Should We Buy It: Most Added Players

May 18

Should We Buy It: Most Added Players

A player turns a good game into a good week, then that week into a good month. Then, before you know it, the player becomes relevant, not only in your AL/NL only twelve team league, or any other deep league for that matter, but in every league you are in. The player has become one of the most added players in Fantasy, but that tinge of doubt circles the back of your head, and taps you on the shoulder, like early onset buyers remorse, and makes you reconsider whether you should drop the relief pitcher on your bench who you’ve waited all year to take over the closer role. But the player has gotten to the point where he cannot stay on the waiver wire any longer. He needs to be picked up now. Not one more second can go buy before someone else might snatch him away from you. Remember that time you could have had Mike Trout/Jose Fernandez? Don’t miss your chance...

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Do More Team Wins Lead to More Save Opportunities?

May 04

Do More Team Wins Lead to More Save Opportunities?

Do more team wins mean more save opportunities? Before I decided to answer this question, I assumed that they didn’t.       My Guess In my head I had a cognitive bias of closers in the 2,000s that racked up saves, but were on teams that were never in contention; In 2000 Antonio Alfonseca (i.e. the Six Fingered Man) led the MLB with 45 saves on a Marlins team tat went 79-82; Joakim Soria was third in baseball with 42 saves on a Royals team that finished with a 75-87 record in 2008. Beyond my selective memory, with further thought about characteristics of winning teams, my assumption was reinforced further. Think about it this way. 90 to 100 win teams have stellar run differentials. We’ve all been there as Fantasy Baseball owners. We pull up our team page, on our respective websites host, and we see that Mariano Rivera (i.e. a closer like Rivera who plays for a frontrunner) pitched one inning, with two strikeouts, and no save, because the Yankees (i.e. a frontrunner) were up 7-2 in the ninth inning. Another characteristic of a winning team, and reason to reinforce my assumption about save opportunities and team wins, are strong bullpens. For example, the Yankees are up 5-2 in the bottom of the ninth, Mariano Rivera has already pitched three times that week, but, as evidence from the previous example, that doesn’t necessarily mean he’s gotten three saves that week, and Joe Girardi/Joe Torre thinks to himself, “Lets give Mo a break, and put in David Robertson/Rafael Soriano/Joba Chamberlain/Fill-In-The-Blank-Eighth-Inning-Man. The Results My study looked at all relievers from 2006 to 2013 who had more than 20 save opportunities. 20 save opportunities is high enough of a threshold to ensure that a reliever was a teams primary closer, and not just middle reliever who had a few save opportunities here and there, which would skew the results: bad, bad. Obviously there were closers who had 20+ save opportunities, got hurt/performed poorly, lost his job, and had a teammate accrue an additional 20+ save opportunities. So really the original closer, absent of injury/poor performance, would have had 40+ save opportunities. Ideally we would like to look at closers who started...

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253 Batting Average Risers and Fallers

