisted of Austin Jackson, Torii Hunter, Miguel Cabrera in front of Fielder. Those first three hitters posted OBP’s of .337, .334, and .442, respectively. That averages out to a .371 mark, albeit an imperfect one due to Cabrera’s significantly higher individual mark (also, Cabrera hit a lot of home runs last year, and while that counts towards his OBP, that means the bases were empty when Fielder came to bat). We’ll refer to this average of the top of the order as tOBP, or “Top OBP” for the rest of the article for the sake of saving space.

The top of the 2014 Rangers lineup will be made up of Shin-Soo Choo, and either Elvis Andrus or Jurickson Profar before Fielder, who will bat third. There are a number of different projection systems we can use to forecast the upcoming season, for this article we’ll be using Steamer. Choo is given a .391 OBP, Andrus a .340, and Profar a .321. With Andrus in the lineup the projected tOBP is .365, with Profar it’s .356. So despite throwing his wallet at Choo and his obscene .423 2013 OBP, Jon Daniels in fact is giving Fielder less to work with in front of him.

Or is he? Part of the smaller (projected) tOBP in Texas is that Fielder simply won’t have the best hitter in the game hitting in front of him anymore. Also, one has to expect Fielder to be better at the plate this year. Steamer awards Fielder a substantial .290/.390/.516 line with a 142 wRC+ and 3.4 WAR, a major uptick over last year’s production. If we factor him into the projected Texas tOBP, with Andrus it’s a .374, and with Profar it’s .367. That’s something you like to see if you’re Adrian Beltre, who lead the league in hits last year and launched 30 homers.

And speaking of homers, Fielder’s move to Arlington will help him in that department. The newly named Globe Life Park ranked seventh last year in home runs with a total of 107 being hit there. Comerica Park, where the Tigers play, ranked fourteenth with 99. This helps Steamer award Fielder 29 home runs, up from 25 last year.

However, can we possibly expect Fielder to exceed these projections? As mentioned earlier, Fielder’s down year was contributed to by a number of off-the-field issues according to Hunter. A change of scenery will definitely do Fielder well, and he also seems to have lost some weight if the pictures and video coming out of Spring Training are to be believed. For that reason I’m willing to bump up Fielder’s numbers by a few slots, and I expect him to be even better than what Steamer predicts. Because baseball is a fickle mistress I could easily be wrong, but call it a gut feeling. All in all, Jon Daniels may have caught lightning in a bottle here with his rather expensive gamble, and if Texas manages to overcome their pitching woes they should be a very dangerous team with Fielder anchoring their lineup.

Whenever one makes any conclusion based off of anything, a bunch of underlying assumptions get shepherded in to the high-level conclusion that they output. Now that’s a didactic opening sentence, but it has a point–because statistics are full of underlying assumptions. Statistics are also, perhaps not coincidentally, full of high-level conclusions. These conclusions can be pretty wrong, though. By about five-hundred runs each and every season, in this case.

Relative player value is likely the most important area of sports analysis, but it’s not always easy. For example, it’s pretty easy to get a decent idea of value in baseball while it’s pretty hard to do the same for football. No one really knows the value of a pro-bowl linebacker compared to a pro-bowl left guard, for one. People have rough ideas, but these ideas are based more on tradition and ego than advanced analysis. Which is why football is still kind of in the dark ages, and baseball isn’t. But just because baseball is out of the dark ages, it doesn’t mean that it’s figured out. It doesn’t even mean that it’s even close to figured out.

Because this question right here still exists: What’s the value of a starting pitcher compared to a relief pitcher? At first glance this a question we have a pretty good grasp on. We have WAR, which isn’t perfect, yeah, but a lot of the imperfections get filtered out when talking about a position as whole. You can just compare your average WAR for starters with your average WAR for relievers and get a decent answer. If you want to compare the top guys then just take the top quartile and compare them, etc. Except, well, no, because underlying assumptions are nasty.

