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tiger337

Winter of Sabermetrics

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In the new 2007 Bill James Handbook, there is a great article about Manufactured Runs. So many "baseball men" talk about its importance, but how important is it to scoring runs, anyway?

Bill James and Steve Moyer (from Baseball Info Solutions) discussed this at length and determined that a "manufactured run" (MR) is "at least one-half created by the offense doing something other than playing station-to-station baseball". By definition, it does not involve extra-base hits, although it can involve a string of singles.

There are two types of MR:

MR1: results from deliberate acts such as bunts and stolen bases;

MR2: results from other things like infield hits, taking advantage of the defense, advancing extra bases on hits, advancing and outs and throws, etc.

The key difference, as far as I can tell, is that MR1 generally result from manager (strategic) decisions, while MR2 result from player (tactical) decisions.

They also developed 12 rules as to what constitutes an MR, which i won't go into here. However, the book did list the 30 teams and how many manufactured runs they scored in 2006:

Lg	Team	MR	MR1	MR2
AL MIN 224 84 140
AL LAA 190 80 110
AL KCA 186 57 129
AL BAL 184 74 110
AL SEA 176 46 130
AL TAM 166 63 103
AL NYA 163 59 104
AL CHA 160 49 111
AL BOS 147 39 108
AL OAK 142 37 105
AL TEX 142 36 106
AL TOR 139 42 97
AL CLE 139 43 96
AL DET 124 41 83

NL COL 198 81 117
NL WAS 185 85 100
NL CHN 175 99 76
NL FLA 175 69 106
NL LAN 172 72 100
NL ARI 169 56 113
NL PIT 167 58 109
NL STL 164 43 121
NL HOU 161 67 94
NL NYN 158 61 97
NL MIL 151 44 107
NL PHI 148 33 115
NL SFN 144 53 91
NL ATL 143 50 93
NL SDN 141 68 73
NL CIN 135 57 78

The Twins were the best in the AL at manufacturing runs; the Tigers were last. It's not that the Tigers didn't try their share of little ball -- they did -- but they also clearly didn't score on the player-oriented tactical stuff as much as the others.

OK, so beyond this basic table -- does MR correlate to scoring lots of runs? Let's find out.

Here is the correlation of MR, MR1 and MR2 to Runs Scored:

Lg	Team	Runs	MR	MR1	MR2
AL LAA 766 190 80 110
AL OAK 771 142 37 105
NL HOU 735 161 67 94
AL TOR 809 139 42 97
NL ATL 849 143 50 93
NL MIL 730 151 44 107
NL STL 781 164 43 121
NL CHN 716 175 99 76
AL TAM 689 166 63 103
NL ARI 773 169 56 113
NL LAN 820 172 72 100
NL SFN 746 144 53 91
AL CLE 870 139 43 96
AL SEA 756 176 46 130
NL FLA 758 175 69 106
NL NYN 834 158 61 97
NL WAS 746 185 85 100
AL BAL 768 184 74 110
NL SDN 731 141 68 73
NL PHI 865 148 33 115
NL PIT 691 167 58 109
AL TEX 835 142 36 106
AL BOS 820 147 39 108
NL CIN 749 135 57 78
NL COL 813 198 81 117
AL KCA 757 186 57 129
AL DET 822 124 41 83
AL MIN 801 224 84 140
AL CHA 868 160 49 111
AL NYA 930 163 59 104

Correl to runs
Runs MR MR1 MR2
Majors 1.00 (0.19) (0.36) 0.12
AL Only 1.00 (0.42) (0.38) (0.02)
NL Only 1.00 (0.15) (0.40) 0.17

Interesting -- looks like there is a decent negative correlation between Runs and MR1 -- the scoring from bunts and stolen bases. That is, the more runs a team scores from MR1, the fewer runs they score overall. That's likely because these managerial decisions generally trade outs, or risk outs, for single runs, and the more a team employs these tactics, the fewer runs they will score overall -- because the more outs they are making on purpose.

There does not seem to be much if any correlation between MR2 and runs scored, since these are player decisions generally made on the fly, based on their judgment, and are risking outs much less than MR1 does.

While I broke out each league as well as looked at the majors in general, I did not see a significant difference between the two leagues.

