The Fantasy Baseball Sherpa

I recently concluded my wrap-up for the 2009 season, ranking the top Hitters and Pitchers for several widely used formats.  Just out of curiosity I checked my rankings for the 2008 season and compared them to the MVP and Cy Young award winners in both leagues.  The Fantasy Baseball Sherpa rankings correctly predicted both MVPs (Albert Pujols and Dustin Pedroia) and the NL Cy Young (Tim Lincecum).  The only discrepancy was with the AL CY Young, where Cliff Lee, who was second in the Fantasy Baseball Sherpa rankings, beat out Roy Halladay, who was first in the Fantasy Baseball Sherpa rankings.

Since the NL MVP race seems to be the only 2009 race with a clear winner, I thought it would be fun to use the 2009 Fantasy Baseball Sherpa rankings to predict the results of several of the awards which are in doubt.  Here are my predictions:

NL MVP - Albert Pujols

AL MVP - Joe Mauer

NL Cy Young - Tim Lincecum

AL Cy Young - Zack Greinke

NL Rookie of the Year - Chris Coghlan

AL Rookie of the Year - Andrew Bailey

Actually, I cheated a bit - I assumed that the MVP awards would go to hitters.  If we allow pitchers to be eligible for the MVP, which technically they are, then according to the Fantasy Baseball Sherpa rankings, Zack Greinke should win the AL MVP too.  I’ll be shocked if that actually happens, but if it does, remember that you read it here first!

I’ll do a follow-up post after all the awards are announced to see how accurately the rankings predicted the award winners.

In the meantime, enjoy the playoffs!

The Sherpa

Fantasy Baseball Sherpa

The Fantasy Baseball Sherpa’s Blog

@fantasy_sherpa on Twitter

The Fantasy Baseball Sherpa’s Facebook fan page

This is the fourth in a series of posts taking a look back at the top fantasy baseball performers for 2009. In this post I’ll review the top 10 Pitchers using a 5×5 NL-only format. For the purposes of this analysis I’m including Cliff Lee’s Phillies’ stats only (he ranked 47th based on 79.2 IP) and Jake Peavy’s Padres’ stats only (he ranked 59th based on 81.2 IP).

1. Tim Lincecum (Preseason rank was 3) - SF, SP

• Actual stats: 225.1 IP, 15 W, 0 SV, 2.48 ERA, 1.05 WHIP, 261 K, 3.46 Sherpa Pts (out of a max of 5.00)
• Projected stats: 220 IP, 12 W, 0 SV, 3.23 ERA, 1.19 WHIP, 259 K, 3.20 Sherpa Pts

2. Javier Vazquez (30) - ATL, SP

• Actual stats: 219.1 IP, 15 W, 0 SV, 2.87 ERA, 1.03 WHIP, 238 K, 3.21 Sherpa Pts
• Projected stats: 213 IP, 12 W, 0 SV, 4.65 ERA, 1.26 WHIP, 203 K, 1.62 Sherpa Pts

3. Chris Carpenter (190) - STL, SP

• Actual stats: 192.2 IP, 17 W, 0 SV, 2.24 ERA, 1.01 WHIP, 144 K, 3.25 Sherpa Pts
• Projected stats: 50 IP, 3 IP, 0 SV, 3.96 ERA, 1.36 WHIP, 27 K, 0.30 Sherpa Pts

4. Dan Haren (6) - ARI, SP

• Actual stats: 229.1 IP, 14 W, 0 SV, 3.14 ERA, 1.00 WHIP, 223 K, 3.20 Sherpa Pts
• Projected stats: 216 IP, 13 W, 0 SV, 3.63 ERA, 1.17 WHIP, 193 K, 2.76 Sherpa Pts

5. Adam Wainwright (10) - STL, SP

• Actual stats: 227 IP, 19 W, 0 SV, 2.58 ERA, 1.21 WHIP, 204 K, 2.98 Sherpa Pts
• Projected stats: 214 IP, 14 W, 0 SV, 3.53 ERA, 1.26 WHIP, 146 K, 2.36 Sherpa Pts

6. Josh Johnson (107) - FLA, SP

• Actual stats: 204.1 IP, 15 W, 0 SV, 3.08 ERA, 1.15 WHIP, 186 K, 2.62 Sherpa Pts
• Projected stats: 175 IP, 11 W, 0 SV, 3.61 ERA, 1.33 WHIP, 152 K, 1.78 Sherpa Pts

7. Matt Cain (22) - SF, SP

• Actual stats: 212.2 IP, 14 W, 0 SV, 2.88 ERA, 1.18 WHIP, 166 K, 2.58 Sherpa Pts
• Projected stats: 208 IP, 12 W, 0 SV, 3.94 ERA, 1.32 WHIP, 178 K, 1.52 Sherpa Pts

8. Jair Jurrjens (36) - ATL, SP

• Actual stats: 207 IP, 14 W, 0 SV, 2.61 ERA, 1.22 WHIP, 143 K, 2.50 Sherpa Pts
• Projected stats: 198 IP, 11 W, 0 SV, 4.59 ERA, 1.24 WHIP, 148 K, 1.35 Sherpa Pts

