How much time does this cast have left on stage?


Last Tuesday, Andrew wrote about the winter of the Duncan Dynasty in San Antonio. His article was pessimistic about how much the current core could contribute to an additional championship, saying “the league passed San Antonio by.’  Of course, this pessimism is not entirely unfounded.

The Spurs haven’t won the vaunted NBA title since 2007. Duncan is 34. Ginobili is 33 and Parker is 28 and coming off an injury-plagued season.  Andrew is probably right to suggest tempered expectations, but do these lowered expectations mean that the Spurs should rebuild? I suspect few will suggest rebuilding until there are very strong signs of decline from at least 2 of the Big 3.  After all, the arthritic Celtics came tantalizing close to their second championship in 3 years this past June.

If the current group of Spurs isn’t at the end of the line, how much longer do they have?

Measurement tools

In order to estimate how much each player can be expected to contribute to a team’s future, I utilized statistical performances over the last two years and age as of December 31, 2010.  I measured each player’s expected contribution using Mean Expected Championships Added (MECA).  MECA is the estimate of the expected championships above average a player would be expected to win if he was removed from his team and randomly placed on any team in the NBA.

Total MECA doesn’t equal total championships won for two reasons.  First, a player can collect a ring simply by being on the right team without any measurable positive contributions to the team. For this reason, poor players tend to have more championships than MECA. Secondly, using the Lakers as an example, one might say that since the Finals were so hotly contested, the Lakers without Kobe Bryant would have had a 30% chance of the winning the 2010 title. In this case, we can say he created 0.7 championships (this doesn’t mean his MECA is 0.7 because MECA adjusts for all potential teams and only accounts for the regular season, but the same logic applies).

However, we could also say that the Lakers without Pau Gasol (but with Kobe) may have only had a 30% chance of repeating.  Before estimating the other players’ championships added, we can see that adding Kobe’s and Pau’s championships created already exceeds the number of actual championships won. The more appropriate way to measure championships added is to always determine each player’s impact on point differential, adding them together (with slight adjustments) and then converting this new adjustment to wins and then championships.  We might find that the Lakers with neither Kobe or Pau would have a 5% chance at a title.

Data for Statistical Plus Minus

In order to be able to project future career expectations, I excluded all players who played this past season so that each observation had “completed career results.” I used data beginning with the 1979/80 season.  I estimated each players performance over the last two years using Advanced Statistical Plus Minus (ASPM). This is an estimate of a player’s value using box score and play-by-play statistics (see articles on Offensive and Defensive ASPM for further explanation).  I weighed 2010 two times as heavily as 2009 (also weighing by minutes for each respective season).

In order to account for players like Garrett Temple and Alonzo Gee, who only played a handful of minutes, I established a credibility factor for the weighted minutes. For players whose 2010 minutes * 2 + 2009 minutes exceed 10,000, I used the pure estimate described above.  Those whose minutes came in less than 10,000, I applied a factor accounting for the data’s credibility to the the initial estimate and added the remaining percentage multiplied by -3, which is approximately the average player’s ASPM.  This factor is (total weighted minutes/10,000)^0.5.

I’ll use Mr. Duncan to illustrate how this is applied. Tim Duncan played 2,525 minutes with a 6.3 ASPM in 2009 and 2,435 with a 5.1 ASPM in 2010. His resulting initial estimate is (6.3*2,525 + 5.1*2,435*2)/(2,525 + 2,435*2) = 5.5.  His total weighted minutes is equal to 2,525 + 2,435*2 = 7,395, which means the initial estimate must be adjusted by (7,395/10,000)^0.5 = 0.86. Finally, 0.86*(-3) is added to the total.  Duncan’s final 2 year weighted ASPM is 5.5*0.86  – 3*0.14 = 4.3. For prediction purpose, this weighted value predicts 2011 ASPM with higher accuracy than only using 2010 ASPM.

Graphing Statistical Plus Minus and age against MECA

Now that I have a reasonable estimation of a player’s expected value, I can utilize this 2-year weighted ASPM, supplemented with player age, to predict future MECA. Taking the average future MECA for each player of all respective ages and excluding all ages with fewer than 15 observations, I can produce the following graph displaying future MECA as age increases:

Similarly, the following graph shows how future MECA changes with increases to ASPM:

The most obvious feature apparent from observing these graphs is the curved progression of each. MECA decreases at a slower rate as players age and increases faster with improvements to ASPM.  Unlike my last post, in which I performed simple linear regression analysis (notice the straight trend line of the graph), a log transformation should be applied to the dependent variable (future expected MECA is dependent on ASPM and Age) in order to appropriately fit the data. This log transformation simply means that I chose the best regression model fitting the natural log of MECA.  The Graphs look much more linear after this adjustment.