The other key thing I wanted to try to determine was: do certain types of teams tend more toward MR, MR1 and MR2, based on their batting average, on base percentage and slugging percentage? I did the same correlation analysis for these attributes, and here are the overall results:

Correl	   AVG	   OBP	   SLG	  iOBP	   ISO
MR 0.23 (0.01) (0.36) (0.26) (0.60)
MR1 (0.02) (0.20) (0.37) (0.22) (0.45)
MR2 0.34 0.20 (0.11) (0.12) (0.36)

In addition to AVG/OBP/SLG, I also looked at isolated slugging percentage (ISO, or SLG-AVG), and what I am calling iOBP (no, it's not a new MP3 player -- it's a shorthand way at getting at isolated on-base percentage, or OBP-AVG)

What we see here is pretty clear, I think: a high batting average can correlate softly to MR, particularly MR2 -- but high on base and high slugging teams do not correlate highly to MR. And it is high OBP and high SLG that correlate to run scoring in general -- which is the opposite of the negative correlation of MR to runs scored.

Conclusion: team that spend a lot of time trying to manufacture runs will not score a lot of them. Perhaps lack of ability to score many runs is the cause of small ball -- but then again, it could be the effect of small ball as well. Someone who knows regression analysis better than I could take that one on.

Looking at that chart, Detroit was bottom of the heap (of both leagues) regarding MR. I am guessing this reflects Leylands general dislike of small ball. I am assuming that all the other runs were from long ball and extra base hits--hence high OBP and SLG. I know there were complaints during the season that the Tigers rely too much on the long ball. Perhaps Leyland is wise in his dislike for bunting.

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I did some regressions for the manufacrured runs analysis. Here are my variables

Runs

MRPCT=% of runs which are manufactured

MR1PCT=% of runs which are MR1

MR2PCT=% of runs which are MR2

BA

ISO=SLG-BA

Extra OBP = EOBP = (walks+HBP)/PA

Simple Correlations:

MRPCT is negatively correlated with runs

MR1PCT is negatively correlated with runs.

MR2PCT has no significant correlation with runs.

This is the same result Chuck got.

Regressions

I then did regressions predicting runs scored from MRPCT after adjusting for BA, ISO, EOBP. After the adjustments, there is no significant correlation between MRPCT and runs. I did the same regression with MR1PCT and MR2PCT and got the same results

Conclusions

Runs scored are essentially a function of batting average, isolated power and extra OBP. Based on the available data, there is no evidence that the % of runs which are manufactured has a significant effect on the total number of runs that a team scores.

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I did some regressions for the manufacrured runs analysis. Here are my variables

Runs

MRPCT=% of runs which are manufactured

MR1PCT=% of runs which are MR1

MR2PCT=% of runs which are MR2

BA

ISO=SLG-BA

Extra OBP = EOBP = (walks+HBP)/PA

Simple Correlations:

MRPCT is negatively correlated with runs

MR1PCT is negatively correlated with runs.

MR2PCT has no significant correlation with runs.

This is the same result Chuck got.

I did run this yesterday as part of my analysis as well. I did not post it because I thought it basically showed the same results as were shown in yesterday's raw runs/MR table I ran. Here is that table:

Team	Runs	%MR	%MR1	%MR2
LAA 766 24.8% 10.4% 14.4%
OAK 771 18.4% 4.8% 13.6%
HOU 735 21.9% 9.1% 12.8%
TOR 809 17.2% 5.2% 12.0%
ATL 849 16.8% 5.9% 11.0%
MIL 730 20.7% 6.0% 14.7%
STL 781 21.0% 5.5% 15.5%
CHN 716 24.4% 13.8% 10.6%
TAM 689 24.1% 9.1% 14.9%
ARI 773 21.9% 7.2% 14.6%
LAN 820 21.0% 8.8% 12.2%
SFN 746 19.3% 7.1% 12.2%
CLE 870 16.0% 4.9% 11.0%
SEA 756 23.3% 6.1% 17.2%
FLA 758 23.1% 9.1% 14.0%
NYN 834 18.9% 7.3% 11.6%
WAS 746 24.8% 11.4% 13.4%
BAL 768 24.0% 9.6% 14.3%
SDN 731 19.3% 9.3% 10.0%
PHI 865 17.1% 3.8% 13.3%
PIT 691 24.2% 8.4% 15.8%
TEX 835 17.0% 4.3% 12.7%
BOS 820 17.9% 4.8% 13.2%
CIN 749 18.0% 7.6% 10.4%
COL 813 24.4% 10.0% 14.4%
KCA 757 24.6% 7.5% 17.0%
DET 822 15.1% 5.0% 10.1%
MIN 801 28.0% 10.5% 17.5%
CHA 868 18.4% 5.6% 12.8%
NYA 930 17.5% 6.3% 11.2%

Correl to runs
Team Runs %MR %MR1 %MR2
Majors 1.00 (0.59) (0.54) (0.33)
AL Only 1.00 (0.75) (0.52) (0.43)
NL Only 1.00 (0.53) (0.59) (0.27)

If anything, when you look at percentages rather than raw runs, the negative correlations for MR% and MR1% are stronger, and there is at least a soft negative correlation with MR2%. I was a little surprised to show even a soft correlation on the last one, but I think that just helps proves that teams that score a lot of runs slug their way to it, rather than having to manufacture runs to get there, even in a way that reflects player decision on the field rather than managerial decision in the dugout.

