Posts Tagged ‘Justin Upton’

Video: Arizona Diamondbacks’ Hitters - 2012 Fantasy Baseball Preview (Wed 3/14/12)

Wednesday, March 14th, 2012

Hi everyone,

Since I’m a social media strategist by day and encourage everyone to make video part of their marketing effort, I’ve decided to take my own advice and finally enter the (late) 20th century.

First up - a fantasy baseball preview of the Arizona Diamondbacks’ hitters.  We’ll see how this experiment goes - if it’s well-received (or I just feel the need to stroke my ego five dozen times), we’ll continue with a fantasy baseball preview of each team’s hitters and (separately) pitchers.  I was hoping to keep the team hitter previews in the 2-3 minute range, but this first one is “a bit” longer than that.  I’ll see what I can do in the future to shorten that time (e.g. - talk faster, write out a script, review the Houston Astros, etc.)

In the meantime, enjoy this first one, and let me know what you think!

Until next time,

The Sherpa

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NL Hitters: Buy Low & Sell High Candidates (6/22/09)

Monday, June 22nd, 2009

This time of year many fantasy baseball team owners look to trades in an effort to improve their place in the standings.  Of course, everyone’s ideal is to trade away players who will perform worse over the remainder of the season than they have year-to-date, while simultaneously trading for players who will perform better over the remainder of the season than they have year-to-date.

How should you assess a player’s year-to-date value vs. his forecasted remainder-of season value?  Using Fantasy Baseball Sherpa’s In-season Updates tool, an owner can quantify both of these values in an effort to identify players who are currently undervalued and overvalued.  Fantasy Baseball Sherpa assigns a score of 1.00 Sherpa Points to the league leader in each category.  All other players are assigned a score for that category based on their result relative to the league leader’s result.

For example, if the league leader has hit 26 HRs year-to-date, then a player who has hit 13 HRs year-to-date would be assigned a scoreof 0.50 Sherpa Points.  For ratio categories (e.g.- AVG, ERA) a proxy statistic is used.  A player’s scores in each category can be added up to determine the player’s Total Sherpa Points.  A player’s maximum score is equal to the number of categories used (note:  this maximum score will be different for Hitters and Pitchers if your league uses a different number of categories for Hitters and Pitchers).

Here are 10 National League Hitters who are good buy-low candidates for a league using the standard 5 Hitting categories (AVG, Home Runs, RBI, Stolen Bases, & Runs Scored) based on stats through games of Sun 6/21/09:

  1. Alfonso Soriano, OF, ChC (2.79 Remainder-of-Season Total Sherpa Points - 1.50 Year-to-Date Total Sherpa Points = +1.29)
  2. Carlos Gonzalez, OF, Col (1.33 - 0.20 = +1.13)
  3. Jimmy Rollins, SS, Phi (2.18 - 1.06 =+1.12)
  4. Geovany Soto, C, ChC (1.55 - 0.50 = +1.05)
  5. Chris Coghlan, 3B/OF, Fla (1.81 - 0.77 = +1.04)
  6. Lance Berkman, 1B, Hou (2.53 - 1.55 = +0.98)
  7. Andrew McCutchen, OF, Pit (1.68 - 0.72 = +0.96)
  8. Ryan Ludwick, OF, StL (2.17 - 1.22 = +0.95)
  9. Brian Giles, OF, SD (1.04 - 0.10 = +0.94)
  10. Everth Cabrera, SS, SD (1.05 - 0.15 = +0.90)

Here are 10 National League Hitters who are good sell-high candidates for a league using the standard 5 Hitting categories based on stats through games of Sun 6/21/09:

  1. Orlando Hudson, 2B, LAD (1.41 - 2.18 = -0.77)
  2. Raul Ibanez, OF, Phi (2.49 - 3.21 = -0.72)
  3. Justin Upton, OF, Ari (2.00 - 2.65 = -0.65)
  4. Todd Helton, 1B, Col (1.80 - 2.26 = -0.46)
  5. Clint Barmes, 2B/SS, Col (1.50 - 1.90 = -0.40)
  6. Pablo Sandoval, C/1B/3B, SF (1.67 - 2.03 = -0.36)
  7. Gary Sheffield, OF, NYM (1.14 - 1.40 = -26)
  8. Mark Reynolds, 1B/3B, Ari (2.38 - 2.62 = -0.24)
  9. Nick Johnson, 1B, Was (1.59 - 1.82 = -0.23)
  10. Michael Bourn, OF, Hou (1.86 - 2.08 = -0.22)

Of course, there are a number of reasons why a player’s performance over the remainder of the season may vary significantly from his performance year-to-date, including normal variation in results, injuries, changes in roles, etc.  By attempting to quantify both a player’s year-to-date and remainder-of-season results, we can take at least some of the guesswork out of identifying buy-low and sell-high candidates.

Until next time,

The Sherpa

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