9. Wandy Rodriguez (69) - HOU, SP

• Actual stats: 199.2 IP, 14 W, 0 SV, 2.97 ERA, 1.23 WHIP, 190 K, 2.42 Sherpa Pts
• Projected stats: 151 IP, 9 W, 0 SV, 4.47 ERA, 1.37 WHIP, 133 K, 0.91 Sherpa Pts

10. Randy Wolf (105) - LAD, SP

• Actual stats: 209.1 IP, 11 W, 0 SV, 3.22 ERA, 1.08 WHIP, 158 K, 2.41 Sherpa Pts
• Projected stats: 157 IP, 9 W, 0 SV, 4.65 ERA, 1.46 WHIP, 135 K, 0.58 Sherpa Pts

Wandy Rodriguez and Randy Wolf were complete surprises to me - they both pitched ~50 innings more than I’d projected for them, but of course that’s primarily a result of the fact they pitched much better than I expected. Chris Carpenter is the classic boom-or-bust pitcher coming off an injury.  Before you run out and stock up on pitchers coming back from injuries in 2010, think of Ben Sheets, who represents the flip side of that coin.  In theory Strikeouts and WHIP should be easier to predict than ERA, Wins, and Saves (since the latter group are more a function of randomness and factors beyond a Pitcher’s direct control), but those predictions aren’t always the most accurate in practice. Dividing the Sherpa Pts by the IP gives a decent indicator of the overall accuracy of the initial projection compared to the actual results.

You’ll also note that only three of the Pitchers listed above were in my preseason top 10 list. Who were the other seven, and how did they fare? I’m glad you asked!

16. Johan Santana (1) - NYM, SP

• Actual stats: 166.2 IP, 13 W, 0 SV, 3.13 ERA, 1.21 WHIP, 146 K, 2.06 Sherpa Pts
• Projected stats: 225 IP, 14 W, 0 SV, 3.00 ERA, 1.09 WHIP, 218 K, 3.78 Sherpa Pts

59. Jake Peavy (2) - SD, SP

• Actual stats: 81.2 IP, 6 W, 0 SV, 3.97 ERA, 1.19 WHIP, 92 K, 0.88 Sherpa Pts
• Projected stats: 213 IP, 13 W, 0 SV, 3.17 ERA, 1.15 WHIP, 215 K, 3.26 Sherpa Pts

37. Cole Hamels (4) - PHI, SP

• Actual stats: 193.2 IP, 10 W, 0 SV, 4.32 ERA, 1.29 WHIP, 168 K, 1.31 Sherpa Pts
• Projected stats: 197 IP, 12 W, 0 SV, 3.56 ERA, 1.13 WHIP, 185 K, 2.97 Sherpa Pts

219. Brandon Webb (5) - ARI, SP

• Actual stats: 4 IP, 0 W, 0 SV, 13.50 ERA, 2.00 WHIP, 2 K, -0.12 Sherpa Pts
• Projected stats: 226 IP, 13 W, 0 SV, 3.38 ERA, 1.18 WHIP, 181 K, 2.91 Sherpa Pts

42. Rich Harden (7) - CHC, SP

• Actual stats: 141 IP, 9 W, 0 SV, 4.09 ERA, 1.34 WHIP, 171 K, 1.19 Sherpa Pts
• Projected stats: 143 IP, 10 W, 0 SV, 2.71 ERA, 1.11 WHIP, 161 K, 2.67 Sherpa Pts

39. Roy Oswalt (8) - HOU, SP

• Actual stats: 181.1 IP, 8 W, 0 SV, 4.12 ERA, 1.24 WHIP, 138 K, 1.23 Sherpa Pts
• Projected stats: 212 IP, 13 W, 0 SV, 3.48 ERA, 1.22 WHIP, 161 K, 2.54 Sherpa Pts

60. Carlos Marmol (9) - CHC, RP

• Actual stats: 73 IP, 2 W, 15 SV, 3.45 ERA, 1.48 WHIP, 91 K, 0.87 Sherpa Pts
• Projected stats: 81 IP, 4 W, 25 SV, 2.45 ERA, 0.99 WHIP, 107 K, 2.42 Sherpa Pts

We’re getting ready here in Sherpaville to develope our projections for the 2010 season, but I’ll continue this series with a look at the 2008 top 10 Hitters in an AL-only 5×5 format as time permits.

Until next time,

The Sherpa

Fantasy Baseball Sherpa

The Fantasy Baseball Sherpa’s Blog

@fantasy_sherpa on Twitter

The Fantasy Baseball Sherpa’s Facebook fan page

This entry is the second in a series of posts taking a look back at the top fantasy baseball performers for 2009. In this post I’ll continue with the top 10 Pitchers using a 5×5 mixed league format.

