Kiley McDaniel is Part of the Orioles Front Office

Kiley McDaniel is now with the Orioles. His responsibilities have not been announced to the public, but the gist most likely has something to do with amateur talent acquisition. Most recently, McDaniel was writing for Baseball Prospectus with a slant on the Latin American market. Before then, he was co-founder of SaberScouting.

His partner in crime there, Frankie Piliere, is now a writer with AOL Fanhouse and focusing on minor league prospects. We have linked to him before.

Anyway, we wish McDaniel the best and hope this is something that help boosts our amateur talent coming into the system.

A somewhat blind stab at revenue sharing . . .

In a recent article at Baseball America, Maury Brown discusses revenue sharing. He wrote:

Revenue-sharing money comes from two pools. One is central fund revenue, which comes from national television and radio deals, Major League Baseball Advanced Media, merchandise sales and the newly formed MLB Network. Each of the 30 clubs got a check for about $30 million in 2009 through this arrangement.

The other pool is the one that has created tension between small- and large-revenue clubs, as it is the one that transfers money between franchises. This pool is made up of net local revenues, such as ticket sales, concessions and media deals that each club negotiates for television and radio.

What is uncertain is how the second pool is dispersed. The following numbers are based on the total of 433MM of revenue sharing reported in the Biz of Baseball. I then merely assumed the money was paid out similarly to the 2005 scheme, but that is probably a rather large assumption.

Tampa Bay Rays 45.9MM
Marlins 43.1MM
Blue Jays 43.1MM
Royals 41.7MM
Pirates 34.8MM
Tigers 34.8MM
Brewers 33.4MM
Twins 31.6MM
Athletics 26.4MM
Reds 22.3MM
Rangers 22.3MM
Diamondbacks 18.1MM
Indians 8.3MM
Phillies 8.3MM
Padres 8.3MM
Nationals 5.6MM
Orioles 2.8MM

This method would suggest that Scott Boras was correct in his assertations earlier this offseason. It also suggests that MLB cuts a check for the Orioles at the tune of 32.8MM.

There is no text after the jump.

Projected Season Wins: Vegas vs Diamond Mind Projections . . . Part II

Last week I compared actual season wins against projected seasons wins using projections systems and the Vegas Line. In general, what we found was that each system was pretty accurate. We also found that teams do not overperform considerably (exceeding one standard deviation) if either system predicts the team to win more than 90 games, but that there are several instances of underperformance for these teams (particularly with the projection-based system). Two interesting and most likely non-applicable observations were that Vegas lines tended to under estimate teams they predict to win 85-90 games while the Projection systems tend to underestimate teams in the 73-78 win range. I do not know why in either instance and think it may just be a statistical abnormality.

Today, after the jump, we will be comparing the Vegas line to the Projection system. Again, I have little to no clue about gambling, so I am not sure what it all means related to that . . . if someone wishes to guest blog something about that would be swell. For me, it has more to do with differences between the wisdom of the crowd and the wisdom of a carefully optimized set of algorithms as well as how that might apply to betting . . . which again is something I do not well understand. In this set of analysis, I will be looking for instances where the crowd wisdom would prevail in an over/under bet against the projection system.


The way I chose to compare the Vegas line against the Projection system is to look at instances where they differed against each other by a standard deviation (~8 wins) and then by an arbitrary number that sounds nice (5 wins).

There are 11 instances in which the two system disagreed by 8 or more wins. In three of these instances, siding in agreement with the projection system would win up with losses against the crowd line. I cannot find much in agreement with these three data points other than all three have Projection estimates of under .500 winning percentage. Limiting it to that criteria, we would get a 4-3 betting scenario. The data here is limited, but that might be a decent working hypothesis: trust the projection systems when there is an 8 game spread between the two and the projection system guesses a winning season. Another working hypothesis is to go with the projection system when the spread is 8 games and the projection system predicts fewer wins (5-1) as opposed to more wins (3-2) than the Vegas line. Still, the amount of data is not very great.



There are 27 instances in which the two systems disagreed by 5 or more wins and again the rate at which the Vegas line wins is about 25%. Using the working hypothesis generated above with 5 game or greater spread and a winning Projection-based record, 9-2 is slightly better than the entire data set. The second working hypothesis (5 or more spread with projection predicting less) winds up with a 10-2 result, which is better than the alternative 11-5). Again, the power of this study is pretty limited, but it is something that we will tease apart more so in the future.



When all of the projections come in, we'll comment on who fits into these classifications and follow how well the working hypotheses work.