May 02

253 Batting Average Risers and Fallers

Because it takes it takes 910 at bats for batting average to stabilize, it is not very helpful to look at the small sample of at bats a player has had in 2014 (as the video below will show). When you try to decide whether or not to by into a player’s early season slump or success, you have to look a bit deeper. So we will look at the players that are projected, by Steamer, to outperform or underperform their current batting average by the largest margin for the rest of the season. Below are some players that should outperform or underperform their current batting averages, according to their Steamer projections. Batting Average Risers and Fallers NameApril AVGROS AVGAVG Diff Daniel Nava0.1490.2620.113 J.B. Shuck0.1560.2630.107 Yonder Alonso0.1670.270.103 Mike Moustakas0.1490.250.101 Pablo Sandoval0.1770.2770.1 Marc Krauss0.130.2290.099 Jedd Gyorko0.1510.250.099 David Lough0.1720.270.098 Carlos Santana0.1510.2440.093 Brad Miller0.1740.2630.089 Jordy Mercer0.1670.2510.084 Ryan Goins0.150.2330.083 Prince Fielder0.2060.2860.08 Carl Crawford0.1940.2710.077 Curtis Granderson0.1360.2120.076 Alexi Amarista0.1720.2460.074 Brett Lawrie0.1920.2640.072 Ryan Raburn0.1640.2360.072 Alejandro De Aza0.1850.2560.071 David Freese0.1930.2640.071 Michael Choice0.2040.2740.07 Chris Carter0.1530.2220.069 Pedro Alvarez0.1720.240.068 Raul Ibanez0.1570.2250.068 Allen Craig0.220.2880.068 Chase Headley0.1860.2520.066 Zack Cozart0.180.2440.064 George Springer0.1820.2450.063 Billy Butler0.2240.2870.063 Jason Heyward0.2060.2620.056 Jhonny Peralta0.1960.2520.056 Will Venable0.1980.2530.055 David DeJesus0.190.2430.053 Mike Olt0.1640.2160.052 Cody Asche0.20.2510.051 Carlos Gonzalez0.2410.290.049 Colby Rasmus0.1940.2410.047 Ike Davis0.1960.2420.046 Ryan Flaherty0.1880.2320.044 Miguel Cabrera0.2770.3210.044 Matt Kemp0.2250.2680.043 Elvis Andrus0.2290.2720.043 Denard Span0.2330.2750.042 Mark Trumbo0.210.2520.042 Starling Marte0.2290.270.041 Abraham Almonte0.2040.2450.041 Chris Johnson0.2310.2720.041 Andre Ethier0.2270.2680.041 Eric Sogard0.2170.2570.04 Kyle Seager0.2290.2660.037 Salvador Perez0.2450.2820.037 Asdrubal Cabrera0.220.2560.036 Wilin Rosario0.2440.2790.035 Brian McCann0.2240.2590.035 Kolten Wong0.2250.260.035 Aaron Hicks0.1880.2230.035 Nick Castellanos0.2330.2670.034 Ian Desmond0.2320.2660.034 Nick Swisher0.2110.2450.034 Grady Sizemore0.2080.2420.034 Nate Schierholtz0.2170.2510.034 Neil Walker0.2350.2680.033 Jean Segura0.2440.2760.032 Travis d'Arnaud0.2090.2410.032 Yunel Escobar0.2190.2510.032 David Ortiz0.250.2820.032 Junior Lake0.2210.2520.031 Buster Posey0.2640.2950.031 Jay Bruce0.220.250.03 Ruben Tejada0.2210.2490.028 Brian Dozier0.2160.2430.027 Jason Kipnis0.2340.260.026 Travis Snider0.2270.2520.025 Donnie Murphy0.220.2440.024 Corey Hart0.240.2620.022 Alex Presley0.2420.2630.021 Brian Roberts0.2220.2430.021 Jason Castro0.220.240.02 Eric Young0.2150.2350.02 David Wright0.2620.2810.019 Martin Prado0.2630.2820.019 Michael Brantley0.2550.2730.018 Gerardo Parra0.2560.2740.018 Luis Valbuena0.2180.2360.018 Alex Avila0.220.2380.018 Joe Mauer0.2760.2940.018 Carlos Beltran0.2630.280.017 Chris Davis0.250.2670.017 Kelly Johnson0.2190.2360.017 Dustin Pedroia0.270.2870.017 Kole Calhoun0.250.2660.016 Aaron Hill0.250.2660.016 Omar Infante0.2770.2930.016 Matt Carpenter0.2640.2790.015 Edwin Encarnacion0.250.2640.014 Brandon Belt0.2550.2690.014 Matt Dominguez0.2310.2450.014 Norichika Aoki0.2840.2970.013 Andrew McCutchen0.2860.2980.012 Domonic Brown0.2530.2650.012 Jonny Gomes0.230.2420.012 Joey Votto0.280.2920.012 Josmil Pinto0.2460.2570.011 J.J. Hardy0.2420.2530.011 A.J. Pollock0.2580.2680.01 Wil Myers0.2450.2550.01 B.J. Upton0.2130.2230.01 Khris Davis0.2380.2480.01 Marcus Semien0.2250.2350.01 Yasiel Puig0.2760.2860.01 Adam Jones0.2650.2740.009 Jose Tabata0.2620.2710.009 Jackie Bradley Jr0.2440.2520.008 Dexter Fowler0.2310.2390.008 Hunter Pence0.2620.2690.007 Brandon Phillips0.2550.2620.007 Alex Gordon0.270.2760.006 Jon Jay0.2690.2750.006 Dan Uggla0.2020.2080.006 Jose Altuve0.2760.2820.006 Derek Jeter0.2720.2760.004 Matt Holliday0.2830.2870.004 DJ LeMahieu0.2910.2950.004...