Keep in mind the end values have fewer observations and are more innately variable.

Summary of Results

Fitting both independent variables (ASPM and Age) to the log transformation of Future MECA, the regression model of 2.95-0.179*Age+0.449*ASPM-0.017*Max(ASPM,0)^1.5 can be used to predict ln(Future MECA).  Converting this to something more meaningful, Tim Duncan’s estimate of future MECA can be estimated by e^(3.36-0.179*34+0.497*4.3-0.084*4.3^1.5) = 2.718^(-1.338) = 0.262.

The results of the other Spurs can be observed in the table below (I have also entered an estimate of future seasons, assuming all of these players play this upcoming season):

PLAYERPOSAgeYrsCareer MECA2010 ASPM2009 ASPMAdj 2yr ASPMAlt ASPMFuture SpanFuture MECAAlt Future MECA
Manu GinobiliSG3381.1927.
George HillPG2420.069-1.70.8-
Tim DuncanC34132.3796.
DeJuan BlairPF2110.019-1.2-2.0-
Matt BonnerPF3060.1913.
Tony ParkerPG2890.3763.8-2.8-
Alonzo GeeSG2310.008-1.0-2.6-
Garrett TempleSG2410.012-1.6-2.6-
Richard JeffersonSF3090.4120.1-1.2-
Antonio McDyessPF36140.3452.1-5.2-2.7-

Before I discuss the results, I want to point out the importance of remembering that all statistical analysis should be sandwiched between non-statistical reasoning. Usually, the process starts with a question and the experiment is designed to answer that question. In the least, the experiment should provide clarification for an observed issue in question.

Next is the statistical analysis, which often takes the longest.  Once results can be determined, the outputs are observed and the design is adjusted in an attempt to make the results more meaningful, obvious or interesting. Finally, the most important part is bringing the numbers back to reality. With new information, one needs to understand the potential driving forces contributing to these results. Sometimes, aspects that aren’t accounted for should be added to the conclusion. The interpretation can be different from person-to-person. None of them are completely right, but some of them are useful and closer to the truth than others.


Getting back to the above table, we see that Ginobili projects the highest, followed by George Hill, Duncan, DeJuan Blair, Matt Bonner and Tony Parker. However, we should keep in mind that this is a basic approximation of expectations. The most glaring problem with these numbers is that they do not focus on the fact that Parker’s number last year were likely hampered by injury. If we assume that he will be unaffected by past injuries, it’s reasonable to project his as the brightest future of anyone on this list.

As you see, Ginobili typically turns out pretty well in most statistical analysis. Of course, this statistical analysis doesn’t adequately account for man-to-man defense, especially on the perimeter.  Ginobili’s defensive reputation doesn’t nearly match his sterling defensive numbers and if you consider him to be a subpar man defender, his defensive value would likely be overrated (I’m not completely convinced either way at this point). Additionally, Manu’s minutes tend to be lower than expected based on his value per play and if this trend continues, his value will likely be lower than his projections.  DeJuan Blair projects well due to his young age and solid contributions last year, but this projection doesn’t factor in concerns about his knees.

Statistical similarity tests are another common method used for projections. This works well in some cases, but in my opinion, often focuses too much on results when the causes of these results might be more indicative of how a player ages. For example, looking at Tim Duncan I suspected he might age well since he relies on height and skills rather than athleticism. However, the list of statistically similar players tends to include players like Patrick Ewing, Alonzo Mourning, Artis Gilmore, Larry Nance, Kevin McHale and David Robinson. Unlike Duncan, Mourning, Nance and Robinson relied significantly on athleticism and Gilmore was several inches taller. Most of these players also seemed to have better natural outside shooting ability than Duncan.