The Giants and Steve Johnson

Last December we explained why it made complete sense why Steve Johnson was left unprotected for the Rule 5 draft and why he was likely to return to the Orioles. Today, I'd like to explore Johnson's potential for sticking with the Giants this season. First off, the Giants will carry seven arms in their pen. Five are essentially locks to being the season. They include the closer Brian Wilson, whom many compare favorably to Jonathan Broxton. He has a live arm and was successful in the role last year for the Giants. Their set up also return. Jeremy Affeldt and Sergio Romo also had solid years and are definites. In middle relief, Brandon Medders solidified his role last year and Dan Runzler emerged as the minor league Giants pitcher of the year as well as being fairly unhittable in his short time in the Majors last year.

This leaves two slots open for Steve Johnson to fill: middle relief or long relief. With both Runzler and Affeldt as southpaws, Johnson's righthandedness should not impede him. It also helps that his role is one in which very little is expected. Merkin Valdez and Joe Martinez/Ryan Sandowski held down the middle relief and long relief/swingman roles, respectively. Of those players, only Joe Martinez remains. What also works for Johnson is that Giants personnel are very positive about Johnson after watching him for several seasons in the Dodgers' system.

After the jump, Johnson's competition for these two positions and what this may mean for the Orioles.


Todd Wellemeyer, RHRP (has started in the past)
Wellemeyer is a non-roster invite to the Giants camp. He came up as a reliever in the Cubs system. After winding up in St. Louis in midway through 2007, he proceeded to pitch quite effectively as a starter for a year and a half. He kept his strikeouts above 6 per 9 and did well to limit walks. That fell apart last year as he missed awfully few bats. Wellemeyer is something that the Giants brass are known to love . . . veterans. He has pitched for many years and has shown a great degree of competence. Todd Wellemeyer is basically Steve Johnson seven or so years from now.

Joe Martinez, RHRP (has started in the past)
Martinez filled the role of swingman and long relief last year. He did not do well posting a 7.50 ERA over 30 innings. Unless he shows some promise, he most likely will be sent down to AAA and be the first brought up. Based on my math, he should have 2 options left.

Kevin Pucetas, LHP (starter in minors)
Pucetas has rather average pitches, but was shown to pitch quite effectively in low and hi A ball. Last year, the Giants chose to skip him over AA and he proceeded to be rather ineffective at AAA Fresno. A conservative organization would allow him another year to start at Fresno. If the Giants think they are close to the playoffs, they might prefer having another left handed option in the pen. I'd be doubtful that he could start in the Majors with his repertoire.

Waldis Joaquin, RHRP
Joaquin threw 10.2 innings at the Major league level and showed that he could miss bats (10.1 k/9) and strike zones (5.9 bb/9). He tasted the Majors last year after dominating AAA for 8 innings. That may have been an aberration.

Guillermo Mota, RHRP
Mota just signed as an NRI and would be considered for the middle relief position. He is a veteran who has pitched as a closer and setup man. It is the typical M.O. for the Giants organization to employ a player like Mota in the pen. His peripherals have been slightly shaky the past two seasons, but he has been an integral part for the Dodgers and Brewers bullpens. I would be surprised if he did not wind up being the 6th man in the pen.

I doubt any of the non-roster invites will put up much competition to these guys. NRIs: Denny Bautista, Santiago Casilla, Rafael Cova, Steven Edlefsen, Eric Hacker, Osiris Matos, Tony Pena Jr., Felix Romero, Dan Turpen, Craig Whitaker, Craig Clark, and Clayton Tanner.

Who is likely to get the middle relief role?
1. Mota
2. Joaquin
3. Wellemeyer
4. Johnson

Who is likely to get the long relief role?
1. Wellemeyer
2. Martinez
3. Johnson
4. Bautista

I find it near impossible for him to win the last middle relief slot. I find there to be some chance he could stick on in the long relief role. My bet is that Mota and Wellemeyer wind up in these two slots. The Giants tend to embrace veterans and might be reluctant in giving slots for a rookie to hide and take his lumps. I do think the Giants value him and believe they will be looking to trade for him.

What is Steve Johnson worth and what do the Orioles need?
John Sickels rates Steve Johnson as a C+ prospect (all Sickels grades links here AL - NL). In return the Orioles would probably receive a prospect with a similar grade. Areas of organizational need for the Orioles would be second base, short stop, and left-handed relief. The following players fit that criteria:

2B Nick Noonan (C+) - Noonan has his supporters and is thought to be more valued in the Giants front office than elsewhere in baseball. It remains to be seen if they would entertain a straight trade for Johnson. Last season saw Noonan as a 20yo in HiA. Poor contact skills, good plate discipline, average power, below average speed, and very good base running. He seems to be a very smart player. He is a kind of prospect who could break out in the next season or two. He would slot in at AA and compete with Ryan Adams. Both profile as offensive 2B, but Noonan has much more speed. Noonan is an NRI this year.

LHSP Aaron King (C+) - King has a powerful arm and would be shoehorned into a tight starting rotation in Frederick. It might be more realistic though to begin shifting him toward being a potential dominant bullpen arm. The hope would be that pitching from the stretch and focusing on his low 90s sinker. His mechanics are a bit of a mess, so I doubt he will be valued by many as a starter.

