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Winter of Sabermetrics

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They are also third in the league in SB. Their success rate is only marginal (67%) though and is 9th in the league.

Podsednick was 50/59 (84.7%) to start the season. He finished the season 9/23 (39.1%). That will skew the numbers as well.

Yeah, I did remember that when I was looking at the White sox stats earlier in the season, their SB% was better. I was surprised to see that were 9th in the league by the end of the season.

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IN 129 games, Podsednik only scored 80 runs on 147 hits and 47 walks....so whoever was hitting behind him wasn't getting him in.

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Detroit Tigers Runs Created Analysis

How many runs does a player contribute to his team’s offense? One way to answer this question is the statistic “runs created”. Runs created (RC) is not the most popular sabermetric measure today but it was one of the statistics which made Bill James (the God father of modern sabermetrics) famous. There are many versions of the statistic but the basic formula is always

(A times B) divided by C

where A=times reached base, B=total bases and C=plate appearances

I used the version published in The Hardball Times (www.hardballtimes.com). It is the most complex of all the RC formulas and includes the impact of every offensive stat available. This includes HBP, stolen bases, caught stealing, sac flies, sac bunts, strikeouts and double plays. It even includes hitting with runners in scoring position.

The specifics of the formula can be found at http://en.wikipedia.org/wiki/Runs_created

The version found in The Hardball Times is also adjusted for ballpark effect. In the case of the Tigers, this means, the runs created is adjusted upward a little for each player to allow for fairer comparisons with players who play in more hitter friendly parks.

Does RC work? If you add up the individual RC (before making ballpark adjustments) for players on a team, it generally comes pretty close to the total runs scored for that team. This is an indication that it is doing a fairly good job of measuring what it is intended to measure: how much each player contributes to his team runs scored total.

Another statistic is runs created per game or runs created per 27 outs (RC/G). Theoretically, this statistics tells you how many runs scored your team would score per game if you had the same player bat in all line-up positions. For example, Brandon Inge had an RC/G of 5.2 so you would theoretically expect a team of 9 Brandon Inges to score 5.2 runs per game. That’s not a very practical or realistic use of the statistic. However, it’s a good statistic for comparing the offensive contribution of different players.

A player like Inge who played a lot of games will have more runs created than a player like Chris Shelton who came up at midseason. On the other hand Shelton hit better when he did play so he’ll have a higher runs created per game. Both stats are useful depending on the question being asked.

The Table below ranks the Tigers in RC.


Player RC Lg Rank
Inge 87 32
Monroe 82 38
Shelton 70 61
White 65 68
Polanco 64 70
Young 64 70
Ordonez 54 98
Rodriguez 47 111
Guillen 42 116
Pena 42 116
Infante 41 122
Logan 35 127
Granderson 27 142
Wilson 14 175
Thames 11 189
Martinez 7 205
McDonald 6 214
Smith 4 226
Giarratano 3 240
Gomez 1 265
Hooper 1 265
Higginson 0 291

The table shows that Inge contributed more runs (87) to the offense than any other player on the team. He was followed by Craig Monroe (82), Shelton (70), Rondell White (65), Placido Polanco (64) and Dmitri Young (64). The final column on the table shows where players ranked within the American League. No Tigers finished in the top 30 which helps to explain why they had trouble scoring runs this year.

The next table ranks the Tigers in RC/G


Player RC/G Lg Rank
Polanco 7.6 13
Shelton 6.9 18
Ordonez 6.9 19
White 6.8 23
Granderson 6.3 ***
Pena 5.7 51
Monroe 5.4 60
Inge 5.2 67
Young 5 80
Guillen 5 84
Martinez 4.9 ***
Hooper 4.3 ***
Logan 3.9 118
Rodriguez 3.5 127
Infante 3.5 129
Thames 3.4 ***
Wilson 3.1 ***
McDonald 3.1 ***
Gomez 2.7 ***
Smith 2.2 ***
Giarratano 2.1 ***
Higginson 0 ***

This table looks a lot different because the players who contributed the most over the course of the full season were not the best hitters. Polanco tops the list at 7.6. Would a team of 9 Polancos score 7.6 runs per game? If the 9 Polancos performed exactly the same as the one Polanco did, then the answer would be yes. That’s a fun way to interpret the stat but it’s impossible to know what would really happen with such a line-up. Whatever way you look at it, Polanco was good ! He was followed by Shelton (6.9), Ordonez (6.9), White (6.8) and Granderson (6.3). Note that Monroe and Inge are much lower on this list (7th and 8th respectively).