1. Zack Greinke (Preseason rank was 37) - KC, SP
   • Actual stats: 223.1 IP, 16 W, 0 SV, 2.06 ERA, 1.07 WHIP, 237 K, 3.55 Sherpa Pts (out of a max of 5.00)
   • Projected stats: 206 IP, 13 W, 0 SV, 3.93 ERA, 1.34 WHIP, 179 K, 1.82 Sherpa Pts
2. Tim Lincecum (4) - SF, SP
   • Actual stats: 225.1 IP, 15 W, 0 SV, 2.48 ERA, 1.05 WHIP, 261 K, 3.46 Sherpa Pts
   • Projected stats: 220 IP, 12 W, 0 SV, 3.23 ERA, 1.19 WHIP, 259 K, 3.20 Sherpa Pts
3. Javier Vazquez (45) - ATL, SP
   • Actual stats: 219.1 IP, 15 W, 0 SV, 2.87 ERA, 1.03 WHIP, 238 K, 3.21 Sherpa Pts
   • Projected stats: 213 IP, 12 W, 0 SV, 4.65 ERA, 1.26 WHIP, 203 K, 1.62 Sherpa Pts
4. Felix Hernandez (50) -SEA, SP
   • Actual stats: 232 IP, 18 W, 0 SV, 2.48 ERA, 1.15 WHIP, 211 K, 3.19 Sherpa Pts
   • Projected stats: 198 IP, 11 W, 0 SV, 3.95 ERA, 1.37 WHIP, 174 K, 1.57 Sherpa Pts
5. Dan Haren (7) - ARI, SP
   • Actual stats: 229.1 IP, 14 W, 0 SV, 3.14 ERA, 1.00 WHIP, 223 K, 3.10 Sherpa Pts
   • Projected stats: 216 IP, 13 W, 0 SV, 3.63 ERA, 1.17 WHIP, 193 K, 2.75 Sherpa Pts
6. Roy Halladay (3) - TOR, SP
   • Actual stats: 239 IP, 17 W, 0 SV, 2.79 ERA, 1.13 WHIP, 208 K, 3.09 Sherpa Pts
   • Projected stats: 240 IP, 14 W, 0 SV, 3.34 ERA, 1.12 WHIP, 173 K, 3.31 Sherpa Pts
7. Chris Carpenter (285) - STL, SP
   • Actual stats: 192.2 IP, 17 W, 0 SV, 2.24 ERA, 1.01 WHIP, 144 K, 3.06 Sherpa Pts
   • Projected stats: 50 IP, 3 W, 0 SV, 3.96 ERA, 1.36 WHIP, 27 K, 0.35 Sherpa Pts
8. Adam Wainwright (13) - STL, SP
   • Actual stats: 227 IP, 19 W, 0 SV, 2.58 ERA, 1.21 WHIP, 204 K, 2.98 Sherpa Pts
   • Projected stats: 214 IP, 14 W, 0 SV, 3.53 ERA, 1.26 WHIP, 146 K, 2.36 Sherpa Pts
9. CC Sabathia (2) - NYY, SP
   • Actual stats: 227.1 IP, 19 W, 0 SV, 3.21 ERA, 1.10 WHIP, 194 K, 2.94 Sherpa Pts
   • Projected stats: 235 IP, 16 W, 0 SV, 3.14 ERA, 1.13 WHIP, 219 K, 3.68 Sherpa Pts
10. Justin Verlander (73) - DET, SP
    • Actual stats: 232.1 IP, 18 W, 0 SV, 3.45 ERA, 1.18 WHIP, 264 K, 2.86 Sherpa Pts
    • Projected stats: 198 IP, 12 W, 0 SV, 4.55 ERA, 1.33 WHIP, 160 K, 1.29 Sherpa Pts

As was the case last year, the most interesting observation from my perspective is the relative difficulty in projecting W, ERA and WHIP vs. projecting Ks. Injuries obviously impact the actual rankings (see Johan Santana, Jake Peavy, and Brandon Webb below), but so do incorrect initial estimates regarding Innings Pitched. Dividing the Sherpa Pts by the IP gives a decent indicator of the overall accuracy of the initial projection compared to the actual results.

You’ll also note that only four of the Pitchers listed above were in my preseason top 10 list. Who were the other six, and how did they fare? I’m glad you asked!

27. Johan Santana (1) - NYM, SP

• Actual stats: 166.2 IP, 13 W, 0 SV, 3.13 ERA, 1.21 WHIP, 146 K, 1.92 Sherpa Pts
• Projected stats: 225 IP, 14 W, 0 SV, 3.00 ERA, 1.09 WHIP, 218 K, 3.72 Sherpa Pts

63. Jake Peavy (5) - SD, SP

• Actual stats: 101.2 IP, 9 W, 0 SV, 3.45 ERA, 1.12 WHIP, 110 K, 1.36 Sherpa Pts
• Projected stats: 213 IP, 13 W, 0 SV, 3.17 ERA, 1.15 WHIP, 215 K, 3.20 Sherpa Pts

