Odds and Ends

“The only correct actions are those that demand no explanation and no apology.” – Red Auerbach

Over the last few weeks, I’ve received plenty of feedback related to my articles on sacrifice flies and the collective bargaining agreement: To Go or Not to Go, Scoring on the Sacrifice Fly, and Competitive Balance and the CBA. Because of that feedback, or maybe because I’m just not that original, this week I’ll answer a few of most frequently asked questions about both sets of articles.

Competitive Balance

First, several readers commented about my use of payrolls in order to perform the correlation. I should mention that the salaries that I used to calculate the payrolls in the Lahman database are those from the start of the season, and do not include in-season signings and trades. While this isn’t ideal, it does avoid the problem of using end of the season salaries, as these tend to overestimate the payroll differences between good and bad teams, due to bad teams shedding payroll to the good teams around the trading deadline.

In any case, the main point is that in my study, payrolls were acting as a proxy for market size, or market revenue potential. In other words, the link between payroll and winning percentage is not that surprising, since better athletes on the whole command higher salaries. But payroll has an implied link with the characteristics of the market the team plays in as well, and that is a variable that teams cannot control. The two are definitely linked, but they are not the same thing. As the Blue Ribbon Commission of 1999 noted:

“Although a high payroll is not always sufficient to produce a club capable of reaching post season play … a high payroll has become an increasingly necessary ingredient of on the field success …”

A more proper study, like that conducted by Donald F. Leypoldt, Jr several years ago, would include the revenue potential of the market, since payroll is under the discretion of management, so even a team with plenty of money can have a fire sale or squirrel away their revenue sharing money. I certainly concede the point, but I chose to use payroll, since that was the data that was on hand, and overall it serves as a good stand-in for the size of the market.

Second, reader Lou Poulas offered a second way of looking at competitive balance, and that is simpy through team records. Using this approach takes payroll and market out of the equation, and as a result illustrates the pure spread of the teams over time. The following table shows the number of teams with the specified number of wins during the last three CBAs (the number of wins were adjusted for 1994 and 1995 using the team’s winning percentage based on 162 games).

Category 1990-1996    1997-2001    2002+
40-49          0          0           1
50-59          3          1           6
60-69         19         31          19
70-79         71         43          27 
80-89         55         36          31
90-99         35         29          27
100+           7          8           9

The table can also be converted into percentages (all rounded up, so each column does not total to 1.0), since the total number of teams went from 190, to 148, to 120 in the three successive periods.

Category  1990-1996    1997-2001     2002+
40-49         .00        .00          .01
50-59         .02        .01          .05
60-69         .10        .21          .16
70-79         .37        .29          .23 
80-89         .29        .24          .26
90-99         .18        .20          .23
100+          .04        .05          .08

As you can see, the percentage of teams with 90 or more wins went from 22%, to 25%, to 31% in the three periods, with the percentage of teams with more than 100 wins also increasing. This is reflected in the standard deviation of winning percentage, which increased from .281, to .329, to .331 over the three periods. At the same time, however, the percentage of teams with fewer than 69 wins has basically remained the same since 1997, although those with fewer than 60 wins has increased six-fold.

Third, our own Dave Studeman posted a variant of the graph I constructed on his site. In his analysis, he took out the Yankees and the four expansion teams from the 1990s, and finds that the coefficient of variation declined during the most recent CBA.

Although I hesitate to disagree with Dave, I generally dislike throwing out data points, since it can be argued that by doing so you’re influencing the results of your study. In this case, some might argue that the Yankees should be excluded, since they’ve made it clear that they’re not going to let little things like revenue sharing and a luxury tax get in their way. At the very least, however, the Yankees, one of the two teams playing in the largest market, should be included, but have their payroll capped at just above the maximum of other teams.

On the contrary, one could argue that the Yankees are a big part of the impetus for creating the revenue sharing and luxury tax system in the current CBA in the first place. As a result, excluding them would render any results fairly meaningless.

With that said, there are signs that the times are a changing. After all, the Yankees did not end up signing Carlos Beltran last year, in part at least, because of the luxury tax as reported by the Washington Post:

“Yankees officials acknowledge that they were constrained by two of the changes adopted three years ago—revenue-sharing and a penalty against high-spending clubs known as the luxury tax. ‘We had priorities this winter—primarily, improving our starting pitching—and we feel we met those priorities,” Yankees President Randy Levine said. ‘We’re like every other team, even though our revenues are larger than other teams. We’re conscious of revenue sharing and the luxury tax.’”

And it has been widely reported that the Yankees lost $50 to $85 million in 2005 and $37 million in 2004, totals that are less than the amount they contributed via revenue sharing and luxury tax—a bill that came to $110 million last year.