The League rank column only has a value for players with 295 or more late appearances. I was going to use a 300 limit but Pena missed by just 5 PA so I decided on the 295 limit. Only 133 AL players reached 295 PA. For this measure, the Tigers did have 4 players in the top 30. This might bode well for 2006.

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Monroe dropping from the 1st list to the 2nd list is going to cause some commotion among those who believe strictly in RBIs. But if you go by the 2nd list, it validates hitting Monroe lower in the lineup. The 2nd list makes sense to me because, by and large, the better Tiger hitters in my mind are higher on the list. The one player that really seems out of place is Pudge, even though I know his lack of BBs is going to hamper him.

Keep it up T337. I'm looking forward to learning more sabermetrics.

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Monroe dropping from the 1st list to the 2nd list is going to cause some commotion among those who believe strictly in RBIs. But if you go by the 2nd list, it validates hitting Monroe lower in the lineup. The 2nd list makes sense to me because, by and large, the better Tiger hitters in my mind are higher on the list. The one player that really seems out of place is Pudge, even though I know his lack of BBs is going to hamper him.

Keep it up T337. I'm looking forward to learning more sabermetrics.

If you use OPS instead of runs created, he would fair a little better (ranked 90 out of 133 qualifiers). Runs created is a better measure though (other than being too complicated to compute on a regular basis). Contrary to popular belief, OPS does not place enough weight on walks. Hits are counted twice in the OPS formula (OBP and slugging) but walks are only counted once (OBP). In the runs created formula, both hits and walks are counted in both the on base and total base parts of the formula as they should be.

Rodriguez was 126/133 in OBP and 61/133 in slugging. His power was not that big of a problem. He couldn't get on base at all though and that killed him and the Tigers. Also, his .213 BA with RISP (125/133) and his 19 GIDP (124/133) dragged him down further. He didn't steal many bases or get sac flies either. He really didn't do many things to help the team score runs.

I think his low BA w RISP was just bad luck so he should be able to fix that next year. He absolutely needs to get on base to be a productive offensive player though.

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Earlier, I looked at how Tiger players ranked in runs created (RC) and runs created per game (RC/G) among the 133 players in the American League with 295 or more plate appearances (PA). Now, I break it down by position starting with the catchers.


Rank Name Team RC/G RC OPS
1 Martinez CLE 6.8 95 .853
2 Mauer MIN 6.4 81 .783
3 Varitek BOS 6.2 78 .856
4 Lopez BAL 5.7 60 .780
5 Posada NYA 5.5 71 .782
6 Molina LAA 5.2 56 .782
7 Zaun TOR 5.2 63 .729
8 Kendall OAK 4.9 79 .666
9 Barajas TEX 4.7 53 .771
10 Hall TB 4.4 50 .683
11 Pierzynski CHA 4.2 53 .728
12 Buck KC 3.8 43 .676
13 Rodriguez DET 3.5 47 .735

The top run producers in the league were Victor Martinez, Joe Mauer and Jason Varitek.

Of the 13 qualifying catchers, Ivan Rodriguez was last. This is probably a surprise to those who are accustomed to OPS (On base percentage plus slugging percentage).

If I had used OPS instead of RC/G, Rodriguez would have ranked 8th.

Why the discrepancy? Both OPS and RC/G are a function of getting on base and advancing runners and players with high OPS typically also have high RC/G. However, walks are not weighted in OPS as much as they should be. In calculation of OPS, walks are included in the on base part of the formula but not the base advancement part of the formula. In the RC/G calculation, walks are included in both parts of the formula. They are not counted as much as singles because singles can be better than walks but they are counted and they should be.

So, Rodriguez is not getting penalized enough for his extreme lack of walks in the OPS formula. But why would John Buck who had about the same OBP and significantly lower slugging percentage have more RC/G than Rodriguez? It’s because RC/G includes a lot of the “little” things which are not accounted for by OPS. Buck had 3 more sac flies than Rodriguez, grounded into 10 fewer double plays and had a better batting average with runners in scoring position (.250 versus .213). When you aren’t hitting much (as those two weren’t), those little things become important and have more influence on the RC/G stat.