402. Brandon Webb (6) - ARI, SP

• Actual stats: 4 IP, 0 W, 0 SV, 13.50 ERA, 2.00 WHIP, 2 K, -0.10 Sherpa Pts
• Projected stats: 226 IP, 13 W, 0 SV, 3.38 ERA, 1.18 WHIP, 181 K, 2.89 Sherpa Pts

65. Cole Hamels (9) - PHI, SP

• Actual stats: 193.2 IP, 10 W, 0 SV, 4.32 ERA, 1.29 WHIP, 168 K, 1.36 Sherpa Pts
• Projected stats: 197 IP, 12 W, 0 SV, 3.56 ERA, 1.13 WHIP, 185 K, 2.71 Sherpa Pts

74. Rich Harden (9) - CHC, SP

• Actual stats: 141 IP, 9 W, 0 SV, 4.09 ERA, 1.34 WHIP, 171 K, 1.22 Sherpa Pts
• Projected stats: 143 IP, 10 W, 0 SV, 2.71 ERA, 1.11 WHIP, 161 K, 2.62 Sherpa Pts

69. Roy Oswalt (10) - HOU, SP

• Actual stats: 181.1 IP, 8 W, 0 SV, 4.12 ERA, 1.24 WHIP, 138 K, 1.27 Sherpa Pts
• Projected stats: 212 IP, 13 W, 0 SV, 3.48 ERA, 1.22 WHIP, 161 K, 2.53 Sherpa Pts

We’ll soon be starting work here in Sherpaville on our projections for the 2010 season, but I’ll continue this series with a look at the 2008 top 10 Hitters in an NL-only 5×5 format as time permits.

Until next time,

The Sherpa

Fantasy Baseball Sherpa

The Fantasy Baseball Sherpa’s Blog

@fantasy_sherpa on Twitter

The Fantasy Baseball Sherpa’s Facebook fan page

With fantasy baseball playoffs starting this week in many Head-to-Head leagues, your selection of Starting Pitchers takes on added importance.  Sure, you’re going to start Zack Greinke, Roy Halladay, and Tim Lincecum (assuming he’s healthy) if you’re fortunate enough to have them on your team this season.  But what if you’re trying to decide between Bronson Arroyo and Kevin Correia for your last pitching spot?

 You could “go with your gut” and hope for the best (good luck with that).  You could look up each pitcher’s historical record (assuming he has one) against his upcoming opponent(s) and use that as a guide, ignoring the fact that a team’s roster is likely to experience significant turnover from season to season that will render historical results obsolete.  You could rely on the Remainder-of-Season Forecasts in the Fantasy Baseball Sherpa’s In-season Updates (shameless self-promotion).

While the third option is definitely better than the first two, it still leaves out one crucial component if you’re trying to make a short-term decision on which pitcher to start:  the quality of the pitcher’s opponent.  How can this be quantified?  The same way you would quantify the pitcher’s results - look at the historical data.

To assess a starting pitcher’s upcoming matchup(s) we want to use opponents’ success (or lack thereof) against a specific team.  For example, if I play in a league that uses the standard 5 pitching categories (Wins, Saves, Ks, ERA, WHIP), I’ll want to look at MLB Opponent Pitching Stats in each category that involves starting pitchers, so that eliminates Saves from my list.

I want to set my scoring system up so that the least desirable opponents have the highest scores, and the most desirable opponents have the lowest scores.  The least desirable opponent would have the highest number of Wins (equivalently, the lowest number of losses), the biggest difference between AB and Strikeouts (or, if you prefer, the lowest Strikeout per AB rate), the highest number of Runs Scored (using this as a proxy for ERA), and the highest number of Walks + Hits (using this as a proxy for WHIP).  Conversely, the most desirable opponent would have the lowest number of Wins (equivalently, the highest number of losses), the highest Strikeout per AB rate, the lowest number of Runs Scored, and the lowest number of Walks + Hits.

We can set up a scoring system for which the “best” team in each category receives a score of 1.00, and all other teams receive a score between 0 and 1 depending on the ratio of their result to the result of the best team in each category.  Thus, the maximum score is the number of pitching categories under consideration (4 in my example).  Add up a team’s results in each category to get its overall score; again, the lower the overall score, the more desirable the opponent.

Based on games through 9/12/09, here’s how the 30 MLB teams rank using the 4 categories in my example (with their accompanying score):

1. Pit 2.82 (max score is 4.00)
2. KC 2.90
3. Cin 2.94
4. SD 2.95
5. Was 2.96
6. SF 3.05
7. Sea 3.06
8. Ari 3.08
9. NYM 3.08
10. Hou 3.09
11. Bal 3.10
12. Oak 3.12
13. ChC 3.15
14. Mil 3.17
15. Cle 3.19
16. CWS 3.20
17. Det 3.20
18. Atl 3.25
19. Tor 3.25
20. TB 3.29
21. Min 3.30
22. StL 3.33
23. Fla 3.35
24. Phi 3.38
25. Col 3.41
26. Bos 3.48
27. LAD 3.50
28. Tex 3.56
29. LAA 3.62
30. NYY 3.80

You may wonder about the impact of September call-ups on these rankings.  Generally, the teams with the highest scores (i.e. - those closest to 4.00) are fighting for playoff berths and figure to play their everyday lineups at least until they’re locked into a playoff spot.  Those with the lowest scores are generally calling up more minor leaguers and “seeing what they’ve got”, so it may be even more advantageous than this chart would indicate to stream pitchers facing these lower-ranked teams.