I suspect that visual observations of player similarities should still play a significant role in player projections given the current state of available data. Robert Parish seems to best represent Duncan’s makeup of athleticism, shooting ability and length. Parish’s teammate, McHale also seems have many of the same skills and much of the same makeup as Duncan. However, at Duncan’s current age of 34, McHale began to suffer from injuries that likely brought his career to a premature halt. There is reason for optimism with Duncan’s longevity, but injuries can always be an issue, especially for older players. In my opinion, Parker seems to relate best to a combination of Isiah Thomas, without the same passing ability, and Andrew Toney (whose career also suffered from injuries).

Ginobili seems difficult to peg but might be most comparable to Clyde Drexler, Sidney Moncrief (another great player whose effectiveness was severely limited due to injuries) and Mitch Richmond. It’s interesting to note that with all these comparable players, several have been hampered by injuries late in their career. Perhaps a reduction in minutes for the big 3 will help preserve them for several more years.

  • Thaddeus Clark

    So as a team what are our chances as per MECA?

  • Ed Portis

    The gentleman writing all of this mathmatical analysis obviously is well educated and knows what he is talking about. I believe most of this colunns readers are strong Spurs fans who like brief but well articulated articles that give good quick analysis and opinion. I also imagine most of your readers did what I did-about 1/3 of the way through this they scratched their heads, got confused on formulas and quit reading the article! Like myself, they will probably begin to look elsewhere for their Spurs analysis! Please go back to what works best!!!

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  • rob

    I would assume that Richard Jefferson’s sub par season last year has a lot to do with his projection which is extremely low.

    How would that change if RJ were to have an expotentially better season this year compared to last being that you would use the same data from last year and this year to predict his future MECA?

    Could/would you disregard an exceptionally good season and bad season to better equate a more balanced asumption?

  • Ed

    A great American once said … “There are 3 kinds of lies…Lies, Damn lies and Statistics”.

  • Timothy Varner

    @Ed. We agree, he’s smart. Re: the what works best stuff, we’re planning an avalanche of that this season, so you’ll get your fill of the sort of stuff you appreciate. If advanced stats aren’t your thing, no worries. It’s only a small part of the program. If our usual content is too few and far between for you right now, blame it on the the offseason. Beginning next Monday, we’re back on all cylinders.

  • Andres

    Nice effort, but this article is completely useless, better luck next time!

  • ThatBigGuy

    Obviously, Bonner needs to start. This in depth analysis proves it! $4 million a year is such an amazing value for a guy with such amazing ASPM numbers.

  • GitErDun

    So after the detailed analysis – how well will the Spurs do this season?? All the analysis without a conclusion is basically worthless.

  • Mark H

    A lot of work went into this analysis, for which I am grateful, because statistics is one of man’s few defenses against chance. (Of course, the Spurs’ best defense against chance has been the big three.) Questions:

    1. Is there a way to estimate Splitter’s MECA?

    2. Is there some kind of baseline that we can use to better understand the Spurs’ MECA as established in the current analysis? For example, the average NBA player MECA or the MECA for the players from the playoff teams from the past two seasons?

    3. It would also be interesting to calculate the MECA for the big three on a rolling basis starting with the first season they played together. The results could then be compared with what actually happened in terms of rings.

  • jacko

    Hey pointdexter, youre talking way above our heads. How about some plain english? geez

  • Mike S

    Wow, Ed Porter! You couldn’t be more wrong about ME! I’m a huge Spurs fan, AND love math. What’s wrong with an article that reaches out and massages our brains a little? Don’t be so rough on the guy.

    Thanks for the great read, Advanced Stats Man!

  • Scott Sereday

    For those of you who found the material too much, I apologize for going too far into my methods and not focusing enough on the results.

    The results show how much each player has remaining in his career given his age and effectiveness the last two seasons. You can see that Duncan’s Career MECA is an outstanding 2.379 and he is projected to contribute an additional 0.262. Clearly, he is well past his midpoint, but his projection is still almost equivalent to McDyess’ total career. I used Alt ASPM to come up with Alt MECA. For Parker and Jefferson, I plugged in results similar to their performances 2 years ago and both saw future MECA increase, Parker significantly. In fact, if he returns to form, I’d conclude he is likely to have much more to contribute in the future than he contributed in the past.

    I’ll get more into a projection for the Spurs some other time. I’ll also try to include some sort of championship probability for 2011.

    Splitter’s projected MECA would have to be determined primarily from his effectiveness in Europe. I’ll be sure to have something on that before the season begins.

