1
NBA Discussion / Re: Stick a fork in 'em!
« on: June 15, 2014, 11:21:14 PM »
Congrats Spurs and their fans. At times this post season they were an absolute machine.
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2
NBA Discussion / Re: ziggy; Jacoby Ellsbury
« on: October 30, 2013, 07:49:39 PM »My nephew and brother went to Jacoby's wedding reception, and they both agreed Pedroia, Lester, and couple of others were engaging, and respectful people. Some though were not.
Who were the dicks, Zig???
One is no longer a Red Sox, involved in a big trade, who was a big fried chicken fan, with the initials of JB. Another is a member of the rotation with the initials CB. Those were the 2 worst, and there were several other who you weren't dicks per se, but they viewed everybody at the reception as clearly beneath them. Pedroia on the other hand was very engaging, came right up to my nephew and chatted with him for 10-15 minutes, very unpretentious. Lester was less forward, but very respectful.
3
NBA Discussion / Re: ziggy; Jacoby Ellsbury
« on: October 25, 2013, 01:05:13 PM »
Well it was truly bitter and sweet! I have been Tiger fan for 45 years. I sucked it up when they lost 119, and we 22 years between World Series appearances. I was rooting for the Tigers to win and for Jacoby to win the Series MVP.
As far as WS I have always been a fan of the Cards, they are such a good organization. I do not care for a number of the Red Sox players (Gomes, Victorino, Lackey, Bucholtz, Salty). At the same time the Sox do have some players who I respect. My nephew and brother went to Jacoby's wedding reception, and they both agreed Pedroia, Lester, and couple of others were engaging, and respectful people. Some though were not.
In the end though I will root for Jacoby to get another ring. So Red Sox all the way!!
As far as WS I have always been a fan of the Cards, they are such a good organization. I do not care for a number of the Red Sox players (Gomes, Victorino, Lackey, Bucholtz, Salty). At the same time the Sox do have some players who I respect. My nephew and brother went to Jacoby's wedding reception, and they both agreed Pedroia, Lester, and couple of others were engaging, and respectful people. Some though were not.
In the end though I will root for Jacoby to get another ring. So Red Sox all the way!!
4
NBA Discussion / Re: 2013 Draft - Cody Zeller
« on: May 24, 2013, 05:59:33 PM »
Since I can't get this to format very well here, you can go to Blazers Edge and see essentially the same thing.
Cody Zeller
http://www.blazersedge.com/2013/5/24/4362908/cody-zeller-comparable-analysis
Here is also one for Steven Adams
http://www.blazersedge.com/2013/5/24/4363692/steven-adams-comparable-analysis
Here is also one for Ben McLemore
http://www.blazersedge.com/2013/5/24/4363848/ben-mclemore-comparable-analysis
Cody Zeller
http://www.blazersedge.com/2013/5/24/4362908/cody-zeller-comparable-analysis
Here is also one for Steven Adams
http://www.blazersedge.com/2013/5/24/4363692/steven-adams-comparable-analysis
Here is also one for Ben McLemore
http://www.blazersedge.com/2013/5/24/4363848/ben-mclemore-comparable-analysis
5
NBA Discussion / 2013 Draft - Cody Zeller
« on: May 24, 2013, 01:05:38 AM »
I hope this displays OK, if not anyone have any ideas on how to make it better
CODY ZELLER
First I am going to include a table showing Cody Zeller?s Physical Attributes, and then how those compare to the average player of his general height and weight.
Now this is how those relate to other players of his general height and weight
So Cody Zeller?s weight relative to his height means he weighs 10 lbs less than an average player of his height. His reach is 4.24? less than ?average?, his wingspan is 4.16? less than average, but his no step vertical is 9.53? greater than ?average?, he did the ? court sprint 0.12 seconds faster than ?average?, and did the agility drill 0.84 faster than average. In short for a player of his general size Cody Zeller has poor to very poor length, but he is very good to exceptional athletically.
Here is a list of recent NBA draftees who were the most similar to Cody Zeller physically, and the degree of physical similarity.