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As for the manufactured run analysis, I'd like to see them break it down by game situation. Manufacturing runs early in the game might not be a good idea whereas manufacturing runs late in a close game might be a good thing (maybe).

I think this concept has been proved a number of times. My take on this analysis is that teams who employ a good deal of "manufactured runs" strategy, all game long, do not score as many runs as teams who employ less of it.

My interest would be in solving the chicken-egg part -- meaning (a) to what degree is the issue one of teams recognizing their meager offensive talents and try to eke out runs in this fashion because they could not otherwise produce them; and (b) to what degree do teams employing this strategy limit the number of runs they might otherwise score if they were to just "let 'er rip". That's what I would like a regression analysis to solve, if possible.

Looking at that chart, Detroit was bottom of the heap (of both leagues) regarding MR. I am guessing this reflects Leylands general dislike of small ball. I am assuming that all the other runs were from long ball and extra base hits--hence high OBP and SLG. I know there were complaints during the season that the Tigers rely too much on the long ball. Perhaps Leyland is wise in his dislike for bunting.

Respectfully, Wendy, I'm just knocked out that people here continue to state the Jim Leyland hates small ball and/or doesn't do enough of it. Leyland was third of 14 (with 57) in the American League for sac bunts, the ultimate small ball tactic. In other small ball tactics, he's 7th in ordering stolen bases attempts (100) and 5th in hit and run attempts (i.e., runners moving on the pitch) with 124 (although 128 would have been good for 2nd). So he definitely does like to "push buttons" on the offensive side.

This makes the Tigers' last place standing in actual manufactured runs scored stand out even more starkly. It would appear clear that all button-pushing isn't having the desired effect -- after all, we're dead last, by a long-shot, in manufactured runs, even though we are somewhat above average in employing the tactics to get those manufactured runs. I think this is because we simply don't have a team built for small ball. So why are we doing it so much?

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Respectfully, Wendy, I'm just knocked out that people here continue to state the Jim Leyland hates small ball and/or doesn't do enough of it. Leyland was third of 14 (with 57) in the American League for sac bunts, the ultimate small ball tactic. In other small ball tactics, he's 7th in ordering stolen bases attempts (100) and 5th in hit and run attempts (i.e., runners moving on the pitch) with 124 (although 128 would have been good for 2nd). So he definitely does like to "push buttons" on the offensive side.

This makes the Tigers' last place standing in actual manufactured runs scored stand out even more starkly. It would appear clear that all button-pushing isn't having the desired effect -- after all, we're dead last, by a long-shot, in manufactured runs, even though we are somewhat above average in employing the tactics to get those manufactured runs. I think this is because we simply don't have a team built for small ball. So why are we doing it so much?

Thank you for straightening me out. I have to admit that, rather than researching it out for myself, I accepted what the general consensus (including the media) has stated. That is why we have guys like you around, who love to research out what everyone else is too lazy to (myself included--actually, I wouldn't know where to begin :grin: ) I appreciate the study and analysis you guys do in here, and check it out periodically. I think I actually understand most of what you are saying too. :cool: Thanks guys.

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Has anyone looked at the MR stats on a month by month basis? I'd be interested to see if Leyland used small ball strategies less after the first few months, maybe trying them again when the offense sputtered late in the season.

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Has anyone looked at the MR stats on a month by month basis? I'd be interested to see if Leyland used small ball strategies less after the first few months, maybe trying them again when the offense sputtered late in the season.

Maybe Bill James has. I think he might be the only guy with the data. It's gonna take a little elbow grease for us regular folks to get to that answer. Anyone here motivated and knowledgeable enough to take his 12 rules and parse through the Retrosheet data? Lee, I'm looking in your direction ... :wink:

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Maybe Bill James has. I think he might be the only guy with the data. It's gonna take a little elbow grease for us regular folks to get to that answer. Anyone here motivated and knowledgeable enough to take his 12 rules and parse through the Retrosheet data? Lee, I'm looking in your direction ... :wink:

Analyzing the retrosheet event data is something I've thought about doing for a while but it would be a really time consuming project. If I ever get around to it, I'll let you know.