The approach I’ve outlined above can take some of the guesswork out of selecting starting pitchers for your weekly lineups.  Of course, use your common sense - given the choice, I’d much rather start Roy Halladay against the Yankees than start Jeff Suppan against the Pirates.  However, if you’re deciding among several pitchers of similar quality, this analysis can be extremely useful.

Good luck in the homestretch!

The Sherpa

Fantasy Baseball Sherpa

The Fantasy Baseball Sherpa’s Blog

@fantasy_sherpa on Twitter

So, it’s Sunday night or Monday morning, and your league’s weekly lineup submissions are due.  You’re trying to decide among three starting pitchers (whether on your current roster or not) to fill your last pitching slot.  How should you go about it?

You could “go with your gut” and hope for the best (good luck with that).  You could look up each pitcher’s historical record (assuming he has one) against his upcoming opponent(s) and use that as a guide, ignoring the fact that a team’s roster is likely to experience significant turnover from season to season that will render historical results obsolete.  You could rely on the Remainder-of-Season Forecasts in the Fantasy Baseball Sherpa’s In-season Updates (shameless self-promotion).

While the third option is definitely better than the first two, it still leaves out one crucial component if you’re trying to make a short-term decision on which pitcher to start:  the quality of the pitcher’s opponent.  How can this be quantified?  The same way you would quantify the pitcher’s results - look at the historical data.

To assess a starting pitcher’s upcoming matchup(s) we want to use opponents’ success (or lack thereof) against a specific team.  For example, if I play in a league that uses the standard 5 pitching categories (Wins, Saves, Ks, ERA, WHIP), I’ll want to look at MLB Opponent Pitching Stats in each category that involves starting pitchers, so that eliminates Saves from my list.

I want to set my scoring system up so that the least desirable opponents have the highest scores, and the most desirable opponents have the lowest scores.  The least desirable opponent would have the highest number of Wins (equivalently, the lowest number of losses), the biggest difference between AB and Strikeouts (or, if you prefer, the lowest Strikeout per AB rate), the highest number of Runs Scored (using this as a proxy for ERA), and the highest number of Walks + Hits (using this as a proxy for WHIP).  Conversely, the most desirable opponent would have the lowest number of Wins (equivalently, the highest number of losses), the highest Strikeout per AB rate, the lowest number of Runs Scored, and the lowest number of Walks + Hits.

We can set up a scoring system for which the “best” team in each category receives a score of 1.00, and all other teams receive a score between 0 and 1 depending on the ratio of their result to the result of the best team in each category.  Thus, the maximum score is the number of pitching categories under consideration (4 in my example).  Add up a team’s results in each category to get its overall score; again, the lower the overall score, the more desirable the opponent.

Based on games through 8/8/09, here’s how the 30 MLB teams rank using the 4 categories in my example (with their accompanying score):

1. Cin 3.11 (max score is 4.00)
2. SD 3.12
3. KC 3.14
4. Pit 3.15
5. Was 3.32
6. Sea 3.33
7. Oak 3.34
8. SF 3.34
9. Hou 3.35
10. Bal 3.38
11. NYM 3.39
12. Ari 3.39
13. ChC 3.40
14. Det 3.43
15. Mil 3.45
16. Fla 3.46
17. Cle 3.47
18. Tex 3.47
19. CWS 3.49
20. Atl 3.52
21. Tor 3.53
22. StL 3.53
23. Col 3.54
24. Min 3.55
25. Phi 3.64
26. Bos 3.68
27. TB 3.69
28. LAD 3.85
29. LAA 3.86
30. NYY 3.98

Several notable changes since the last rankings update (on 7/5/09):  Washington, Oakland, Arizona, and the Cubs are among the teams whose offenses have improved in the last month; Cincinnati, Pittsburgh, and Toronto are among the teams whose offenses have regressed during that same time period.  Obviously, it’s important to take a quick glance at a team’s current overall health compared to its health season-to-date.  Tracking the standings over time (weekly or bi-weekly updates are best) will give you a good sense of whether a team’s offenses is improving, treading water, or getting worse.

The approach I’ve outlined above can take some of the guesswork out of selecting starting pitchers for your weekly lineups.  Of course, use your common sense - given the choice, I’d much rather start Tim Lincecum against the Dodgers than start Livan Hernandez against the Reds.  However, if you’re deciding among several pitchers of similar quality, this analysis can be extremely useful.

Until next time!