FanGraphs uses FIP-WAR as its primary value measure for pitchers, and it’s based on the basic theory that pitchers only really control walks, strikeouts, and home runs–and that everything else is largely randomness and isn’t easily measurable skill. RA9 WAR isn’t a good measure of individual player skill because a lot of it depends upon factors like defense and the randomness of where the ball ends up, etc. This is correct, of course. But when comparing the relative value of entire positions against each other, RA9 WAR is the way to go. Because when you add up all the players on all of the teams and average them, factors like defense and batted balls get averaged together too. We get inherently perfect league average defense and luck, and so RA9 WAR loses its bias. It becomes (almost) as exact as possible.

Is this really a big deal, though? If all of the confounding factors of RA9 WAR get factored together, wouldn’t the confounding factors of FIP-WAR get factored together too? What’s so bad about using FIP-WAR to judge value? Well there’s this: From 1995 onward, starting pitchers have never outperformed their peripherals. Relievers? They’ve outperformed each and every time. And it’s not like the opposite happened in 1994–I just had to pick some date to start my analysis. Here’s a table of FIP-WAR compared to RA9-WAR compared to starters for the last 18 years, followed by the same table for relievers.

Starter RA9-WAR/FIP-WAR Comparisons

Reliever RA9-WAR/FIP-WAR Comparisons

Ok, so that’s a lot of numbers. The basis, though, is that FIP thinks that starters are better than they actually are, while it thinks relievers are the converse. And this is true year after year, by margins that rise well above negligible. Starters allow roughly 250 more runs than they should according to FIP every season, while relievers allow about 250 less than they should by FIP’s methodologies–in much fewer innings. In more reduced terms this means that starters are over-valued by about 10% as whole, while relievers are consistently under-valued by about 25% according to FIP-WAR. Now, this isn’t a completely new idea. We’ve known that relievers tend to outperform peripherals for a while, but the truth is this: relievers really outperform peripherals, pretty much all the time always.

Relievers almost get to play a different game than starters. They don’t have to face lineups twice, they don’t have to throw their third or fourth-best pitches, they don’t have to conserve any energy, etc. There’s probably a lot more reasons that relievers are better than starters, too, and these reasons can’t be thrown out as randomness, because they pretty much always happen. Not necessarily on an individual-by-individual basis, but when trying to find the relative value between positions, the advantages of being a reliever are too big to be ignored.

How much better are relievers than starters at getting “lucky”? Well, a few stats that have been widely considered luck stats (especially for pitchers) for a while are BABIP and LOB. FIP assumes that starters and relievers are on even ground, as far as these two numbers are concerned. But are they? Here’s a few tables for comparison, using the same range of years as before.

BABIP Comparisons

LOB Comparisons

With the exception of BABIP in ’96, relievers always had better luck than starters. Batters simply don’t get on base as often–upon contacting the ball fairly between two white lines–when they’re facing guys that didn’t throw out the first pitch of the game. And when batters do get on, they don’t get home as often. Relievers mean bad news, if good news means scoring more runs.

Which is why we have to be careful when we issue exemptions to the assumptions of our favorite tools. There are a lot of solid methodologies that go into the formulation of FIP, but FIP is handicapped by the forced assumption that everyone is the same at the things that they supposedly can’t control. Value is the big idea–the biggest idea, probably–and it’s entirely influenced by how one chooses to look at something. In this case it’s pitching, and what it means to be a guy that only pitches roughly one inning at a time. Or perhaps it’s about this: What it means to be a guy who looks at a guy that pitches roughly one inning at a time, and then decides the worth of the guy who pitches said innings, assuming that one wishes to win baseball games.

The A’s and Rays just spent a bunch of money on relievers, after all. And we’re pretty sure they’re not dumb, probably.

5. Alex Gonzalez

Friday morning, as I began the tedious process of combining all MLB schedules in one spreadsheet, I noticed that FanGraphs’ resident volcano expert and prolific content generator Jeff Sullivan posted one very similar article, and then another shortly thereafter. He focused on projected WAR, while I planned to look specifically at projected average ERA and wOBA a team must contend with over the 2014 season. So at the risk of writing a similar post, one with drier writing and less cool graphics, I submit to you the following simple table and graphs.