Finally, several readers asked about solutions to the problem of competitive balance. While in the article I showed that competitive balance hasn’t really increased in the last four years, I do think that the current system has helped, in the same way that even a partially clogged sink holds back some of the water. Without the provisions of the last CBA, can you imagine what the Yankees, Red Sox, and Angels teams would look like with the spigot turned on full?

But I do agree with Dayn Perry at Fox Sports, who argues that more needs to be done, and it seems to me that a good start is upping the percentage of local revenues shared to 50%. Equally important, however, is that teams should be held accountable for the way they use the money they receive. The late Doug Pappas, in reviewing the 2002 CBA, wrote that:

“Each club receiving revenue sharing is required to ‘use its revenue-sharing payments in an effort to improve its performance on the field,’ subject to unspecified penalties from the Commissioner if it doesn’t.”

So although Mr. Selig has the power, it seems he either doesn’t have the mechanism or the will to hold teams accountable.

I don’t agree with proposals that would force a minimum payroll, as that could just as likely cause a team like the Royals to spend money on third tier free agents, rather than invest in the future by signing international players or expanding their scouting and minor league programs. Wait … maybe that’s a bad example.

Sacrifice Flies

After my two articles looking at sacrifice flies—an interesting but admittedly small part of the game—several readers wrote to ask how teams stacked up against each other. Their reasoning for wanting to analyze this information was to see if some teams, perhaps via their third base coaching, were more risky and therefore enjoyed better success rates than others. Sounds reasonable, and so I totalled up the same set of sacrifice fly statistics I looked at in the previous articles, but did so for each team from 2000 to 2005 and for each individual team season.

First, at an aggregate level, here are the teams sorted by the percentage of time they were successful when the runner was sent.

                Opp  Scores      OA   Hold%   Succ%
TEX             356     280       7   0.194   0.976
SFN             386     304       8   0.192   0.974
NYA             320     256       7   0.178   0.973
LAN             275     223       7   0.164   0.970
DET             361     293      10   0.161   0.967
NYN             300     230       8   0.207   0.966
TOR             340     282      10   0.141   0.966
SDN             353     283      11   0.167   0.963
CHN             329     257      10   0.188   0.963
KCA             385     307      12   0.171   0.962
PHI             343     263      11   0.201   0.960
ARI             334     276      12   0.138   0.958
ANA             392     288      13   0.232   0.957
ATL             339     282      13   0.130   0.956
MIL             293     233      11   0.167   0.955
SEA             409     332      16   0.149   0.954
TBA             332     253      13   0.199   0.951
FLO             354     271      14   0.195   0.951
OAK             340     271      14   0.162   0.951
CHA             357     290      15   0.146   0.951
BAL             359     287      15   0.159   0.950
CLE             350     281      15   0.154   0.949
BOS             396     316      17   0.159   0.949
MON/WAS         308     236      13   0.192   0.948
MIN             335     269      15   0.152   0.947
CIN             274     227      13   0.124   0.946
COL             345     278      16   0.148   0.946
SLN             376     307      18   0.136   0.945
PIT             314     236      14   0.204   0.944
HOU             360     282      17   0.169   0.943

As you can see the spread from the team that was most successful, the Rangers, and that which was the least successful, the Astros, varies from 2.4% to 5.7% over the period. The average for all teams, as I mentioned previously, was 95.6%. From an overall perspective, you don’t really see major differences in success rate, largely because the overall success rate is so high and also because in a larger sample like this, variation tends to decrease.

It is mildly interesting as well that Seattle had over 400 opportunities to score on sacrifice flies, while Cincinnati had just 274. I wouldn’t have expected such a large disparity.

Now let’s take a look at the same list but sorted by hold percentage, defined as the percentage of time the runner did not try and score on a sacrifice fly opportunity.

                Opp  Scores      OA   Hold%   Succ%
ANA             392     288      13   0.232   0.957
NYN             300     230       8   0.207   0.966
PIT             314     236      14   0.204   0.944
PHI             343     263      11   0.201   0.960
TBA             332     253      13   0.199   0.951
FLO             354     271      14   0.195   0.951
TEX             356     280       7   0.194   0.976
SFN             386     304       8   0.192   0.974
MON/WAS         308     236      13   0.192   0.948
CHN             329     257      10   0.188   0.963
NYA             320     256       7   0.178   0.973
KCA             385     307      12   0.171   0.962
HOU             360     282      17   0.169   0.943
MIL             293     233      11   0.167   0.955
SDN             353     283      11   0.167   0.963
LAN             275     223       7   0.164   0.970
OAK             340     271      14   0.162   0.951
DET             361     293      10   0.161   0.967
BOS             396     316      17   0.159   0.949
BAL             359     287      15   0.159   0.950
CLE             350     281      15   0.154   0.949
MIN             335     269      15   0.152   0.947
SEA             409     332      16   0.149   0.954
COL             345     278      16   0.148   0.946
CHA             357     290      15   0.146   0.951
TOR             340     282      10   0.141   0.966
ARI             334     276      12   0.138   0.958
SLN             376     307      18   0.136   0.945
ATL             339     282      13   0.130   0.956
CIN             274     227      13   0.124   0.946