The Sherpa

Fantasy Baseball Sherpa

The Fantasy Baseball Sherpa’s Blog

@fantasy_sherpa on Twitter

Hi everyone,

Here are the forecasted Top 10 performers for the rest of the season for a Mixed League 5×5 format.  The leader in each category is given 1.00 Sherpa Points; all other players’ scores in that category are based on their results relative to the category leader’s (e.g. - if the forecast for the league-leader is 62 RBI, then a player with a forecast of 31 RBI would be given a score of 0.50 Sherpa Points).  The maximum Total Sherpa Points is equal to the number of categories (i.e. - 5.00).

1. Albert Pujols (StL, 1B) - 246 AB, 22 HR, 62 RBI, 5 SB, .333 AVG, 53 R, 3.80 Total Sherpa Points
2. Dan Haren (Ari, SP) - 97 IP, 5 W, 0 SV, 2.69 ERA, 0.96 WHIP, 92 K, 3.48 Total Sherpa Points
3. Chase Utley (Phi, 2B) - 289 AB, 17 HR, 54 RBI, 8 SB, .311 AVG, 57 R, 3.46 Total Sherpa Points
4. Tim Lincecum (SF, SP) - 100 IP, 5 W, 0 SV, 2.70 ERA, 1.11 WHIP, 117 K, 3.36 Total Sherpa Points
5. Hanley Ramirez (Fla, SS) - 273 AB, 14 HR, 47 RBI, 11 SB, .326 AVG, 49 R, 3.32 Total Sherpa Points
6. Matt Kemp (LAD, OF) - 304 AB, 10 HR, 46 RBI, 17 sB, .313 AVG, 49 R, 3.22 Total Sherpa Points
7. Carl Crawford (TB, OF) - 302 AB, 7 HR, 36 RBI, 30 SB, .301 AVG, 48 R, 3.19 Total Sherpa Points
8. Ryan Braun (Mil, OF) - 292 AB, 16 HR, 51 RBI, 8 SB, .301 AVG, 52 R, 3.17 Total Sherpa Points
9. Alex Rodriguez (NYY, 3B) - 256 AB, 20 HR, 60 RBI, 7 SB, .281 AVG, 51 R, 3.17 Total Sherpa Points
10. Roy Halladay (Tor, SP) - 144 IP, 9 W, 0 SV, 3.00 ERA, 1.08 WHIP, 112 K, 3.10 Total Sherpa Points

If you’re interested in more details, here’s a description of our In-season Updates to Player Projections & Rankings.  These are the only rankings in the industry that are updated daily throughout the season - our Remainder-of-Season rankings reflect injuries, minor league call-ups, and role changes (e.g.- new Closers)! If you’d like to see the top performers by position, change the scoring categories, or change the league type, here’s a demo of our In-season Updates to Player Projections & Rankings.

Enjoy!

The Sherpa

FantasyBaseballSherpa.com

Fantasy Baseball Sherpa’s blog

@fantasy_sherpa on Twitter

Hi everyone,

Here are the Top 10 performers through Week 14 for a Mixed League 5×5 format.  The leader in each category is given 1.00 Sherpa Points; all other players’ scores in that category are based on their results relative to the category leader’s (e.g. - if the league-leader has hit 32 HR, then a player with 24 HR would be given a score of 0.75 Sherpa Points).  The maximum Total Sherpa Points is equal to the number of categories (i.e. - 5.00).

1. Albert Pujols (StL, 1B) - 307 AB, 32 HR, 87 RBI, 10 SB, .332 AVG, 73 R, 3.83 Total Sherpa Points
2. Dan Haren (Ari, SP) - 130.0 IP, 9 W, 0 SV, 2.01 ERA, 0.81 WHIP, 129 K, 3.69 Total Sherpa Points
3. Tim Lincecum (SF, SP) - 127.2 IP, 10 W, 0 SV, 2.33 ERA, 1.05 WHIP, 149 K, 3.31 Total Sherpa Points
4. Zack Greinke (KC, SP) - 127.1 IP, 10 W, 0 SV, 2.12 ERA, 1.08 WHIP, 129 K, 3.22 Total Sherpa Points
5. Carl Crawford (TB, OF) - 353 AB, 8 HR, 39 RBI, 44 SB, .309 AVG, 58 R, 2.94 Total Sherpa Points
6. Hanley Ramirez (Fla, SS) - 312 AB, 14 HR, 61 RBI, 13 SB, .349 AVG, 53 R, 2.94 Total Sherpa Points
7. Prince Fielder (Mil, 1B) - 308 AB, 22 HR, 78 RBI, 1 SB, .315 AVG, 58 R, 2.85 Total Sherpa Points
8. Chase Utley (Phi, 2B) - 307 AB, 20 HR, 61 RBI, 9 SB, .313 AVG, 62 R, 2.81 Total Sherpa Points
9. Felix Hernandez (Sea, SP) - 124.2 IP, 9 W, 0 SV, 2.53 ERA, 1.14 WHIP, 121 K, 2.76 Total Sherpa Points
10. Justin Morneau (Min, 1B) - 334 AB, 21 HR, 70 RBI, 0 SB, .311 AVG, 59 R, 2.72 Total Sherpa Points

If you’re interested in more details, here’s a description of our In-season Updates to Player Projections & Rankings.  These are the only rankings in the industry that are updated daily throughout the season - our Remainder-of-Season rankings reflect injuries, minor league call-ups, and role changes (e.g.- new Closers)! If you’d like to see the top performers by position, change the scoring categories, or change the league type, here’s a demo of our In-season Updates to Player Projections & Rankings.