We often look at the strength of a division and make generalizations about the hardest place to pitch (AL East) and hit (NL East). Like park effects, we sometimes jump to conclusions about the effects of dream lineups and weak interdivision rivals. Chad Young’s analysis of Prince Fielder’s move to Arlington is a perfect example of how enthusiasm can be misplaced when we forget that 90 of a club’s 162 games take place outside of their division, with 20 games occurring in a different league.  The table below shows projected mean wOBA and ERA by team, which are weighted by expected plate appearances and innings pitched, respectively. As expected, AL teams generally have a DH-fueled high wOBA and inflated ERA when compared to their NL counterparts. All projections are courtesy of Steamer’s 2014 pre-season projections. Keep in mind that Steamer regresses stats like wOBA and ERA, so there is not as huge a gap between the Red and White Sox (0.332 vs. 0.317) compared to what you might see during the season. However, Steamer has been shown to be one of the best projection systems available when it comes to capturing player-to-player variation in performance (i.e. ranking players by production), which is sufficient for looking at the differences between teams.

*adjusted for PA and IP

I was surprised by the high ERA attributed to the San Diego Padres, poor enough for 6^th worst in the NL. The Reds’ Choo-less offense is also, somewhat surprisingly, projected as the 7^th worst in the majors. Let’s take a moment to silently reflect that the Minnesota Twins, despite having a spacious ballpark and a non piss-poor payroll, are still projected to give up more earned runs than the Colorado Rockies.

While the table displays projected wOBA and ERA by team, the charts below illustrate the mean wOBA and ERA faced by each team over 162 games.

Last September Dave Cameron presented a convincing argument that Chris Sale’s 2013 season was as good if not better than Max Scherzer’s, but was obscured in part because Sale routinely pitched against the Tigers and Scherzer routinely pitched against the White Sox. These projections reinforce the argument in favor of opponent-adjusted measurements—Detroit pitchers are projected to face a wOBA of 0.321 while Chicago pitchers play against teams with a projected wOBA of 0.324.

San Diego and San Francisco are home to some of the most pitching-friendly stadiums in the country. However, in part because they play 28 away games against the Rockies, Diamondbacks, and Dodgers, their opponent’s wOBA is higher than people might expect. However great it is that a flyball pitcher like Ian Kennedy has a home in spacious San Diego, it’s important to note that the Padres are slated to face some tougher-than-average lineups.

ERA drops off pretty sharply when we get to the NL. Surprisingly, hitters for the Nationals and Dodgers appear to have the easiest schedules in their league, despite being in divisions which are better known for their sharp pitching than strong offense. Not having to face the likes Clayton Kershaw or Stephen Strasburg can do wonders for a lineup.

The heavy-hitting Tigers are slated to face the worst pitching staff in the majors. While this is somewhat unfair considering they have the league’s best hitter, it is very unfair that the lowly Marlins will face the best pitchers in the league.

Projections are only predictions, and assuredly some teams will drastically outperform and others will underwhelm by season’s end. However, these data remind us that our preconceptions about who plays in an extreme park or which teams are in difficult divisions should not be overemphasized, nor should we discount the idea that some lineups or pitching staffs will have a significantly more difficult time than others. Over the course of the season, a single team will square off against almost 20 other teams in over a dozen different parks. Whatever the strength of their schedule, position players and pitchers face a wide variety of competition, and no doubt a good many will surprise us all.

Who will lead the Athletics in power statistics this year?

The Oakland Athletics are a very deep and very solid team. There are few holes on the team and they get contributions from most of the hitters in the lineup. The Athletics do lack one thing that some of the other competitors for the American League crown have: one power bat that pitchers have to plan for. This may not be a bad thing, as there could be as many as three guys in the Athletics lineup that could hit over 30 home runs.