So which one is better? I like runs created better because it weights walks more correctly and it includes more game factors. Some might argue that hitting with men in scoring position is not a real skill and is largely a function of luck. However, luck or not, it does help the team score runs and there is value to including it in a stat which measures overall past production. RC/G is a good stat but it’s not perfect. It’s a reasonably good summary stat but summary stats do not measure specific skills and can mask important characteristics of players.

For example, Rodriguez had a really difficult time getting on base this year and frankly didn’t do a lot of things to help the Tigers score runs. He really needs to improve his OBP significantly, stop hitting into DP so much and hit better with men on base (I think that it was just bad luck but he still didn’t do it). However, he was 6th in slugging so he did do ok in the base advancement part of the formula. Hopefully, he keeps that up next year while improving other parts of his offensive game.

Later in the week, I’ll look at some other positions.

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This is very thought provoking Lee. The low rating of Pudge is no surprise, and though RBI is a quaint statistic, the RC/G formula helps explain how he drove in so few runs. It's just hard to believe that this man could have only driven in only 50 runs all season but this goes a long way to explaining it. Thanks. Please keep posting on this thread.

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Yesterday, I ranked American League catchers by runs created per game (RC/G). Today, I present the rest of the positions with comments.

First basemen


Rank Player Team RC/G RC
1 Hafner CLE 9.7 122
2 Giambi NYA 9.1 103
3 Ortiz BOS 8.7 136
4 Teixeira TEX 8.5 142
5 Sexson SEA 8 122
6 Shelton DET 6.9 70
7 Konerko CHA 6.8 103
8 Sweeney KC 6.6 81
9 Stairs KC 6.6 70
10 LeCroy MIN 6 50
11 Palmeiro BAL 5.8 59
12 Pena DET 5.7 42
13 Johnson OAK 5.6 56
14 Hillenbrand TOR 5.5 86
15 Hinske TOR 5.3 69
16 Lee TB 5.1 55
17 Erstad LAA 5 82
18 Young DET 5 64
19 Broussard CLE 5 64
20 Hatteberg OAK 4.8 61
21 Millar BOS 4.8 58
22 Martinez NYA 4.8 41
23 Morneau MIN 4.4 61

Chris Shelton finished 6th among first basemen creating 6.9 runs per game. Remember from yesterday’s discussion that this means that a line-up of nine Sheltons would have theoretically scored 6.9 runs per game. I’d be pretty happy if this one Shelton could produce at the same level for a full season (6.9). Roller coaster Carlos Pena (5.7) finished in the middle of the pack after a horrid start, a trip to Toledo and a strong finish. And yes, runs created does penalize a player for strikeouts. Dmitri Young (5.0) finished near the bottom of the list. Young appears to be on the decline so I hope they manage to move him somehow this off season. Despite his tendency for terrible slumps, I’d rather see Pena get at bats than Young.

Second basemen


Rank Player Team RC/G RC
1 Roberts BAL 8 114
2 Polanco DET 7.6 64
3 Ellis OAK 7.1 78
4 Kennedy LAA 6 65
5 Cantu TB 6 95
6 Belliard CLE 5.3 75
7 Iguchi CHA 5.2 72
8 Soriano TEX 5.2 89
9 Green TB 4.6 42
10 Hudson TOR 4.6 57
11 Cano NYA 4.4 59
12 Gotay KC 3.9 31
13 Boone SEA 3.8 29
14 Infante DET 3.5 41
15 Bellhorn BOS 3.4 28
16 Punto MIN 3.3 36

Placido Polanco (7.6) was outstanding in a half season for the Tigers. Polanco had a career year this year and I’d be surprised if he did as well next year. He’s always been an underrated player though so there’s no reason why he shouldn’t be among the leaders at his position again next year. Omar Infante had a bad year after an apparent break out year last year. He’s still only 23 years old but will have a hard time getting a regular job back anytime soon.