Enjoy!

The Sherpa

FantasyBaseballSherpa.com

Fantasy Baseball Sherpa’s blog

@fantasy_sherpa on Twitter

Hi everyone,

Here are the forecasted Top 10 performers for the rest of the season for an NL-only 5×5 format.  The leader in each category is given 1.00 Sherpa Points; all other players’ scores in that category are based on their results relative to the category leader’s (e.g. - if the forecast for the league-leader is 62 RBI, then a player with a forecast of 31 RBI would be given a score of 0.50 Sherpa Points).  The maximum Total Sherpa Points is equal to the number of categories (i.e. - 5.00).

1. Albert Pujols (StL, 1B) - 246 AB, 22 HR, 62 RBI, 5 SB, .333 AVG, 53 R, 4.15 Total Sherpa Points
2. Chase Utley (Phi, 2B) - 289 AB, 17 HR, 54 RBI, 8 SB, .311 AVG, 57 R, 3.80 Total Sherpa Points
3. Hanley Ramirez (Fla, SS) - 273 AB, 14 HR, 47 RBI, 11 SB, .326 AVG, 49 R, 3.74 Total Sherpa Points
4. Matt Kemp (LAD, OF) - 304 AB, 10 HR, 46 RBI, 17 SB, .313 AVG, 49 R, 3.66 Total Sherpa Points
5. Dan Haren (Ari, SP) - 97 IP, 5 W, 0 SV, 2.69 ERA, 0.96 WHIP, 92 K, 3.48 Total Sherpa Points
6. Ryan Braun (Mil, OF) - 292 AB, 16 HR, 51 RBI, 8 SB, .301 AVG, 52 R, 3.47 Total Sherpa Points
7. David Wright (NYM, 3B) - 273 AB, 8 HR, 44 RBI, 14 SB, .319 AVG, 48 R, 3.40 Total Sherpa Points
8. Tim Lincecum (SF, SP) - 100 IP, 5 W, 0 SV, 2.70 ERA, 1.11 WHIP, 117 K, 3.36 Total Sherpa Points
9. Prince Fielder (Mil, 1B) - 267 AB, 18 HR, 58 RBI, 1 SB, .296 AVG, 47 R, 3.14 Total Sherpa Points
10. Shane Victorino (Phi, OF) - 303 AB, 6 HR, 34 RBI, 15 SB, .300 AVG, 54 R, 3.08 Total Sherpa Points

If you’re interested in more details, here’s a description of our In-season Updates to Player Projections & Rankings.  These are the only rankings in the industry that are updated daily throughout the season - our Remainder-of-Season rankings reflect injuries, minor league call-ups, and role changes (e.g.- new Closers)! If you’d like to see the top performers by position, change the scoring categories, or change the league type, here’s a demo of our In-season Updates to Player Projections & Rankings.

Enjoy!

The Sherpa

FantasyBaseballSherpa.com

Fantasy Baseball Sherpa’s blog

@fantasy_sherpa on Twitter

Hi everyone,

Here are the Top 10 performers through Week 14 for an NL-only 5×5 format.  The leader in each category is given 1.00 Sherpa Points; all other players’ scores in that category are based on their results relative to the category leader’s (e.g. - if the league-leader has hit 32 HR, then a player with 16 HR would be given a score of 0.50 Sherpa Points).  The maximum Total Sherpa Points is equal to the number of categories (i.e. - 5.00).

1. Albert Pujols (StL, 1B) - 307 AB, 32 HR, 87 RBI, 10 SB, .332 AVG, 73 R, 4.10 Total Sherpa Points
2. Dan Haren (Ari, SP) - 130.0 IP, 9 W, 0 SV, 2.01 ERA, 0.81 WHIP, 129 K, 3.69 Total Sherpa Points
3. Tim Lincecum (SF, SP) - 127.2 IP, 10 W, 0 SV, 2.33 ERA, 1.05 WHIP, 149 K, 3.30 Total Sherpa Points
4. Hanley Ramirez (Fla, SS) - 312 AB, 14 HR, 61 RBI, 13 SB, .349 AVG, 53 R, 3.28 Total Sherpa Points
5. Chase Utley (Phi, 2B) - 307 AB, 20 HR, 61 RBI, 9 SB, .313 AVG, 62 R, 3.03 Total Sherpa Points
6. Prince Fielder (Mil, 1B) - 308 AB, 22 HR, 78 RBI, 1 SB, .315 AVG, 58 R, 3.01 Total Sherpa Points
7. Matt Kemp (LAD, OF) - 325 AB, 11 HR, 50 RBI, 19 SB, .320 AVG, 48 R, 2.85 Total Sherpa Points
8. Ryan Braun (Mil, OF) - 332 AB, 16 HR, 58 RBI, 7 SB, .310 AVG, 61 R, 2.82 Total Sherpa Points
9. David Wright (NYM, 3B) - 327 AB, 5 HR, 44 RBI, 20 SB, .324 AVG, 56 R, 2.82 Total Sherpa Points
10. Raul Ibanez (Phi, OF) - 259 AB, 22 HR, 60 RBI, 4 SB, .309 AVG, 53 R, 2.69 Total Sherpa Points