Josh Reddick was an powerful force for the Athletics in 2012 after the team acquired him for Andrew Bailey. Reddick was a solid offensive prospect for the Red Sox coming up through the system but after a breakthrough 2008 season, never hitting more than 20 home runs again and seeing his average lower as he struck out more. He had a good 2011 season with Red Sox, but the team was looking to add bullpen depth after losing Jonathan Papelbon and Reddick was seen as disposable. Given a full time role in Oakland, Reddick hit 32 home runs, stole 11 bases, and exhibited his cannon of an arm; he finished 16th in the MVP race and, even with a lack of patience and rise in home runs, the Athletics had an answer for a power boost. In 2013, Reddick was injured a bit and when he was healthy some of his positive trends from 2012 regressed. The most obvious difference was that Reddick hit 5% less fly balls in 2013 than in 2012 and also averaged 5% less home runs per fly ball. Given those ratios, it should not be too much of a surprise that his home run total dropped from 32 to 12. Reddick was a bit more selective with his swings and if he is able to get some better contact, he may be able to get back to hitting 25 or more home runs. It is very important that he does not focus on hitting home runs as that could detract from his better strike zone recognition.

Yoenis Cespedes came over from Cuba as a big time power hitter and has done a pretty job of hitting for power thus far in the majors. He was a top 10 MVP finisher in 2012, with 23 home runs on top 16 steals and a .292 average. He struck out a bit too much, but nothing that was that much of a problem for the Athletics. In 2013, Cespedes was inconsistent and his free swinging ways really hurt him. He may have him 26 home runs, but he had a sub-.300 OBP and appeared to be hacking for the fences way too much. His fly ball rate rose as he hit more home runs, but almost everything else about his game was worse in 2013 than in 2012. The 28 year old Cespedes is in a similar place as Reddick in that he needs to make strides to become a better hitter rather than mash the ball out of the park. He does have extreme power, putting it to display by winning the Home Run Derby in 2013, but his downfall may be his aggression. He has the reputation of a free swinger and that can get him into a lot of trouble with strikeouts and a loss of good contact. Cespedes may be able to hit 30-35 home runs and has the most power potential on the team, but his power may be a detriment to his whole game. The Athletics acquired Cespedes for his power and the team will still rely on that power but it would help the Athletics if he would focus more on finding ways to get on base.

Brandon Moss came out of nowhere to be a very good player for the Athletics the past two years. After bouncing around the Red Sox, Phillies, and Pirates organizations and showing that he had some good power without results at the big league level, it finally clicked at the big league level in 2012 for Oakland. Moss had a .954 OPS with 21 home runs and was versatile in that he played first base and the outfield. The ugly thing for Moss is that he does not have a ton of patience at the plate, which held him up in his pursuit of a major league job, and that was an issue in 2012 and became a big reason for a regression in 2013. He was still very solid with a .859 OPS and 30 home runs in 145 games but his average was down from .291 to .256. He did walk a bit more and strikeout less and those are positive trends that could lead to Moss becoming an All-Star. He showed that he could withstand a full MLB season for the first time and was stronger in the second half of 2013 than the first half. He is having a good spring training thus far and it would not be insane to see Moss with 35-40 home runs this year. His average might only get to the low .270s, but if he builds on the good trends of less strikeouts and more walks, he will be the best offensive player for the Athletics.

When will Addison Russell take over at shortstop?

As this prediction will show, the Athletics should be the team that wins the American League West; this is even without a hitter that could be the number 2 hitter for the Athletics right now. Addison Russell is a very solid hitting, consistent shortstop and should be the shortstop for the Athletics for the better part of the next decade. Unfortunately for him, Carlos Correa, Javier Baez, and Francisco Lindor all play the same position as him, so he has been swept under the rug a bit. Soon this will not be the case and Russell will take over as the shortstop and the Athletics will be better off for it.