Third basemen


Rank Player Team RC/G RC
1 Rodriguez NYA 9.1 138
2 Mueller BOS 6 81
3 Mora BAL 6 94
4 Figgins LAA 5.8 99
5 Chavez OAK 5.7 96
6 Inge DET 5.2 87
7 Crede CHA 5 60
8 Hill TOR 5 48
9 Blalock TEX 4.7 83
10 Beltre SEA 4.7 79
11 Teahen KC 4.2 52
12 Gonzalez TB 4.2 40
13 Koskie TOR 4 39
14 Cuddyer MIN 3.9 45
15 Boone CLE 3.8 55

It may come as a surprise to some Tiger fans that Brandon Inge (5.2) finished as high as sixth. The problem with Inge is that most of his hitting was done in the first half. Inge has made great strides over the past couple of years but has still not put up a full season of good hitting and many feel he is better suited to the super sub role.

Shortstops


Rank Player Team RC/G RC
1 Young TEX 7.6 125
2 Peralta CLE 6.9 92
3 Tejada BAL 6.5 110
4 Lugo TB 6.4 102
5 Jeter NYA 6.3 106
6 Crosby OAK 5.3 48
7 Guillen DET 5 42
8 Renteria BOS 4.9 82
9 Adams TOR 4.8 64
10 Cabrera LAA 4.3 64
11 Uribe CHA 4.3 58
12 Scutaro OAK 4.3 45
13 Berroa KC 4.2 68

After a near MVP caliber season last year, Carlos Guillen (5.0) spent the season going on and off the disabled list. His knee is supposedly going to be at full strength by next spring but I’m skeptical. Infante might be getting a lot of bats there next year too.

Left fielders


Rank Player Team RC/G RC
1 Ramirez BOS 9.2 134
2 Catalanotto TOR 7.1 77
3 White DET 6.8 65
4 Matsui NYA 6.8 110
5 Crawford TB 6.6 111
6 Dellucci TEX 6.5 78
7 Ibanez SEA 6.3 103
8 Crisp CLE 6.3 97
9 Anderson LAA 5.6 86
10 Winn SEA 5.2 54
11 Johnson TOR 5.1 55
12 Everett CHA 5.1 69
13 Kielty OAK 5.1 53
14 Stewart MIN 4.8 71
15 Long KC 4.7 58
16 Podsednik CHA 4.7 62
17 Mench TEX 4.7 72
18 Surhoff BAL 3.6 30
19 Womack NYA 3 28

I was a bit surprised to see Rondell White (6.8) ranked as high as he was. As usual, he did spend a lot of time on the DL though. He’s a free agent this off season and his status is unclear. He’s a nice guy to have as a part time outfielder/designated hitter but they need left-handed bats so I’m not sure what will happen with him.

Center fielders


Rank Player Team RC/G RC
1 Damon BOS 6.6 104
2 Sizemore CLE 6.4 107
3 DeJesus KC 6.4 77
4 Kotsay OAK 5.6 86
5 Wells TOR 5.6 93
6 Hunter MIN 5.5 55
7 Matos BAL 5.3 55
8 Ford MIN 5.1 73
9 Rowand CHA 4.9 76
10 Williams NYA 4.7 63
11 Hollins TB 4.7 45
12 Matthews TEX 4.6 60
13 Logan DET 3.9 35
14 Reed SEA 3.8 52
15 Finley LAA 3.5 41

Even with stolen bases included in the RC/G formula, Nook Logan (3.9) didn’t do much to create runs. It would be great if they could utilize his speed and outfield range but he doesn’t hit well enough to get regular at bats in the majors. Curtis Granderson did not get enough plate appearances to qualify for the list but his 6.3 runs created per game would have put him 4th on the list. Like I said about Shelton, if he can do that for a full season, I’ll be very pleased.

Right fielders


Rank Player Team RC/G RC
1 Guerrero LAA 8.6 113
2 Sheffield NYA 8.5 131
3 Gomes TB 7.2 67
4 Ordonez DET 6.9 54
5 Suzuki SEA 6.5 114
6 Brown KC 6.4 92
7 Nixon BOS 6.3 70
8 Gibbons BAL 6 78
9 Dye CHA 5.5 78
10 Rivera LAA 5.4 51
11 Monroe DET 5.4 82
12 Huff TB 5.3 84
13 Jones MIN 5.1 75
14 Swisher OAK 4.8 63
15 Rios TOR 4.1 54
16 Blake CLE 3.8 56
17 Hidalgo TEX 3.7 33
18 Sosa BAL 3.5 39

Magglio Ordonez missed the first half of the season with a hernia but had a solid second half producing 6.9 runs per game. It would be good to see a full season of Ordonez but I’m still a little concerned about his knee holding up. He looked like he had a great deal of trouble moving around last year and I’m not convinced his hernia was not related to his knee rehab. Craig Monroe played all three outfield positions and would have finished somewhere in the middle of any of the positional lists. He’s been a durable and versatile outfielder giving average production the last couple of years but I suspect he may be traded as they attempt to become more left-handed.