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What the Stanford Prison Experiment and Stolen Base Totals Have in Common

Apr 01

What the Stanford Prison Experiment and Stolen Base Totals Have in Common

The Stanford Prison experiment was a 1971 psychological study in which 24 male Stanford students were divided into two groups—12 guards and 12 inmates—in the Stanford psychology building and was funded by the US  Office of Naval Research as an investigation into the causes of conflict between military guards and prisoners. The experiment was supposed to last two weeks, but only lasted six days. Guards preformed psychological torture on inmates, took away prisoners’ mattresses and made them sleep on the concrete, told them defecate in buckets that they were forced to keep in their cells, and even forced them to be naked as a method of degradation. Philip Zimbardo, the experiment’s facilitator, concluded that both prisoners and guards had become grossly absorbed in their roles. From a wider perspective, it seemed that the situation, rather than the participants’ individual personalities, caused the participants’ behavior. The same can be said for aspects of Fantasy Baseball, and how the role a player is placed in on their team may matter more than the actual skill set of that player. As I discussed in my last article, a reliever’s value, regardless of their ability, is intrinsically tied to whether or not they are a teams closer. For this week, I thought we would talk about stolen bases, how they are tied to the context of a team’s manager, and discuss players who might see a rise in stolen bases in 2014 from a change in organization. 2013 Stolen Base Attempts by Manager TEAMManagerSBCSSBASB% TEXRon Washington149461950.764 MILRon Roenicke142491910.743 KCANed Yost153321850.827 HOUBo Porter110611710.643 CLETerry Francona117361530.765 TORJohn Gibbons112411530.732 SDNBud Black118341520.776 NYNTerry Collins114351490.765 CHARobin Ventura105421470.714 NYAJoe Girardi115311460.788 COLWalt Weiss112321440.778 BOSJohn Farrell123191420.866 PITClint Hurdle94421360.691 ANAMike Scioscia82341160.707 TBAJoe Maddon73381110.658 BALBuck Showalter79291080.731 MIAMike Redmond78291070.729 LANDon Mattingly78281060.736 ARIKirk Gibson62411030.602 OAKBob Melvin75271020.735 ATLFredi Gonzalez6431950.674 SFNBruce Bochy6726930.72 MINRon Gardenhire5233850.612 SLNMike Matheny4522670.672 Managers that coached in 2013, but are no longer with that organization in 2014, have been removed from the chart. As you can see there is a relatively high variation when it comes to the amount of times each manager attempted to steal a base in 2013. Whether this is a statistic that has a high year-to-year correlation, I don’t know, and could be a topic of another article for the future....

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The Best Non-Closing Relievers: Top 137

Mar 20

The Best Non-Closing Relievers: Top 137

When I graduated high school, I went to Regis University in Denver, CO, for one year, because I thought I wanted to play baseball. After two weeks I not only knew that I did not want to play baseball, but that the title of “University” was a misnomer for what Regis really is: 13th grade. Don’t get me wrong, it may have been an ideal situation for some, but for me the lack of beautiful platinum blondes and recreational indulgences spelled out URGENT. My relocation to the University of Colorado at Boulder met all of the requisite needs that I had for an institute of higher learning, but my transition from Regis to CU enforces an important idea: context. If you took a girl of average appearance from the University of Colorado, G.O.A.P. mind you, and placed her next to the most attractive girl at Regis, most would mistake the girl from Regis for a soccer mom that has given birth to three children and whose last priority, right below procurement of coupons for oven degreaser, is her appearance. The girl from the CU did not change at all to have her value increased. She was just placed into a different context. The same can be true for elite relievers that are not closers in Fantasy Baseball. Unless relievers are placed in a certain context—used as the pitcher that throws the last inning of each game—they maintain significantly less value. Over the long run, a reliever will pitch the same whether or not it’s the seventh inning or the ninth. Like I’ve said before, I assume that because you’ve found this article on some far off corner of the Internet, and as a result have a more developed knowledge of baseball than people that consume baseball through ESPN, you’ll know the previous statement to be true. And because this statement is true, I thought we would look at the best non-closing relievers, as projected by the 2014 Steamer forecasts. The deeper the league, the more important these pitchers become. Because as the season goes on, closers will lose their jobs, get injured, or a combination of the two, and be replaced by the players on this list. There are some...