There is a very good chance that the 2012 draft will go down as one of the strongest drafts in recent history, as most of the top 20 picks in the draft have either aggressively moved up through their respective organizations or have had extreme success in the lower levels. In 659 at-bats since he was drafted, Russell has a .302 BA, 39 doubles, 19 triples, 24 home runs, and 37 steals. Those are extremely impressive numbers, but it is even more impressive when you consider that he was only 18 and 19 as he accumulated these numbers and that he has even had a short stint in Triple-A. He may not have the plate discipline of Francisco Lindor, but as a 19 year old in High-A, Russell still had a .369 OBP and 125 strikeouts compared to 61 walks. He was the best player in the California League for most of the season and did not look overmatched hitting against pitchers that were 2 or 3 years older than him. All of the hitting was impressive, but his fielding is what will make him a stalwart in the Athletics infield and move him up through the system quickly. His defense grades out as outstanding and when added to his solid hitting for a shortstop, Russell may be an All-Star for years to come.

If the Athletics wanted to move Russell aggressively through the system, they could. Alberto Callaspo is a serviceable player, but he is not going to add any value to an already solid Athletics team. He could play all over the diamond and Russell could easily take his spot in the starting lineup. Jed Lowrie is a super utility player at shortstop and could easily move to second base if Russell is going to move up to the majors. The Athletics are a very good team and have flexibility with both Lowrie and Callaspo so it might not be a bad idea if the Athletics move up the talented 20 year old shortstop to the majors. He needs to continue to work on his plate discipline and have his walk rate continue to trend in a positive way. He has had a decent start so far in major league camp in Spring Training, hitting .263 in his first 19 at-bats. It would be smart for the Athletics to let him develop in the minors a bit longer but a hot start should get Russell to Oakland as the starting shortstop.

How good exactly is the Athletics bullpen?

The Oakland Athletics had a very strong bullpen over the past couple years and they did something this offseason that most of the good teams do; they made it even stronger. Through the aggressive acquisitions of Jim Johnson, Luke Gregerson, and Eric O’Flaherty, Oakland may be in a position to end games once they get a lead in the 6th or 7th inning. This may be a very good thing as the rotation is very young and may not been able to get as deep in games as other rotations could.

Sean Doolittle was a good prospect out of the University of Virginia, in fact was a first round pick as a first baseman in 2007, but had two major knee injuries and a wrist injury that derailed his hitting career and he turned back to pitching. In 2012, Doolittle fully converted to pitching and was absolutely stellar in the bullpen in the minors, moving from High-A to the majors with only 25 innings; albeit 25 innings where he struck out 48 batters with 7 walks and allowed only 2 runs. Since getting up to the majors in June 2012, Doolittle has a 3.09 ERA, 1.006 WHIP, and 9.3 K/9 with a 5: 1 K: BB ratio. His true ERA is even lower, at 2.37 and Doolittle has been very reliable, pitching around 70 innings each of the past two years. He has had 51 shutdowns as compared to only 15 meltdowns over the past two seasons and his fastball has been a true weapon, rated as one of the best pitches in baseball. He was a bit worse in 2013 than 2012, seeing his ERA rise while striking out fewer batters, but it was also his first full season in the majors and everything would suggest that Doolittle will continue to be a lefty force out of the Athletics bullpen.

Ryan Cook is another one of the strong young arms in the Oakland bullpen. A part of the trade that sent Trevor Cahill to Arizona and brought Jarrod Parker to Oakland, Cook has been the best pitcher out of the Athletics bullpen over the past two seasons. His ERA is sterling at 2.30 with a WHIP of 1.11 and has more than a strikeout an inning since coming over to Oakland. He walks a bit more batters than Oakland would like and was more dominant in 2012 than 2013; he threw more changeups in 2013 than 2012 in an effort to be more of a ground ball pitcher. His ground ball rate was similar in 2013 and 2012, but there were more line drives hit off of Cook in 2013, raise his GB: FB ratio. The biggest issue for Cook is that he throws a strong 95 mph fastball and that pitch was dominant in 2012 and saw a decrease in value in 2013. With such a strong fastball that is thrown 68% of the time, Cook needs to get his value back to that pitch; his slider and changeup can develop off of this pitch and make Cook even more value than he has been over the past two seasons. Cook will be relied upon in the 7th and 8th inning to get some tough outs for the Athletics and will give the Athletics a weapon out of the bullpen.