When considering Cody Zeller?s physical attributes, and his Freshman season the two best seasons of total comparability are;
So in short
Very Best Case Comps - Derrick Coleman, Christian Laettner 15%
Likely Best Case - Dales Davis, Raef LaFrentz 12%
Most Likely - Matt Geiger, Lorenzen Wright, Terry Mills 40%
Likely Worst Case - Cherokee Parks, Alaa Abdelnaby 18%
Absolute Worst Case - Donald Hodge, Derrick Alston 15%
This is the projected statistical line for his first 3 seasons;
Overall Cody Zeller will be a league about a league average player for his first 3 NBA seasons. He will be a highly efficient offensive player (112.3 Points per 100 possessions, 15.4 points per 36 minutes, 53.4% true shooting %), but a very poor defensive player (allow 111 points per 100 possessions). He will be a slightly below average rebounding big man, but will have a reasonable number of blocks, and will not be overly foul prone.
CODY ZELLER
First I am going to include a table showing Cody Zeller?s Physical Attributes, and then how those compare to the average player of his general height and weight.
| Name Height Inches no Shoes Height Inches w/shoes Weight Body Fat Hand Length Hand Width Wingspan Inches Reach in Inches No Step Vert Reach in Inches Max Vert Reach in inches No Step Vert Max Vert Bench Agility Sprint Cody Zeller 83 84.25 230 4.8% 8.5 10.5 83 106 142 143.5 35.5 37.5 10.82 3.15 |
Now this is how those relate to other players of his general height and weight
| Name Weight > than standard (in lbs) Body Fat < than Standard (as a % of BF) Reach > than standard (in inches) Wingspan > than standard (in inches) Vertical > than standard (in inches) Speed > than standard (in sec) Agility > than standard (in sec) Cody Zeller -10 -3.15% -4.24 -4.16 9.53 0.12 0.84 |
So Cody Zeller?s weight relative to his height means he weighs 10 lbs less than an average player of his height. His reach is 4.24? less than ?average?, his wingspan is 4.16? less than average, but his no step vertical is 9.53? greater than ?average?, he did the ? court sprint 0.12 seconds faster than ?average?, and did the agility drill 0.84 faster than average. In short for a player of his general size Cody Zeller has poor to very poor length, but he is very good to exceptional athletically.
Here is a list of recent NBA draftees who were the most similar to Cody Zeller physically, and the degree of physical similarity.
| Jason Smith 95.46% Perry Jones 93.62% Jon Leuer 92.81% Joakim Noah 92.55% Arnett Moultrie 91.83% Blake Griffin 91.82% Kevin Pittsnogle 91.80% Mason Plumlee 91.46% Andrea Bargnani 91.44% Tyler Zeller 90.92% Pops Mensah-Bonsu 90.78% Thaddeus Young 90.75% Harrison Barnes 90.72% Miles Plumlee 90.63% Jeff Taylor 90.61% Chris Anstey 90.61% |
When considering Cody Zeller?s physical attributes, and his Freshman season the two best seasons of total comparability are;
| Cody Zeller 19 Big Ten Player Season League Statistical Similarity Donald Hodge 20 Atlantic 10 94.1% Dale Davis 19 Atlantic Coast 93.7% Dale Davis 20 Atlantic Coast 93.8% Derrick Coleman 19 Big East 93.5% Cherokee Parks 20 Atlantic Coast 93.4% Lorenzen Wright 19 Conference USA 93.5% Adam Keefe 19 Pacific 12 94.3% Cherokee Parks 21 Atlantic Coast 94.0% Donald Hodge 21 Atlantic 10 92.0% Paul Davis 19 Big Ten 95.2% Alaa Abdelnaby 21 Atlantic Coast 96.3% Othella Harrington 19 Big East 95.0% Terry Mills 20 Big Ten 92.7% Matt Geiger 22 Atlantic Coast 93.8% Lorenzen Wright 20 Conference USA 93.0% D.J. White 19 Big Ten 93.8% Derrick Alston 19 Atlantic 10 92.8% Terry Mills 22 Big Ten 93.0% Derrick Coleman 20 Big East 92.5% Calvin Booth 19 Big Ten 89.7% |