Here, you can see that there are some differences between teams. The Angels, who pride themselves on taking the extra base, held their runners fully 10% more often than did the Reds and the Braves. And while the bottom four teams in this list are from the National League, there doesn’t seem to be a strong tendency for one league or the other to either be more successful, or hold runners more frequently. The larger differences here may indeed point to personnel issues, either on the field or in the coaching box.

For individual team seasons, there were 20 teams that were never caught when sending the runner during the period, led by the 2000 Giants, who sent 66 runners successfully.

Year    Team         Opp  Scores      OA   Hold%   Succ%
2000    SFN           79      66       0   0.165   1.000
2002    ANA           89      64       0   0.281   1.000
2005    DET           61      52       0   0.148   1.000
2003    ARI           58      52       0   0.103   1.000
2002    MIN           61      52       0   0.148   1.000
2004    ATL           52      48       0   0.077   1.000
2000    TEX           64      47       0   0.266   1.000
2000    NYA           55      47       0   0.145   1.000
2003    NYN           53      44       0   0.170   1.000
2001    KCA           59      44       0   0.254   1.000
2005    BAL           50      42       0   0.160   1.000
2005    HOU           49      42       0   0.143   1.000
2000    SDN           50      42       0   0.160   1.000
2002    MON           50      41       0   0.180   1.000
2001    NYA           51      41       0   0.196   1.000
2003    TEX           50      40       0   0.200   1.000
2002    PIT           50      40       0   0.200   1.000
2003    FLO           47      39       0   0.170   1.000
2005    CHN           53      37       0   0.302   1.000
2004    NYN           47      34       0   0.277   1.000

Although this list features the 2000, 2002, and 2003 World Champions and the 2001 AL champs, those teams at the bottom include the 2001 World Champion Arizona Diamondbacks.

Year    Team         Opp  Scores      OA   Hold%   Succ%
2001    ARI           47      36       5   0.128   0.878
2003    CHA           53      39       5   0.170   0.886
2005    MIN           57      40       5   0.211   0.889
2000    CLE           68      49       6   0.191   0.891
2001    BOS           57      41       5   0.193   0.891
2001    TBA           33      25       3   0.152   0.893
2002    KCA           65      50       6   0.138   0.893
2001    PIT           51      34       4   0.255   0.895
2000    ANA           65      43       5   0.262   0.896
2001    NYN           54      35       4   0.278   0.897

In looking through I couldn’t really identify any year to year correlation in success percentage, indicating that the success rate is largely due to factors out of the team’s control or that the variety of runners on a team has the effect of evening out the percentages. The Royals which are pretty much all over the board, are a typical example.

Year    Team         Opp  Scores      OA   Hold%   Succ%
2000    KCA           84      68       1   0.179   0.986
2001    KCA           59      44       0   0.254   1.000
2002    KCA           65      50       6   0.138   0.893
2003    KCA           67      57       2   0.119   0.966
2004    KCA           54      38       2   0.259   0.950
2005    KCA           56      50       1   0.089   0.980

There were a few teams who were more conservative than most in sending runners, as you can see from the list below.

Year    Team        Opp  Scores      OA   Hold%   Succ%
2003    LAN           42      28       1   0.310   0.966
2004    CIN           36      24       1   0.306   0.960
2005    CHN           53      37       0   0.302   1.000
2000    DET           71      49       1   0.296   0.980
2002    MIL           51      34       2   0.294   0.944
2005    OAK           59      40       2   0.288   0.952
2002    ANA           89      64       0   0.281   1.000
2001    NYN           54      35       4   0.278   0.897
2005    PHI           65      46       1   0.277   0.979
2004    NYN           47      34       0   0.277   1.000

And generally, except for the 2001 Mets, that strategy paid off by getting few runners thrown out.

Print Friendly
 Share on Facebook0Tweet about this on Twitter0Share on Google+0Share on Reddit0Email this to someone
« Previous: Three-and-Oh
Next: Around the Majors: Reds sign Dunn »

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>

Current day month ye@r *