Luke Gregerson was added to the bullpen for the 2014 season and he should only strengthen a bullpen that was already strong. Over the past five seasons, Gregerson has been a strong reliever for the Padres and the Athletics looked to add some veteran leadership to the bullpen by adding the 30 year old. There is a lot of strength in the Athletics bullpen, but a lot of the pitchers are relatively unproven. Gregerson averages 73 appearances a season since 2009 and has a 1.09 WHIP and averages more than a strikeout an inning during that time period. He had a bit of a rough 2011 where he only had a 5.5 K/9 and 3.07 BB/9, but those ratios returned to their career baselines over 2012 and 2013. The biggest issue for Gregerson is that he had only 29 shutdowns and 15 meltdowns last year; those numbers were able to be contained on a Padres team that did not compete in 2013 but he is now on a competitor in Oakland. He averaged 31 shutdowns and 12 meltdowns in the seasons prior to 2013 and he should return to numbers close to that in 2014. He will a part of the new 8th/9th inning combination with the Athletics and should serve as a part of a good ending to a lot of Athletics’ games.

Jim Johnson has very big shoes to fill, as Grant Balfour was a great closer for the Athletics in the past two seasons. For a team like the Athletics who are ready to compete for a World Series title, it is important that they are able to close down the game, especially considering that the rest of the bullpen is so good. Johnson’s power sinker was devastating 2011 and 2012 as he was one of the best relievers in baseball and a part of a bullpen in 2012 that was 29-9 in one run games and had a streak of over 100 games won where they had the lead going into the 7th inning. He has saved 50 games in each of the two seasons, but in 2013 he had 12 meltdowns as compared to only 3 in 2012. He is not a strike out pitcher and that scares a lot of people. Also, his ground ball rate was down 4% in 2013 and that 4% moved to line drive rate. The eight more line drive hits between 2012 and 2013 may seem insignificant but in one inning spurts, this could be the difference that leads to the Athletics losing games. If Johnson is able to keep his sinker down and induce ground balls, the Athletics strong infield defense will allow him to have a great season as the new closer in Oakland.

The Athletics have a young rotation that will need a lot of assistance from a strong bullpen and that will probably be the case in 2014. With a strong bullpen like the Athletics have, most games that the Athletics lead in the 6th or 7th should be a win.

What will Josh Donaldson do to repeat his great 2013 season?

Josh Donaldson did not come out of nowhere entirely during the 2013 season, he was a first round pick in the 2007, but no one could have reasonably predicted that he would be as successful as he was in only his second full year in the majors. In fact, coming into the season, many assumed that it was his defense that would make him so valuable to the team and that was why he broke camp as the starting third baseman to begin with. After a 4th place finish in the MVP race, it will be important to see why Donaldson was so successful and how that success can translate to the 2014 season.

Donaldson was a first round pick by the Cubs out of Auburn in 2007 and was a part of the trade that sent Rich Harden to the Cubs in 2008. Donaldson was extremely attractive because he was a catcher that hit .346 in Low-A in 2007 with more walks than strikeouts, but was off to a slow start in Peoria in 2008, making him expendable for the Cubs. After he moved on to the California League with Stockton in the Athletics organization, he went back to having an outstanding walk to strikeout ratio and had a .381 OBP between the 2008 and 2009 seasons in High-A Stockton and Double-A Midland. Between the 2010 and 2012 seasons in the minors, Donaldson alternated between third base and catcher and his numbers in 2010 and 2011 were pedestrian in Triple-A Sacramento. A hot start in 2012 in Sacramento led to a promotion to Oakland.