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Thinking About Expected Strikeout Rates: The Top “_____” xK% Leaders from 2013

Feb 09

Thinking About Expected Strikeout Rates: The Top “_____” xK% Leaders from 2013

(WARNING: THERE ARE GIFS AT THE END) Real estate, knick-knacks at a garage sale, and players, in the sense of professional sports, can be undervalued. For instance, in Boomerang: Travels in the New Third World, Michael Lewis interviews Kyle Bass, a hedge fund manager who made a fortune shorting subprime mortgage assets, who recently bought a million dollars worth of nickels. Yes, a million dollars of nickels. “The value of the metal in a nickels is worth six point eight cents,” Bass said. Bass went on to describe how difficult it is to obtain 20 million nickels, the process he had to go through with the bank from which he bought the nickels from, and the Federal Reserve agent who questioned his motives and asked, “Why do you want all these nickels?” To which he responded, “I just like nickels.” Baseball or Fantasy Baseball, for our purposes, is no different. Just like Kyle Bass’ exploitation of the market inefficiency in nickels, the best Fantasy Baseball players are the ones who can tell if a player will perform better or worse in the future relative to their current value. In that vain, this post will look at expected strikeout rates and the players in 2013 that posted the best xK%, so that we may be able to find undervalued assets that will win our leagues. For starters, why do we use K%? Let’s recap the stats that tell us about a pitchers’ strikeout ability. There’s your grandfather’s age old K that depends on innings pitched. K fails to tell us about the pitcher who may have only pitched a couple of games last year, so that doesn’t work. You have K/9, but then you have pitchers like Rich Hill. Hill’s the workaholic 70 hour work week father with a trophy wife and three kids who’s put his family into a 7,500 square feet house in Malibu, only to find out that his wife of 10 years has (for the last nine and a half years to be exact) been screwing the local yoga instructor with matted hair, a hemp poncho that would seem like it would be more suitable on Clint Eastwood in a Sergio Leone spaghetti western, and whose...

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200 Highest Increases in OBP & Shin-Soo Choo

Jan 29

200 Highest Increases in OBP & Shin-Soo Choo

I struggle to find topics to write about. Because, for me, if I don’t think a topic is interesting to write about, I don’t know how it could possibly be of interest for anyone to read. The past two weeks I’ve started and deleted several excel and word documents; I get to the point where I say to myself “this is garbage”, I take a shot of Fire Ball, and I start over. So I aimlessly wandered around the Internet in search of a topic until I saw a picture of Shin-Soo Choo. I checked out his Fangraphs page, scrolled to last season, and saw that he had a 50 point increase in his OBP from 2012 to 2013, which is convenient for him that this happened in a contract year. How often does a player improve his OBP this drastically? Choo increased his BB% by over five percent in one year (15.7% in 2013 and 10.6% in 2012), but should we expect this to happen again next year? Since 2003 there have been 123 players (with a minimum of 300 at bats in each season) that have improved their OBP as much or more than Shin-Soo Choo from one season to the next. There have also been 214 instances where players have improved their OBP by 39 points or more, but we’ll focus on the top 200 hundred to keep the number round. Highest Increases in OBP NameSeasonOBP DIFF Adrian Beltre20040.098 Casey Kotchman20110.098 Jason Giambi20050.098 Mike Napoli20110.098 Tony Womack20040.098 Josh Hamilton20100.096 Matt Kemp20110.089 Ray Durham20080.085 Cristian Guzman20080.085 Magglio Ordonez20070.084 Omar Infante20080.084 Travis Hafner20040.083 Brandon Phillips20060.082 Gaby Sanchez20130.082 Dustan Mohr20040.08 Hanley Ramirez20130.08 Barry Bonds20040.08 Carlos Gonzalez20090.08 Scott Spiezio20060.078 Alex Cora20040.077 Corey Patterson20100.077 Mike Lamb20060.077 Aubrey Huff20100.075 Brandon Inge20040.075 Justin Morneau20100.074 Alex Avila20110.073 Carlos Pena20070.073 Geovany Soto20100.072 Michael Cuddyer20130.072 Josh Bard20070.071 Justin Morneau20060.071 Mark Ellis20050.071 Alex Rios20120.069 Jose Bautista20110.069 Ryan Howard20060.069 Marlon Byrd20070.068 Aramis Ramirez20110.067 David Bell20040.067 Jeff Keppinger20120.067 Kelly Johnson20100.067 Bill Hall20050.066 Daric Barton20100.066 Jayson Werth20070.066 Michael Bourn20090.066 Milton Bradley20080.066 Yadier Molina20070.066 Luis Matos20050.065 Ramon Vazquez20080.065 Alberto Callaspo20110.064 Mark DeRosa20060.064 Dioner Navarro20080.063 Jose Reyes20110.063 Derrek Lee20050.062 Garrett Atkins20060.062 Ichiro Suzuki20040.062 J.D. Drew20040.062 Aaron Hill20120.061 Adrian Beltre20100.061 Julio Lugo20080.061 Ryan Theriot20080.061 Alex Gonzalez20050.06 Austin Jackson20120.06 Corey Patterson20060.06 Jason Bartlett20090.06 Placido...

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