| Cody Zeller 20 Big Ten Player Season League Statistical Similarity Donald Hodge 20 Atlantic 10 94.7% Cherokee Parks 21 Atlantic Coast 94.8% Dale Davis 20 Atlantic Coast 93.5% Lorenzen Wright 19 Conference USA 94.8% Lorenzen Wright 20 Conference USA 94.1% Christian Laettner 20 Atlantic Coast 93.4% Alec Kessler 22 Southeastern 93.5% Clifford Rozier 20 Big East 94.5% Calvin Booth 22 Big Ten 93.7% Othella Harrington 19 Big East 96.5% Adam Keefe 19 Pacific 12 95.4% Anthony Avent 21 Big East 96.1% Terry Mills 22 Big Ten 93.6% Dale Davis 19 Atlantic Coast 92.6% Cherokee Parks 20 Atlantic Coast 92.2% Derrick Coleman 20 Big East 92.9% Othella Harrington 20 Big East 95.6% Raef LaFrentz 20 Big-12 93.3% Derrick Coleman 19 Big East 93.2% Donald Hodge 21 Atlantic 10 91.0% |
So in short
Very Best Case Comps - Derrick Coleman, Christian Laettner 15%
Likely Best Case - Dales Davis, Raef LaFrentz 12%
Most Likely - Matt Geiger, Lorenzen Wright, Terry Mills 40%
Likely Worst Case - Cherokee Parks, Alaa Abdelnaby 18%
Absolute Worst Case - Donald Hodge, Derrick Alston 15%
This is the projected statistical line for his first 3 seasons;
| Season Shooting Statistics Totals FG FGA FG% 2P 2PA 2P% 3P 3PA 3P% FT FTA FT% TS% eFG% Cody Zeller 1 268 560 48.0% 264 546 48.5% 4 13 30.0% 165 232 70.9% 52.8% 48.4% Cody Zeller 2 270 562 48.2% 263 539 48.9% 7 23 29.5% 161 222 72.6% 53.2% 48.8% Cody Zeller 3 314 653 48.2% 307 623 49.2% 8 29 26.2% 209 277 75.5% 54.0% 48.8% 3 Year Average 285 594 48.1% 279 571 48.9% 6 22 28.5% 179 245 73.1% 53.4% 48.7% Season Accumulation Stats Totals ORB DRB TRB AST STL BLK TOV A/TO PF PTS Cody Zeller 1 163 250 406 73 47 56 109 0.67 183 705 Cody Zeller 2 175 304 474 91 45 71 108 0.85 208 708 Cody Zeller 3 176 305 473 107 48 77 120 0.89 213 845 3 Year Average 172 288 452 91 47 68 113 0.81 202 756 Season Shooting Statistics per 36 Minutes FG FGA FG% 2P 2PA 2P% 3P 3PA 3P% FT FTA FT% TS% eFG% Cody Zeller 1 5.86 12.20 48.0% 5.77 11.91 48.5% 0.09 0.29 29.7% 3.58 5.05 70.9% 52.8% 48.4% Cody Zeller 2 5.51 11.45 48.2% 5.38 10.98 49.0% 0.14 0.46 30.0% 3.28 4.51 72.6% 53.2% 48.8% Cody Zeller 3 6.02 12.50 48.2% 5.87 11.94 49.2% 0.15 0.56 26.2% 4.00 5.30 75.5% 54.0% 48.8% 3 Year Average 5.8 12.1 48.1% 5.7 11.6 48.9% 0.1 0.4 28.6% 3.6 5.0 73.1% 53.4% 48.7% Season Accumulation Stats per 36 Minutes ORB DRB TRB AST STL BLK TOV A/TO PF PTS Cody Zeller 1 3.56 5.43 8.83 1.60 1.02 1.22 2.37 0.67 4.00 15.39 Cody Zeller 2 3.58 6.19 9.66 1.86 0.92 1.44 2.20 0.85 4.26 14.44 Cody Zeller 3 3.37 5.84 9.06 2.05 0.93 1.47 2.29 0.89 4.08 16.19 3 Year Average 3.5 5.8 9.2 1.8 1.0 1.4 2.3 0.81 4.1 15.4 Season Usage Stats ORB% DRB% TRB% AST% STL% BLK% TOV% USG% Cody Zeller 1 10.8% 16.8% 13.5% 6.4% 1.4% 2.1% 14.5% 18.2% Cody Zeller 2 10.2% 17.3% 13.5% 7.7% 1.4% 2.6% 14.0% 18.0% Cody Zeller 3 10.6% 18.0% 14.1% 8.4% 1.3% 2.7% 13.6% 19.6% 3 Year Average 10.5% 17.4% 13.7% 7.5% 1.4% 2.5% 14.0% 18.6% Season Advanced Measurements PER ORtg DRtg OWS DWS WS WS/48 Cody Zeller 1 14.20 110.5 112.2 1.13 1.62 2.95 0.083 Cody Zeller 2 14.77 112.0 111.5 1.70 1.59 3.42 0.088 Cody Zeller 3 16.43 114.3 109.5 2.54 2.24 4.95 0.117 3 Year Average 15.18 112.3 111.0 5.4 5.4 11.32 0.097 |
Overall Cody Zeller will be a league about a league average player for his first 3 NBA seasons. He will be a highly efficient offensive player (112.3 Points per 100 possessions, 15.4 points per 36 minutes, 53.4% true shooting %), but a very poor defensive player (allow 111 points per 100 possessions). He will be a slightly below average rebounding big man, but will have a reasonable number of blocks, and will not be overly foul prone.