    All historical statistics for MECA can be found at this site:

  • mvg03

    If these stats and formulas make Bonner look good it must be flawed!!

  • rob

    Scott Sereday

    “The results show how much each player has remaining in his career given his age and effectiveness the last two seasons.”

    And a very good job at that. But when you only calculate the last two seasons…it seems that there might be some pertinent values that may be over and/or under emphasized. Point in case Richard Jefferson and Matt Bonner. It would seem that Bonner would be no where near as good as might be projected and Jefferson no where near as bad as projected.

    But that’s my “perceived” notion based on gut and not actual dynamics.

  • Dr. Love

    I’m about to have a braingasm from all the rosterbating.

  • Jim Henderson

    From the main post:

    “His article was pessimistic about how much the current core could contribute to an additional championship, saying “the league passed San Antonio by.’”

    First of all, Andrew was acknowledging that our “aging” core is simply no longer capable of carrying a team with a less than “stellar” supporting cast. And I don’t think his piece was “pessimistic” at all. Pessimism is when someone reflects on an issue by predominantly focusing on the “adverse” aspects of a situation, and thus inevitably comes up with unappealing conclusions. On the contrary, Andrews piece showed an understanding of the good and bad with the Spurs, and was simply willing to accept that the odds do not favor a bonafide title challenge for this team this year. That’s accepting and properly weighing all the facts as they currently exist. It is not “pessimistic”, but “realistic”, not dodging truth, but embracing inner authenticity with gratitude and perspective.

    On the data:

    The bottom line is that our two most proficient “ASPM guys” over the past two seasons by far, Ginobli & Duncan, are showing a steady decline in future MECA (even if incrementally) until about the age of 36, when a plateau appears to more clearly develop. It would be nice to see a MECA of last year for all players, particularly for those with positive ASPM’s, so that we can get a feel for whether the improving players in terms of future MECA can adequately offset the future MECA decline in our most productive players at present (Manu & TD). Since the team has not really come close to “title worthy” in the last couple years, on the surface this data does not appear to bode too well for Spur title aspirations over the next couple of years, UNLESS our young and relatively unexamined players make a significantly stronger contribution than the odds would typically confer.

  • Greyberger

    I really liked the article and thought it was very well documented with the links to make help understand the nitty-gritty.

    Honestly however to someone with no prior exposure to how SPM or APM work there is a brick wall in the middle, and nothing past it is going to make any sense.

    Even if the reader is familiar with SPM there are a lot of moving parts introduced in this analysis. Some are more sophisticated than others – like the problem of box score data being unable to realistically explain team defensive efficiency.

    Of course there’s a lot going on after SAPM is calculated, and it seems like the possibility of error (either in the statistical sense or human sense) would build with each step. Without a understanding of step one, it can be hard to invest the time and cost in squinting.

    I think you’ll find Spurs fans are educated and engaging and as willing to read about advanced stats as any fanbase, and more than most. We will need to take baby steps, however – many readers here have probably never really heard of +/-, even after many posts in this blog about it.

    Getting people to think of +/- data as explaining success and failure is I think a necessary step to getting them hooked on better versions of it and the work you can do with them.

  • Scott Sereday


    If we’re talking about ASPM or value per minute, it isn’t always about who looks better or even who IS better, it just looks at who helps the team more in their role. Bonner was more efficient last year, similarly productive when he played and the Spurs did better when he was on the court.

    Regarding perceptions, I like to think of not only why the statistics conflict with my perceptions, but why my perceptions conflict with the facts. Is it because Bonner looks so weird when he shoots? Is it because of Jefferson’s athleticism and success with the Nets? The first factor should probably be disregarded, but the second might be important at times.

    I’m not really sure if the visual plays a large part in the projection in this case. Jefferson might be more versatile, which helps for longevity, but Bonner is a tall shooter and neither height nor shooting really decrease with age. He might stick around a long time like Donyell Marshall and Sam Perkins.

  • Jim Henderson

    Looks like TP wants to go back to Summer play again next year:

  • McShane

    I think there are too many extraneous variables and individual variability in a player’s performance to use their last two years’ performance to predict their next year accurately.

    Your list of caveats tends to address many of these problems.

    I think the best we can glean from this is who will be most important to the Spurs next year, and most people can see that without statistical analysis.

