Top 25 Base Stealer Board, Vol. 1

March 3, 2007

Anothr particular feature I intend on using when applicable are Top 25 Boards. Similarly to those of which appear weekly in college sports, these will rank the top 25 in their particular genre. The first genre I’ll take a look at it are prospective base stealers, who will currently be ranked in terms of last year’s totals, their speed scores, baserunning skills, and my own 2007 projections. I think its usefulness is pretty self-explanatory, and if I update the rankings as often as I intend, it not only gives you a good idea as to who can help you out in a particular department, but which player’s value regarding this exclusive niche have fluctuated the most in that timespan.

Without further adieu, the top 25 base stealers heading into 2007:

Player, Position, Team; Previous Ranking, SB total in ‘06, SB% in 06, SB Opportunity Rate, Projected SB total in ‘07

1) Jose Reyes, SS, NYM (1):
2006: 64 SB/79%/38.38%; 2007 Projection: 67 SB

2) Carl Crawford, LF, TAM (2):
2006: 58 SB/87%/36.02%; 2007 Projection: 54 SB

3) Ichiro Suzuki, RF, SEA (3):
45 SB/96%/18.43%; 2007 Projection: 47 SB

4) Hanley Ramirez, SS, FLA (4):
51 SB/77%/30.98%; 2007 Projection: 46 SB

5) Juan Pierre, CF, LAD (5):
58 SB/74%/35.45%; 2007 Projection: 49 SB

6) Dave Roberts, CF, SFO (6):
49 SB/89%/30.22%; 2007 Projection: 43 SB

7) Chone Figgins, UTIL, LAA (7):
52 SB/76%/32.54%; 2007 Projection: 46 SB

8) Ryan Freel, OF, CIN (8):
37 SB/77%/28.24%; 2007 Projection: 39 SB

9) Jimmy Rollins, SS, PHI (9):
36 SB/90%/25.00%; 2007 Projection: 41 SB

10) Corey Patterson, CF, BAL (10):
45 SB/83%/42.19%; 2007 Projection: 36 SB

11) Brian Roberts, 2B, BAL (11):
36 SB/84%/21.18%; 2007 Projection: 39 SB

12) Chris Duffy, CF, PIT (12):
26 SB/96%/28.72%; 2007 Projection: 36 SB

13) Derek Jeter, SS, NYY (13):
34SB/87%/14.66%; 2007 Projection: 29 SB

14) Alfonso Soriano, CF, CHC (14):
41SB/71%/29.29%; 2007 Projection: 31 SB

15) Felipe Lopez, SS, WAS (15):
44SB/79%/23.73%; 2007 Projection: 32 SB

16) Eric Byrnes, CF, ARZ (16):
25SB/89%/18.06%; 2007 Projection: 32 SB

17) Willy Taveras, CF, COL (17):
33SB/79%/24.00%; 2007 Projection: 36 SB

18) Bobby Abreu, RF, NYY (18):
30SB/83%/12.86%; 2007 Projection: 29 SB

19) Rafael Furcal, SS, LAD (19):
37SB/74%/20.41%; 2007 Projection: 32 SB

20) Scott Podsednik, CF, CWS (20):
40SB/58%/32.42%; 2007 Projection: 28 SB

21) Julio Lugo, 2B, BOS (21):
24SB/73%/22.92%; 2007 Projection: 31 SB

22) Rickie Weeks, 2B, MIL (22):
19SB/79%/20.17%; 2007 Projection: 27 SB

23) Grady Sizemore, CF, CLE (23):
22SB/79%/12.23%; 2007 Projection: 29 SB

24) Chris B. Young, CF, ARZ (24):
19SB*/73%*/16.35%*(includes AAA stats); 2007 Projection: 25 SB

25) Rocco Baldelli, CF, TB (25):
10SB/91%/10.78%; 2007 Projection: 22 SB

Notes:

Rankings aren’t determined on the total number of stolen bases expected alone, but a formula including total SBs as well as the player’s projected base-stealing efficiency (SB%).

Stolen Base Opportunity Rate:
((SBA)/(Hits – HR – Triples + Walks))

The SB Opportunity Rate stat is just an off-the-cuff measurement of how often a player will steal a base when given the opportunity. It measures the number of  stolen base attempts based on the number of singles, doubles, and walks a player accumulates (the number of times he reaches base, not including reaching base on error or despite making an out, in which the opportunity of a stolen base is present). It’s very much a work in progress, in that it doesn’t take into account whether or not runners are on base in front of him, the fact that a player is less likely to steal third after a double than second after a single, or other variables that would limit a player’s opportunities.  It merely provides a general outlook as to how opportunistic a player is when it comes to attempted to swipe a bag.

It also worth noting that the 2007 projections are not necessarily what I fully expect a player to do, but what I expect him to do if he stays healthy all season. Injuries are the hardest thing to predict in sports, and I rather focus on a player’s actual potential rather than health, which is clearly less predictable.