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Another question might be, how many hits are lost because the first baseman is no longer holding the runner on firstbase after Podsednik has stolen secondbase?

That's an important after effect of having someone steal a base. I think Bill James did a study that showed that Ba dropped by 30 points after a stolen base attempt (successfull or not). He attributed it to the first baseman moving back into position, and the fact that hitters often take pitches to give base stealers a chance to steal, thus putting them behind in the count more often.

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Thanks Lee. I think I would take Matsui's 6.8 over Rondell's for some reason.:cheeky:

I would definitely take Matsui over White. The main reason is because he's much more durable and that is reflected in his RC (110 versus 65). The other reason is that Matsui is more likely than White to repeat his performance next year. White was given a slight boost because of his ballpark (it was 2% easier to score runs in Yankee Stadium versus Comerica last year) but neither is a good hitter's park. White made up most of the the difference with a better BA with RISP (.364 versus .315) which is something I wouldn't expect him to repeat next year.

I think the version of the RC formula I took off the Hardball Times site is very accurate for determining a player's contribution to his team's offense in 2005 (better than OPS). It's a good formula for determining who was the most valuable hitter on his team during the season. Because it is dependent on BA with RISP though, it's probably not the best one for projecting into the future. There are other versions of the formula that do not use BA with RISP.

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:laugh::laugh:

So maybe we should have online lessons in how to do it...cuz it seems very complicated for a math idiot like myself.

Actually that one (percentages of homeruns)wouldn't be too hard--mostly compiling all the numbers. Add up all the teams runs and all their homeruns and divide the home runs by the number of runs (Homeruns/runs), use a calculator and round off. :confused: He went to a lot of work to get those totals. What I want to know is, where are the Astros on that list? What was their percentage?

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Actually that one (percentages of homeruns)wouldn't be too hard--mostly compiling all the numbers. Add up all the teams runs and all their homeruns and divide the home runs by the number of runs (Homeruns/runs), use a calculator and round off. :confused: He went to a lot of work to get those totals. What I want to know is, where are the Astros on that list? What was their percentage?

The Astros were 23%

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thanks. How come they weren't on the list?

I only did the calculation for the American League.

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There was a lot of talk this year about the inconsistency of the Detroit Tigers. All year long, media and fans alike moaned that “they are the streakiest team in baseball”. They would get on a roll for a few games but just when it seemed they had things figured out, they would fall back down again. All teams go through streaks but were the Tigers streakier than other teams?

Using raw data on winning and losing streaks from Baseball Prospectus, I determined that the Tigers had 25 streaks of three games or longer. This included:

* 6 three game winning streaks and 5 three game losing streaks

* 3 four game winning streaks and 4 four game losing streaks

* 2 five game winning streaks and 3 five game losing streaks

* 1 eight game losing streak

* 1 nine game losing streak

Only the Houston Astros and Tampa Bay Devil Rays, each with 27 streaks of three games or longer, had more streaks of three games or longer than the Tigers. Furthermore, the 14 Tiger streaks of four games or longer were more than any other team in the majors.

While the Tigers had 23 or more streaks of three to five games (most in the majors), they had only two streaks of six games or longer, both of those coming in their horrible September stretch drive. Only the Toronto Blue Jays (0), St. Louis Cardinals (1) and Pittsburgh Pirates (1) had fewer streaks of six games or longer.

So, I can conclude that the Tigers were indeed streakier than most teams. They didn’t have a lot of really long streaks. However, they specialized in modest streaks of three to five games and they did that better (and worse) than any other team.

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This involves alot of reading and thinking and stuff.

Yeah, I know I'm a geek but I love this stuff. You should check out my blog. It's got even more stuff like this. My blog needs some hits.

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Yeah, I know I'm a geek but I love this stuff. You should check out my blog. It's got even more stuff like this. My blog needs some hits.
You are bookmarked. Thanks for these contributions Lee. I like the idea that Pena could have some Andre Thornton years in him. That would be too cool!:smile:

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Similarity Scores were introduced by Bill James about 20 years ago. They are now included in the Baseball-reference database. The way it works is you select any player and run him through the database to see which players in the history of the game are most similar to him statistically. For example, the player who was most similar to Carlos Pena through the age of 27 was Andre Thornton.