LHSP Clayton Tanner (C+) - Tanner is similar to Johnson in that he is a lefty that is better known for pitchability than how impressive his actual pitches are. After repeating HiA and getting hit much harder the second time through (1hr in 2008 vs 18hr in 2009), he still managed to do pretty well. His soft spot was right handers hitting him hard. His FIP against lefties was 3.04, while it was 5.11 against righties. Only one lefties hit a home run off him. He will probably start in AA, but is beginning to look like someone who will eventually be shifted to a LOOGY role.

SS Ehire Adrianza (C) - His raw tools are very solid. His glove is excellent. He has an athletic body that can probably put on another 10-15 pounds. He also has shown very good plate discipline. At 19, he held his own quite well in loA with a 258/333/327 line. His contact rate is not good and I doubt he will develop much power. That said, a young SS with a solid glove and good discipline is a rare find.

SS Brandon Crawford (C) - Crawford, as you many remember, was our 4th round selection in the 2008 shadow draft we ran in real time. His glove is solid and compares rather well with Adrianza's. Both should be MLB quality in their defense. His bat? Back in 2008 we wrote this:

Dating back to the Cape, he has been pressing rather than letting his game flow naturally. As his struggled continued, he pressed harder -- regularly lunging at pitches and frequently showing signs of frustration. He has demonstrated a potential for plus-power, but he'll have to improve his contact rate to realize it.

In HiA, Crawford was either excellent or was no match for the pitching at that level. He broke out with a 371/445/600 line in 105 at bats showing off very good power. He was then promoted to AA and struggled. He struck out 25% of the time. Had difficulty earning walks. He did show some gap power (ISO - .107), but nothing very extraordinary. It would probably benefit him repeating AA. He needs to show better plate discipline and a better contact rate. In the Baltimore system, he will be having to share time with Pedro Florimon, Jr., whom the Orioles seem to favor.

Who would I want?
1. Ehire Adrianza
2. Nick Noonan
3. Brandon Crawford
4. Aaron King
5. Clayton Tanner

I think the Giants would probably look to move Crawford or King from that group.

Beyond Batting Average and interview with author Lee Panas

As many of us who discuss sabermetrics and statistics in general and how they relate to baseball; it is a subject that carries a broad range of awareness and acceptance in conversations about the game. The most recent statistical discussions have occurred over the past decade and taken place on the internet. As conducive as the internet is to share information and quickly acclimate to new truths and create or discover new applications, it has some problems as it is a very ephemeral library. Little is written down and much is carried on in a digitalized form similar to Homer. Web sites close shop, people get hired and their work gets scrubbed, and many baseball critics do not follow rules of citation very well. It makes it difficult to get caught up to speed on the conversation even if you are interested in how to use metrics in baseball.

A problem I have often seen when a book is written about sabermetrics is that they are often grooved for those in the mid- to hi- level of competency in the field. Introductory level works are hard to find and are a major reason why many web sites are beginning to post running SABR 101 FAQ's on their sites. It has also led to SABR series on Yahoo! and other online publications. Thankfully, I think I have found an actual book that is somehow both a handy introduction to what statistics mean and their utility in baseball as well as a resource for more advanced users of metrics (which is quite needed as metrics are often used incorrectly). Lee Panas' Beyond Batting Average is this book.

Panas does well to present the historical time line of statistics from Chadwick's original descriptive statistics to Branch Rickey and his usage of ISO to present day concepts like linear and nonlinear metrics. One amusing side note indicates how folks complained about new metrics in the late 1800s just as people do now with stats like WAR or xFIP. Panas does well to give you the formulas for advanced stats if you wish to play around with them, but moreso they act as an illustration letting you know what each statistic accounts for and how they are weighted. In the text, he simply and straight-forwardly explains what the formulas mean and how that effects statistical outputs. He informs the reader what each stat does well and their limitations.

As you have noticed I rarely review a book, but this is one that I think merited that. It is a solid addition to anyone's library. The introductory baseball statistics reader who wants to learn more and be able to start engaging in conversations about metrics would find this most useful. More advanced readers will see this as being useful at times for the quick to grab metrics and have a solid citation when making a claim about repeatability for a certain statistic and how that might relate to a skill.

Lee was kind enough to take part in an interview with Camden Depot. It is shown in full after the jump.


Camden Depot: I often find it important when reading a book to understand who the author is and from where personal experience is he/she writing. I was hoping you could give us your background, information about the blog you write, and other items you think potential readers of your book would be interested in.