Once in Oakland, Donaldson moved to third base for good and, although he was not a force offensively, was good enough to be in the running to be the starter at third in 2013. Nothing could have predicted that Donaldson would have the offensive season that he had in 2013, but his walk rate and strikeout rates were back to the solid ratios of the past and much better than the paltry numbers from 2012. In fact, most of Donaldson’s ratios returned to those that he had when he was taking his first try at A ball in 2007 or when he tore up Triple-A for 51 games in 2012. He had a .883 OPS with 24 home runs, 37 doubles, and 93 RBI. His defense continued to be elite, in fact he was the third best defensive third baseman in the American League, and he even had a higher WAR than MVP Miguel Cabrera.

For Donaldson to be as successful in 2014, he needs to continue to hit the ball hard. A ground ball hitter in 2013, Donaldson needs to make sure that those grounders find holes or his average will fall off a bit. He was a decent base runner in 2013 and had a jump in HR/FB ratio, two trends that will continue to give Donaldson value. He may not be nearly an 8 win player again in 2014, but his defense and solid walk and contact rates will keep Donaldson as a 5 win player; this is much more than the Athletics envisioned when they acquired him in 2007 and will keep him as a vital part of the Athletics’ success.

Why are the Athletics going to win 95 games?

The Oakland Athletics may be the best team in baseball. In fact, there were a couple different projection methods that were examined in these analyses and none of them had the A’s winning less than 93 games. Their bullpen is very solid, the rotation is young and deep, the lineup has great depth, and there is very good leadership with this team. Projections are great and math is not everything, though, and there are a couple things that may hurt the Athletics and could even keep them out of the playoffs. Brandon Moss has been very good in spurts over the past few years and the projections like him a lot more than his true talent, the same goes with Yoenis Cespedes. There has been enough written on Josh Donaldson and there are reasons to believe that his numbers from last year were an aberration. Moss needs to keep up with what he has done in the past, Cespedes needs to be less streaky, and Donaldson needs to show that last year was not a fluke. If those three things can happen, the A’s could quietly have the best lineup in baseball. There are many young, strong arms in the rotation and there is every reason to believe that their respective best seasons are coming soon.

5 You Know:

1. AJ Griffin

2. Josh Donaldson

3. Jed Lowrie

4. Brandon Moss

5. Yoenis Cespedes

5 You Will Know:

1. Addison Russell

2. Sonny Gray

3. Raul Alcantra

4. Michael Ynoa

5. Billy Burns

5 You Should Remember:

1. Billy McKinney

2. Bobby Wahl

3. Daniel Robertson

4. Renato Nunez

5. Dylan Covey

By far, the hardest thing about fantasy baseball is the fact that you can’t predict the future. Every year, a Matt Carpenter or a Chris Davis vastly outperforms expectations and wins a fantasy league for somebody, and a Matt Kemp battles injuries all year and makes somebody else tear their hair out. But you learn to deal with that sort of thing, or you take up a less stressful hobby, like Russian roulette. C’est la vie, and all that.

What this article is about, however, is that the second-hardest thing about fantasy baseball is trying to juggle categories. Which is better, Mike Trout’s five-category production, or Miguel Cabrera’s dominance in four categories? How much is it worth to have Billy Hamilton singlehandedly win stolen bases for you while contributing nothing in the other categories? Can you absorb Pedro Alvarez’s batting average hit for the home runs he gives you? Over the years, people have come up with a few different ways to try to answer those questions. Standing Gain Points (SGP) is one popular method. Z-scores are another. There are others, but those are the two I see the most, so they’re the two I’m going to talk about. The point of this article isn’t to compare all of the ranking systems out there and figure out which one is “right.” The point of this article is to call attention to the fact that your choice of ranking system matters, probably more than you think.

Of course, most fantasy ranking systems start with projections. Personally, I like to use composite projections, because I think there’s value in combining projections and smoothing out spots where one system might be exceptionally high or low on a player. You can disagree with the projections – that’s not the point. The point is, you (or your fantasy expert of choice, if you use published rankings) can take the same projections, plug them into different ranking systems, and get substantially different results.