James did not develop a really sophisticated algorithm and did not intend for it to be taken as a serious projection tool. In some cases, it might put a player’s career in perspective or give you some kind of clue as to where he might be headed. In other cases, it’s nothing more than a conversation piece. Below, I ran a few Tigers through the program. Note that a perfect similarity score is 1000. A score of 1000 would indicate that two player’s were exactly alike.

Carlos Pena

Andre Thornton (956)

Mike Epstein (955)

Bob Robertson (952)

Jay Buhner (948)

Don Mincher (939)

Tino Martinez (938)

Phil Plantier (938)

Nick Esasky (937)

Jay Gibbons (936)

Rob Deer (936)

Not surprisingly, Pena is matched with players who hit a lot of homeruns and walked a lot but hit for low average with a lot of strike outs. Note that the similarity score algorithm does not adjust for era. Nor does it adjust for ballpark.

Brandon Inge

Roy Smalley (957)

Daryl Spencer (952)

Eli Marrero (950)

Dale Sveum (947)

Luis Rivera (944)

Andre Rodgers (944)

Frank Duffy (942)

Pat Meares (941)

Alex Cora (936)

Billy Myers (936)

It would be nice if he could be matched to Roy Smalley Jr. rather than Roy Smalley Sr.

Craig Monroe

Harry Anderson (982)

Jeffrey Hammonds (967)

Art Shamsky (964)

Hal McRae (961)

Henry Rodriguez (961)

Johnny Rizzo (960)

Bob Nieman (960)

Jim Greengrass (959)

Jerry Lynch (956)

Larry Sheets (956)

Hopefully, he’ll have a better career than Harry Anderson.

Placido Polanco

Todd Walker (932)

Gil McDougald (925)

Adam Kennedy (923)

Fred Dunlap (919)

Jimmie Dykes (915)

Johnny Ray (914)

Odell Hale (911)

Hubie Brooks (907)

Julio Franco (905)

Tony Bernazard (903)

Todd Walker is not a bad comparison. Luckily, Polanco is better defensively.

Carlos Guillen

Johnny Logan (942)

Julio Lugo (935)

Billy Sullivan (932)

Tom Burns (929)

Sam Wise (928)

Alvin Dark (926)

Ron Belliard (926)

Rich Aurilia (925)

Adam Kennedy (924)

Mike Lansing (924)

Logan is not a bad player with whom to be compared. Guillen needs to stay healthy though.

Magglio Ordonez

Mike Sweeney (963)

Wally Berger (952)

Fred Lynn (941)

Tony Oliva (938)

Dave Parker (936)

Larry Walker (925)

Jim Edmonds (925)

Tim Salmon (919)

Ellis Burks (918)

George Foster (916)

There are some interesting names on that list, a lot of good players who missed significant time due to injury.

Ivan Rodriguez

Ted Simmons (864)

Yogi Berra (822) *

Gary Carter (812) *

Johnny Bench (791) *

Joe Torre (791)

Cal Ripken (788)

Bill Dickey (778) *

Ryne Sandberg (770) *

Joe Cronin (769) *

Bobby Doerr (768)*

Lot’s of HOFers (that’s what the * is for) there. Hopefully Pudge has something left.

Dmitri Young

Rondell White (950)

Felipe Alou (948)

Richie Zisk (942)

Joe Adcock (939)

Cecil Cooper (938)

Bobby Higginson (938)

Leon Durham (930)

Wally Joyner (929)

Cliff Floyd (927)

Bill Skowron (920)

Dmitri=Rondell

In case you are wondering, they didn’t do similarity scores for Chris Shelton and Curtis Granderson because their careers are too short at this point.

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Yeah, I know I'm a geek but I love this stuff. You should check out my blog. It's got even more stuff like this. My blog needs some hits.

Yes - check out his blog. Lee rocks, and if he gets discouraged because nobody is reading his blog he might quit - and that will suck.

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Yes - check out his blog. Lee rocks, and if he gets discouraged because nobody is reading his blog he might quit - and that will suck.

The traffic has been getting a little better the last couple of days.

Check out billfer's blog too. :happy:

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