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It was posted somewhere, but I cant find the Sabremetrics of Runs created for Adam Dunn. Does anyone have these numbers by anychance?

Was wondering:

Basic Run's created in 0-2/3-2 counts

OPS with Runners on

Avg with Runners on in scoring position (also with amount of outs.)

Thanks in advance for any help that can be given.

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It was posted somewhere, but I cant find the Sabremetrics of Runs created for Adam Dunn. Does anyone have these numbers by anychance?

Was wondering:

Basic Run's created in 0-2/3-2 counts

OPS with Runners on

Avg with Runners on in scoring position (also with amount of outs.)

Thanks in advance for any help that can be given.

You can find Adam Dunn's split stats at both his ESPN Splits and Yahoo Situational cards. Retrosheet has deeper split results, although they have fewer splits, and they won't have it updated to include 2006 until probably next spring.

They don't have the deeper sabermetrics on any of the splits card, although you could apply the standard Runs Created formula to get at that number if you really want it. I would think that relationally speaking, RC would result in the same comparison as would basic stats review.

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Regarding Leyland's small ball proclivities: I've always had the impression that he wants to be a manager pushing buttons. He's clearly not a stats guy, he brags about not liking computers. I give him credit for figuring out, at least to some extent, that small ball doesn't work well with the Tigers.

The situation that comes to mind is the Yankee ALDS series. Leyland was quoted as saying he would do a lot of managing because the Tigers were underdogs and they needed to make things happen. He tried this in game one and it didn't work. To the best of my recollection, there was very little small ball the rest of the series.

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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).

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.

In the last couple of years, I’ve found that an acceptable substitute for the complicated RC, and the troubled OPS, is bases per out. One of the things I like most about it is, not only is it simple to compute, it works equally well for hitters and pitchers,

I’m not so enthralled with BARISP as most are. What does it show other than hits? This week Lofton drew 2 bases loaded walks in the 9th inning. Although he got deservedly got 2 RBI’s, his BARISP wasn’t affected. And how many batters hit a grounder to either move a runner from 2nd to 3rd or to drive in a run, and their BARISP goes down?

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Excellent stuff. As a newbie (and a refugee from a site where you mention math and most everyone mocks or complains), I appreciate that this is stuck here to find easily. Great work, Lee!

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Excellent stuff. As a newbie (and a refugee from a site where you mention math and most everyone mocks or complains), I appreciate that this is stuck here to find easily. Great work, Lee!

This particular thread fizzled out but I think you'll see that a lot of people on this site like stats or at least are open to it. Welcome to MotownSports.

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This particular thread fizzled out but I think you'll see that a lot of people on this site like stats or at least are open to it. Welcome to MotownSports.

Thanks for the welcome! I love the stats - they're what makes the game unique.

Last weekend I found, in a box, a program from the first game my late mother ever attended in Chicago. (She's the one who taught me how to keep score.) She didn't score that particular game, but wrote the date on the program (6/30/1958) and a brief note telling whoever found the program that Cleveland won 5-3 (damn Indians). Through the "magic of the Internet" I've found the boxscore and play-by-play for that date. Cal McLish got the win for the Indians that day.

For that matter, I also found a card - scored - from opening day 1966 at Wrigley Field. The names in those lineups - Mays, McCovey, Banks, Williams...

I'm unaware of any other sport that has the sense of history that we enjoy in baseball.

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I think Lee (Tiger337) is too proper to advertise his own book here (and the rules might not allow it.) I hope its OK if I recommend Beyond Batting Average for getting a start on sabermetrics.

E-edition.

Print edition.

Thanks, Lee, for being one of the more informative, helpful posters for those with good intentions who are new to sabermetrics.

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Interesting nugget from Jayson Stark, not worth a thread and I didn't know where to put it....

"5. Carlos Pena, who is hitting .209, has reached base more times (66) than Andrew McCutchen (64), who is hitting .340."

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Yep I remember posting an article on here last year about how the Rangers got extremely lucky with their sequencing and clustering of hits while the Tigers were actually unlucky.  That was one of the reasons why I thought the Tigers would be fine this year was because of that stat, unfortunately I didn't expect most of the team to crap the bed.

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Whatever happened top hongbit?  He was one of the funniest posters in MTS history.  

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Hongbit was in my fantasy football league up until a couple of years ago, and I haven't heard from him since.  I never had his email, he kept it private.

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