For the purposes of this article, I’m keeping things very simple, perhaps a little too simple. I don’t care about volatility, risk, upside, injuries, etc. I’m assuming that these projections are accurate. And I’m not going to bother with positional adjustment, because I’m lazy and these aren’t the rankings I’m drafting from, and it doesn’t matter anyway. I’m concerned with how using different methods changes players’ rankings relative to each other, not how much to bump Buster Posey up my draft board because I need a catcher. And I’m looking at rankings, not auction values, because that’s another step that I don’t feel like taking right now.

I’m going to look at the shortstop position (specifically the top 14, because I play in a 14-team league) for this article, because I need to narrow things down to a manageable number of players. I’m assuming a standard 5×5 league. And what I’m looking at is SGP (using the formula here), compared to two slightly different ways of calculating z-scores. In all cases, I’m looking at the rankings of each player among shortstops and among all hitters.  Really, though, I’m concerned with the overall rankings because I want to see how players move around – the choice to focus on shortstops is just a convenient way to select a handful of players to look at.

Anyway, on to the fun stuff:

SGP shortstop rankings:

Looks reasonable. I don’t know. We don’t have anything to compare it to yet. So let’s compare it to z-scores. For this example, I’m going to calculate my average and standard deviation for each category using all players projected for over 300 at bats.

Z-score shortstop rankings using all players with >300 AB:

Comparing those two tables, the methods agree on the top 14 shortstops. For the most part, these rankings are pretty similar. But Tulowitzki moves up a few spots in the overall rankings, which isn’t insignificant that early in the draft. Segura drops a round or two, and swaps spots with Desmond in the shortstop rankings. Andrus moves down the overall rankings a bit. Everth Cabrera moves down the overall rankings quite a lot, going from a mid-round steal to a guy who’s probably merely a decent value at his ADP.

So we learned a few things there, maybe. But when I use z-scores, I don’t think it makes sense to calculate them using every player who sees significant playing time – most of those will probably never be rostered in your fantasy league. I want to compare fantasy-relevant players to other fantasy-relevant players, not waiver wire fodder. So let’s take the top 200 hitters, as determined by the initial z-score rankings, recalculate the average and standard deviation for each category using only those players, and try again.

Z-score shortstop rankings using the top 200 players:

Again, everything looks pretty similar at first glance. Alexei Ramirez drops off the list in favor of Jed Lowrie, but that’s no big deal. But Tulowitzki moves up another couple spots – he’s pushing first-round value now, even before positional adjustments. Segura and Andrus drop a little further in the overall rankings. Cabrera, who was already worth less using z-scores, is even worse with a smaller player pool. Remember, that rank of 93 is only among hitters – factor in pitchers, and Cabrera, a mid-round steal using SGP, now looks overvalued at his ADP of 106 (though we can’t say that for sure without applying positional adjustments). All things considered, simply changing the size of the player pool had as much of an effect as changing from SGP to z-scores in the first place.

Depending on which ranking method you use, you’re going to place a pretty different value on some of these players (again, with the caveat that I didn’t do positional adjustments). At the top of the shortstop rankings, Tulowitzki could be anywhere from a late second round pick to a borderline first-rounder. Cabrera’s value swings wildly depending on what system you use – he’s either a player to target fairly early, or borderline undraftable where you’d have to take him. Other players, like Hanley Ramirez or Brad Miller, are remarkably consistent across all three methods, but there’s no way to know how much of that is chance.

The natural thing now is to wonder is which of these systems is right. This seems like it should be solvable. I really want there to be an answer to this, a clear way to combine five categories of production into a single overall rank. Unfortunately, I’m not convinced that exists. People smarter than me have come up with a few different ways to reach that goal, and the results don’t agree with each other. Even if they did, the needs of your team are going to evolve as the draft goes on. When you pick whatever method you prefer and compile your pre-draft rankings, the numbers you get are going to look pretty absolute, there in black and white in your spreadsheet. But really, they’re more like ballpark estimates, and they could easily be totally different.