6
NBA Discussion / 2013 NBA Draft - An analysis of a players best comparables
« on: May 23, 2013, 11:38:27 PM »
I have been working on a project revolving around the NBA draft for quite a while, at this point is has been longer than a year. At some point I want to create a website, and this would be the basis for much of the web sites content, but I would have other things as well. I am not ready to do a website at this point, so I thought I would publish some of what I have done here.
My concept is pretty simple. For years I have read a lot about the players coming into the NBA draft, and one thing you see with the evaluation of incoming collegiate and Euro players is an attempt to find comparable players in the NBA to the potential draftee. There are lots of attempts to describe players relative to one or more ?comps?, and you see this much more with basketball players than with football or baseball players. The process of determining ?Comps? though has always seemed to me to be a very subjective measurement, and some players seem to have multiple ?Comps? that are pretty diverse. I decided to take on a project to make this ?Comp? determination process far more objective, and the project has grown and grown and grown in the last 15 or so months I have been working on it.
I will try and express what I am doing metaphorically.
1.) My son described it his way, ?Think of a player as a color, say blue. Now exactly what shade of blue is he? Player A is Sky Blue, Player B is Royal Blue, Player C is Navy Blue. This draftee is a little of all three of those shades of blue, but not actually any one of those 3 shades?.
2.) My son described it another way, ?There are no true synonyms, no two words mean exactly the same thing. There are a lot of words that are similar, some very similar, and you can describe something pretty effectively using a multitude of synonyms, but it will not be exact. With a player you can use ?Comps? to pretty effectively describe a player, but not exactly?.
3.) A third way to express my effort is to think of the universe of NBA players as a 3 dimensional cube. Each and every player will have some specific place inside that cube that perfectly describes them. In a 3 dimensional circle around that player will reside other players, and those players can best be described as his ?Best Comparables?.
The way I have come to determine a player?s ?Comps?, is by developing a very rigorous process of numerically describing that target player, as holistically as possible. Now I don?t have access to some data, so I used whatever data I could find about the population of NBA players and potential NBA players.
The basic components of this are;
1.) The physical attributes of the player, as measured at the NBA combine, basically height, weight, wingspan, reach etc.
2.) The NBA combine also does testing on a players ?raw athleticism?, by measuring vertical leap, speed, and agility, and some others.
3.) I studied the relationship between some of these various raw measurements, and found the relationship between them, and from that I can place a player?s physical attributes and athleticism into a context. For instance, Cody Zeller?s vertical leap was the highest of any player over 6-9 ever at the combine. That is interesting, but exactly how much of a better leaper is he than you would expect for a player of his height? I have calculated what I believe is a fair representation of that.
4.) A player?s college, or European League stats.
5.) The player?s age.
6.) The player?s competition level.
In total I have found 123 different discreet descriptive measurements of a player for his seasons prior to his NBA seasons (and in some European player?s data on seasons after they played in the NBA). I found that data (or at least as much of that data as I could find) on almost every player that has played in the NBA since 1990, as well as a number of other players who played prior to 1990. In total my database includes over 4,000 player seasons.