Lee Panas: I have been interested in sabermetrics since the early 1980s. Bill James was writing his Baseball Abstracts at the time and he was a big influence on me. In addition, I was studying mathematics and statistics in college and some of my classes required me to apply statistical methods to real data. So, I used baseball statistics in a few of my projects. This gave me the opportunity to prepare for my career as a research analyst while learning more about baseball at the same time.
I have been writing at DetroitTigerTales.com since 2005. I discuss a lot of topics besides statistics there - Tigers history, prospects, transactions, etc - but sabermetrics has always been the overriding theme. I have written a lot about baserunning and fielding statistics in particular. In addition to my blog , I am currently writing about the Tigers for John Burnson's Heater Magazine. I have also contributed to books such as Tigers Corner, Graphical Player and How Bill James Changed Our View of Baseball.

CD: From experience, I have found that taking on a large endeavor (i.e. a book) often comes from a moment of transcending excitement and then several months of trying to pay dues to that initial moment of inspiration. Was there a singular moment that convinced you that you had to write this book? If not, where do you think this urge originated?

LP: There was not really a single moment where I decided to write a book. It's something that has been building for a long time. I have avidly been discussing baseball on message boards and blogs for a couple of decades. Much of my time has involved explaining sabermetrics to people. In the early years, there wasn't a great deal of interest in the subject. However, I have noticed a lot more people getting curious about it in recent years. Blogging has been a good way to educate more people about the field but I can only give small does in that format. Thus, it became increasingly clear that I wanted to write a book where I could tie all the information together into a complete story.


CD: The sabermetric field has seemed to me that it is moving toward a goal that is to evaluate the true talent of a player. That is, a progression from simple descriptive statistics to predictive/evaluative ones. From what I have read in your book as well as the outline, it seems to me that you very much support this perspective on moving toward predictive statistics. Do you think anything (i.e. blind luck, MVPs) is lost or being lost (or devalued) in terms of appreciation by doing this and is that bad?

LP: For the most part, I think trying to evaluate a player with predictive statistics is a good thing. As you know, some of the more traditional statistics are based on things that are largely beyond a player's influence. It makes sense to eliminate as many outside factors as possible and to evaluate a player on things he can control most easily. I think that we are getting increasingly better at finding statistics which more accurately define a player's true talent.
There is, however, the potential for skills to get lost in this approach if we are not careful. I'll use ERA as an example. Statistics such as a strikeout rate, walk rate, ground ball percentage and FIP are more predictive than ERA for most pitchers. However, they don't take into account the ability of a pitcher to pump up his fastball or to induce a double play ball with runners on base. It has been shown that this has more to do with overall pitcher quality than clutch pitching ability. However, I think more work needs to be done to identify pitchers who may have more ability to pitch in high impact situations than others. For these pitchers, ERA might be telling us something that the so called true talent stats are missing.

CD: One of the more fearsome aspects of writing a book on baseball statistics is that the community is internet based and the level of information progresses so quickly. I think you have done a great job is writing something that is rather resilient in light of that. How did your recognition of the blinding pace of statistical innovation direct you in writing this book?

LP: First, I think the fast pace of sabermetrics has left some people frustrated because they can't keep up. That is one of the reasons I wrote the book. By organizing all the information in one place, I think it helps people catch up. I also hope through reading the book, fans will understand more about the reasoning behind the statistics. This should help readers make sense of future measures more quickly.

One thing I have done throughout the book is to include a bit of history showing the evolution from simple traditional measures to the more advanced measures of today. I think this better prepares readers for the future advances in statistics than if I just dove into the present and talked about the statistics developed in the last two years.

CD: You have mentioned before that you largely relied on peer review for this book. Can you tell us some of the people you consulted in writing this book?

LP: I think peer review is essential in this kind of effort. It's a complex subject and I wanted make sure I got everything right. There are a couple of important sections of the book that might have been left out if it were not for the suggestions of others. There was also a matter of educating myself in certain areas. I had a good handle on most of the statistics coming in but there were a couple of instances where I was not interpreting statistics as accurately as I could. So, I was glad to have the developers of the statistics correct me. Finally, I think peer review helped me write the book in a way that would make it accessible to as many people as possible. For example, there were some sections in early drafts which reviewers felt were a little too mathematical for my target audience. I either eliminated those sections or wrote them more simply.

The reviewers ranged anywhere from very talented sabermetricians who know the field better than I do to intelligent baseball fans who are relatively new to sabermetrics. Some of the key contributors in alphabetical order are John Dewan, Brandon Heipp (aka U.S. Patriot), Chuck Hildebrandt, Justin Inaz, Mitchel Lichtman, Kurt Mensching, Pete Palmer, Samara Pearlstein, Tom Tango and Geoff Young. There were many others but I think this gets the point across that I got input from a lot of different kinds of people.

CD: Thanks again Lee. Very well done.

LP: Thanks very much for the interview.

Lee Panas' blog is Tiger Tales and has recently written, Beyond Batting Average.