If you’re interested in more details, here’s a description of our In-season Updates to Player Projections & Rankings.  These are the only rankings in the industry that are updated daily throughout the season - our Remainder-of-Season rankings reflect injuries, minor league call-ups, and role changes (e.g.- new Closers)! If you’d like to see the top performers by position, change the scoring categories, or change the league type, here’s a demo of our In-season Updates to Player Projections & Rankings.

Enjoy!

The Sherpa

FantasyBaseballSherpa.com

Fantasy Baseball Sherpa’s blog

@fantasy_sherpa on Twitter

So, it’s Sunday night or Monday morning, and your league’s weekly lineup submissions are due.  You’re trying to decide among three starting pitchers (whether on your current roster or not) to fill your last pitching slot.  How should you go about it?

You could “go with your gut” and hope for the best (good luck with that).  You could look up each pitcher’s historical record (assuming he has one) against his upcoming opponent(s) and use that as a guide, ignoring the fact that a team’s roster is likely to experience significant turnover from season to season that will render historical results obsolete.  You could rely on the Remainder-of-Season Forecasts in the Fantasy Baseball Sherpa’s In-season Updates (shameless self-promotion).

While the third option is definitely better than the first two, it still leaves out one crucial component if you’re trying to make a short-term decision on which pitcher to start:  the quality of the pitcher’s opponent.  How can this be quantified?  The same way you would quantify the pitcher’s results - look at the historical data.

To assess a starting pitcher’s upcoming matchup(s) we want to use opponents’ success (or lack thereof) against a specific team.  For example, if I play in a league that uses the standard 5 pitching categories (Wins, Saves, Ks, ERA, WHIP), I’ll want to look at MLB Opponent Pitching Stats in each category that involves starting pitchers, so that eliminates Saves from my list.

I want to set my scoring system up so that the least desirable opponents have the highest scores, and the most desirable opponents have the lowest scores.  The least desirable opponent would have the highest number of Wins (equivalently, the lowest number of losses), the biggest difference between AB and Strikeouts (or, if you prefer, the lowest Strikeout per AB rate), the highest number of Runs Scored (using this as a proxy for ERA), and the highest number of Walks + Hits (using this as a proxy for WHIP).  Conversely, the most desirable opponent would have the lowest number of Wins (equivalently, the highest number of losses), the highest Strikeout per AB rate, the lowest number of Runs Scored, and the lowest number of Walks + Hits.

We can set up a scoring system for which the “best” team in each category receives a score of 1.00, and all other teams receive a score between 0 and 1 depending on the ratio of their result to the result of the best team in each category.  Thus, the maximum score is the number of pitching categories under consideration (4 in my example).  Add up a team’s results in each category to get its overall score; again, the lower the overall score, the more desirable the opponent.

Based on games through 7/3/09, here’s how the 30 MLB teams rank using the 4 categories in my example (with their accompanying score):

1. Was 2.96 (max score is 4.00)
2. SD 3.00
3. KC 3.01
4. Oak 3.07
5. Ari 3.11
6. ChC 3.16
7. Cin 3.21
8. SF 3.23
9. Sea 3.23
10. Hou 3.24
11. Pit 3.29
12. Atl 3.30
13. Tex 3.36
14. CWS 3.37
15. Bal 3.38
16. Mil 3.39
17. Fla 3.40
18. NYM 3.40
19. Cle 3.41
20. StL 3.43
21. Col 3.44
22. Det 3.44
23. Min 3.53
24. LAA 3.53
25. Phi 3.58
26. Tor 3.65
27. Bos 3.71
28. TB 3.72
29. LAD 3.73
30. NYY 3.77

No significant changes since the last rankings update (on 6/21/09), but it’s important to take a quick glance at a team’s current overall health compared to its health season-to-date.  Tracking the standings over time (weekly or bi-weekly updates are best) will give you a good sense of whether a team’s offenses is improving, treading water, or getting worse.

The approach I’ve outlined above can take some of the guesswork out of selecting starting pitchers for your weekly lineups.  Of course, use your common sense - given the choice, I’d much rather start Tim Lincecum against the Dodgers than start Livan Hernandez or Russ Ortiz against the Nationals.  However, if you’re deciding among several pitchers of similar quality, this analysis can be extremely useful.

Until next time!

The Sherpa

Fantasy Baseball Sherpa

The Fantasy Baseball Sherpa’s Blog

@fantasy_sherpa on Twitter