For each of these player seasons, I found the relationship between each player season and every other player season. These relationships are expressed as a % of similarity between one player and each and every other player. For instance you have a target player, and you compare him to 2 other players. The target player averages 10 points per game, and player A averages 12, and Player B averages 8. In both of these cases (Player A to the Target Player and Player B to the Target Player) the degree of similarity of PPG is 80% similar. The actual math is more complex, and not exactly like this, but I don?t want to get caught up in the minute?, so this is in general the way the process works. I find the relationship of a target player to all other players for all 123 measurements, and then develop a composite degree of similarity for each target player.
The composite measurement of similarity then defines a player?s ?Comps?. From this group of comps, I find the specific relationship between the target players and each of the comps, based upon their relative collegiate or Euro seasons, and use that in conjunction with the ?Comps? actual NBA stats to calculate a predicted NBA stat line for the target player for his first 3 season in the NBA.
I tested the methodology on the 2012 draft class, and some selected players from the 2011 draft class. Overall the predicted stat lines have been pretty accurate, though obviously not perfect. I would say that they have been directionally very accurate, highly accurate for some categories, good for other, all the way down to marginally/reasonably accurate on a few stat categories. Some players were extremely accurate, other players very accurate, some accurate, and a few would be described as marginally accurate. The marginally accurate were generally due to very low minutes played. I have had a number of iterations to this predicted stat line, and I have continually improved the tool, but it is certainly a work in progress, and I have a number of ideas to make it more accurate.
So as I said above, I am going to publish my list of best ?Comps? for a number of this year?s top 100 prospects, and give some other data about the various potential draft picks, and my 3 year NBA stat projection, and then eventually give my ranking of the players as I see them using this methodology.
One last thing, the data I used to develop this tool was freely available on the web, and I found and used data from a number of sites. I do want to acknowledge Draft Express and Basketball Reference, as the two main sources, and also Dean Oliver?s book Basketball on Paper. Derek, please pass along my sincere appreciation to Jonathan Givoney for all that he has done with Draft Express.
I hope you find this interesting, it has certainly been a lot of fun to do.
My concept is pretty simple. For years I have read a lot about the players coming into the NBA draft, and one thing you see with the evaluation of incoming collegiate and Euro players is an attempt to find comparable players in the NBA to the potential draftee. There are lots of attempts to describe players relative to one or more ?comps?, and you see this much more with basketball players than with football or baseball players. The process of determining ?Comps? though has always seemed to me to be a very subjective measurement, and some players seem to have multiple ?Comps? that are pretty diverse. I decided to take on a project to make this ?Comp? determination process far more objective, and the project has grown and grown and grown in the last 15 or so months I have been working on it.
I will try and express what I am doing metaphorically.
1.) My son described it his way, ?Think of a player as a color, say blue. Now exactly what shade of blue is he? Player A is Sky Blue, Player B is Royal Blue, Player C is Navy Blue. This draftee is a little of all three of those shades of blue, but not actually any one of those 3 shades?.
2.) My son described it another way, ?There are no true synonyms, no two words mean exactly the same thing. There are a lot of words that are similar, some very similar, and you can describe something pretty effectively using a multitude of synonyms, but it will not be exact. With a player you can use ?Comps? to pretty effectively describe a player, but not exactly?.
3.) A third way to express my effort is to think of the universe of NBA players as a 3 dimensional cube. Each and every player will have some specific place inside that cube that perfectly describes them. In a 3 dimensional circle around that player will reside other players, and those players can best be described as his ?Best Comparables?.
The way I have come to determine a player?s ?Comps?, is by developing a very rigorous process of numerically describing that target player, as holistically as possible. Now I don?t have access to some data, so I used whatever data I could find about the population of NBA players and potential NBA players.
The basic components of this are;
1.) The physical attributes of the player, as measured at the NBA combine, basically height, weight, wingspan, reach etc.
2.) The NBA combine also does testing on a players ?raw athleticism?, by measuring vertical leap, speed, and agility, and some others.
3.) I studied the relationship between some of these various raw measurements, and found the relationship between them, and from that I can place a player?s physical attributes and athleticism into a context. For instance, Cody Zeller?s vertical leap was the highest of any player over 6-9 ever at the combine. That is interesting, but exactly how much of a better leaper is he than you would expect for a player of his height? I have calculated what I believe is a fair representation of that.
4.) A player?s college, or European League stats.
5.) The player?s age.
6.) The player?s competition level.