    I’m interested to see what you come up with for the probability of winning a championship, and I hope you include other teams (Lakers, Heat, Magic, Celtics, Mavs, Thunder, Utah) for comparison.

  • Erik

    Well the season is in the hands of one young brazilian.

  • Bushka

    Loved the article. I have been on board the interesting metrics train for a few years now. I think it is what it is. An especially effective tool that should be taken advantage of but not relied upon solely.

    With a guy like Bonner the main issue with the general populace is they have enormous problems breaking away from stereotypes, and fundamentally inground prejudice. So often people will literally write “he hits one three per game and gets 5 rebounds, I could do that and play better defence myself”.

    He is tall white and looks awkward, shoots it weird and runs like a duck. But time and again the numbers say that we play better when he is on the court.

    I’m not advocating Bonner starts and plays big minutes.

    I do believe however, that by all reliable measures he has a valuable skillset we as a franchise should take advantage of. Obviously the front office agrees.

    Will be amazingly fun to see some of the articles that you contribute during the course of the season. You are going to have heaps of spurs fans who just refuse to believe the numbers, and i’m guessing some of your threads will be rather heated.

    Especially when Pop stops giving the rookies minutes sometime around mid December and you post up a statistically based graph showing who is producing.

    Rock on.

  • Titletown99030507

    For those of you who want Tony traded in the event we may lose him for nothing when the season is over. If that’s the case Trade now along with Bonner or McDyess for a first round future lottery pick and a proven big man or swing man. Risky but hey its better than getting nothing for Parker. He’s already told the Spurs FO he’s playing for France after this season. Kinda I don’t care what you say I’m leaving anyway after the season attitude.

  • GOfor5

    Wow. Since when did this blog become a convoluted stats sheet? I frequently used this site as an escape from my grueling school readings but now I feel like I just did another homework assignment. Articles like these are great once in a while…let’s not make it a habit, maybe??

    I appreciate the effort though. GO SPURS GO!

  • Colin

    Wow. A little too much computer guy and not enough realistic impression.

    EA sports style analyzation does not apply to actual games on the court.

  • Manolo Pedralvez

    Not all may appreciate it, but somewhere out there is a basketball fan cum statistician who must be agog over this piece. This off-the-wall articles are just what keeps our mental muscles working and keeps us coming back to this website for more.

  • Pop-a-vich

    STOP with the statistics

    As long as Timmy is on our side, there is every reason to hope for a 5th title

  • marcos4303

    Scott should cut off the explanations on how he gets to the formulas and results. We trust you Scott. Just a shorter introduction of what it is that you will show would be great and enough explanation for 99.99% of us dumb readers.
    The tables, and the conclussions are excellent!

  • ITGuy

    don’t forget about Manu.
    No Manu, no great playoff run.

    Go Spurs Go!!

  • Timothy Varner

    @Marcos4303 and all,

    Thanks for the feedback. We had an internal conversation that basically arrived at the same conclusion. Less explanation of method, more discussion of findings. We’ll get it right.

  • BlaseE

    Awesome. I look forward to reading your next piece on the subject.

    One thing that bothers me a little bit is that young players like Hill and Blair are successful enough to project long careers. Their MECA is likely to decrease as they come into their prime because they have less years to play, yet they will simultaneously become more valuable to winning a current (future) championship. Is there a prime championship span where a player is more likely to contribute to a title?

    A good example for my point might be OKC. Personally, I don’t think they are ready to win a championship. My guess is that their young lineup might lead the league (or be in the top 3 at the least) in total MECA, but the MECA isn’t explicitly referring to next season. They might be more likely to win a championship when their total MECA has decreased and adjusted average age has increased.

  • doggydogworld

    Gotta love logarithmic graphs on a basketball blog. Keep ’em coming!

  • CoyoteMan

    Scott & Tim – great stuff. Thanks for taking a creative risk here. This sort of analysis can yield some good insights. I look forward to seeing this synthesized into the normal content on this blog.

    So, let me see if I’m reading this right.

    1. The core should still provide a solid base for a championship run. (Tim’s & Manu’s strong MECA scores indicate they still provide strong “expected championship” contribution. MECA decreases at a slower rate as players age.).

    2. Jumps in ASPM from Tony (the other core member) and the others (RJ, Dejuan, George Hill, Tiago) will make the difference. (MECA increases faster with improved ASPM).

    That sounds about right to me. Tim & Manu play injury free, Tony bounces back this year, George, Dejuan, and Tiago (or others) give improved contributions and we’re in contention.

  • Scott Sereday

    Thanks to everyone for all the feedback.


    Future MECA should usually decrease just the same as future years will always decrease. The only way it will increase is if new information changes our opinion of the player. And it is definitely important to try to have your best players peak at the same time, in terms of championship expectations. Individual MECA or ASPM tends to peak and be fairly consistent between 26 and 31. After that, players start declining slowly and then begin to decline at a faster and faster rate. This can be inferred by looking at the results, but is not explicit.


    I suspect that the Spurs will be legitimate contenders for a couple more years. After that, it depends on how the young players develop. Clearly replacing Duncan’s and Ginobili’s decreasing value would be tough for any organization.
    Yes, MECA increases faster proportionally than ASPM.

  • BlaseE

    Thanks for the reply. This is making me think that Blair’s peak MECA value will be past Duncan and Manu’s time. Hill and Splitter however will be entering their theoretical peak years next season and the middle of this season respectively. Gary Neal also turns 26 a few days prior to preseason. It seems we will be getting prime MECA years out of all of three of these players (in spite of not having data on Neal or Splitter yet) over the next couple of seasons. Even Temple was a 4 year NCAA player so he is 24.

    As much emphasis as the Spurs have made to get younger, there still seems to be an appropriate amount of “peakage” to occur before the Duncan/Ginobili window closes.

    I think most Spurs fans agree that Blair and Hill could still improve, increasing their MECA with improved ASPM offsetting their decreasing NBA lifespans.

    All of this stuff makes logic sense, but its nice to see a stat, MECA, that shows the correlations.

  • Jim Henderson

    Scott Sereday
    September 21st, 2010 at 10:10 am

    “I suspect that the Spurs will be legitimate contenders for a couple more years.”

    Scott, with the above quote in mind, how do you respond to the following excerpt from my previous comment on this thread:

    “The bottom line is that our two most proficient “ASPM guys” over the past two seasons by far, Ginobli & Duncan, are showing a steady decline in future MECA (even if incrementally) until about the age of 36, when a plateau appears to more clearly develop. It would be nice to see a MECA of last year for all players, particularly for those with positive ASPM’s, so that we can get a feel for whether the improving players in terms of future MECA can adequately offset the future MECA decline in our most productive players at present (Manu & TD). Since the team has not really come close to “title worthy” in the last couple years, on the surface this data does not appear to bode too well for Spur title aspirations over the next couple of years, UNLESS our young and relatively unexamined players make a significantly stronger contribution than the odds would typically confer.” (e.g., Hill, Blair, Anderson, Splitter, Temple…).

  • Scott Sereday


    This is the Spurs 2010 (last year) individual MECAs.
    Player Name MECA
    Manu Ginobili 0.209
    Tim Duncan 0.120
    George Hill 0.058
    Matt Bonner 0.040
    Richard Jefferson 0.034
    Keith Bogans 0.026
    DeJuan Blair 0.019
    Roger Mason 0.015
    Garrett Temple 0.011
    Michael Finley 0.010
    Malik Hairston 0.010
    Tony Parker 0.009
    Antonio McDyess 0.007
    Ian Mahinmi 0.006
    Marcus Haislip 0.001
    Cedric Jackson 0.001
    Theo Ratliff -0.002

    The issue you bring up seems to be the big question on the Spurs frontier. Although Blair might improve at a faster rate than Duncan declines, since Duncan’s value is currently more significant, this nets out to a overall decline. This might also be the same for Ginobili vs Hill. Of course, you should remember that if Parker was healthy the Spurs would have been decently better last year. Additionally, new players like Splitter and Anderson are pickups that can only be expected to improve their chances.

    In summary, I would say, if the Spurs don’t do anything, they will obviously steadily decline, but quality off-seasons can make them significant factors over the next few years. (It’s always going to take some level luck to actually win everything.) Beyond that, a few young players will need to exceed expectations, but the same can be said for almost any team with aging stars.

  • Jim Henderson


    Thanks for the data (are the numbers MECA from last year?), and the balanced response. You’re not only a wiz with the stats, but a good writer as well. Glad to have you on board the 48MOH ship.

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