In total I have found 123 different discreet descriptive measurements of a player for his seasons prior to his NBA seasons (and in some European player?s data on seasons after they played in the NBA). I found that data (or at least as much of that data as I could find) on almost every player that has played in the NBA since 1990, as well as a number of other players who played prior to 1990. In total my database includes over 4,000 player seasons.
For each of these player seasons, I found the relationship between each player season and every other player season. These relationships are expressed as a % of similarity between one player and each and every other player. For instance you have a target player, and you compare him to 2 other players. The target player averages 10 points per game, and player A averages 12, and Player B averages 8. In both of these cases (Player A to the Target Player and Player B to the Target Player) the degree of similarity of PPG is 80% similar. The actual math is more complex, and not exactly like this, but I don?t want to get caught up in the minute?, so this is in general the way the process works. I find the relationship of a target player to all other players for all 123 measurements, and then develop a composite degree of similarity for each target player.
The composite measurement of similarity then defines a player?s ?Comps?. From this group of comps, I find the specific relationship between the target players and each of the comps, based upon their relative collegiate or Euro seasons, and use that in conjunction with the ?Comps? actual NBA stats to calculate a predicted NBA stat line for the target player for his first 3 season in the NBA.
I tested the methodology on the 2012 draft class, and some selected players from the 2011 draft class. Overall the predicted stat lines have been pretty accurate, though obviously not perfect. I would say that they have been directionally very accurate, highly accurate for some categories, good for other, all the way down to marginally/reasonably accurate on a few stat categories. Some players were extremely accurate, other players very accurate, some accurate, and a few would be described as marginally accurate. The marginally accurate were generally due to very low minutes played. I have had a number of iterations to this predicted stat line, and I have continually improved the tool, but it is certainly a work in progress, and I have a number of ideas to make it more accurate.
So as I said above, I am going to publish my list of best ?Comps? for a number of this year?s top 100 prospects, and give some other data about the various potential draft picks, and my 3 year NBA stat projection, and then eventually give my ranking of the players as I see them using this methodology.
One last thing, the data I used to develop this tool was freely available on the web, and I found and used data from a number of sites. I do want to acknowledge Draft Express and Basketball Reference, as the two main sources, and also Dean Oliver?s book Basketball on Paper. Derek, please pass along my sincere appreciation to Jonathan Givoney for all that he has done with Draft Express.
I hope you find this interesting, it has certainly been a lot of fun to do.
7
NBA Discussion / Re: LAL vs. LAC
« on: March 16, 2013, 06:28:52 PM »
Do Yankee fans root for the Mets?
Do Cubs fans root for the White Sox?
Do Alabama fans root for Auburn?
Do Beaver fans root for the Ducks?
Do Trojan fans root for the Bruins?
Did Russians root for Americans?
Do Republicans root for Democrats?
Do Cubs fans root for the White Sox?
Do Alabama fans root for Auburn?
Do Beaver fans root for the Ducks?
Do Trojan fans root for the Bruins?
Did Russians root for Americans?
Do Republicans root for Democrats?
9
NBA Discussion / Re: The Long, Slow, Sad Decline
« on: February 11, 2013, 01:50:38 PM »
I am doing well, all things considered. My relationship with all my children is really strong and positive, one of love and mutual respect and trust. I am developing a strong and positive relationship with my daughter-in-law. I am very happy and thankful for all of that.
As regards ex-wife #2, well we barely speak, and we have no relationship. I am doing better with regards to my divorce, but the deep bitterness remains. My counselor said to me a couple of years ago that perhaps I am holding onto the bitterness because that is all I have left. Perhaps that is the case, but I will never allow her to "F" me ever again. If my bitterness is my defense mechanism to keep that from happening I am content with it. I am alone and I am content with that at this point. I keep everyone at arms length, with the exception of my children. Maybe I am creating lonely future for myself, but I will deal with the future, in the future.
As far as the rest of things, I am working hard, using a number of the things I learned in my MBA everyday in my work life. I get great satisfaction from that.
In my off times I have been working on a project that I has interested me for a long time. It is about evaluating NBA draft prospects. I have learned a lot, and expect to learn a lot more. I hope at some point to write a blog. I could probably start now, but I want refine my tools and ideas more. Every time I think I am making a breakthrough I look at it a different way, and my models and concepts start to change. Each time that I happens I think things improve, but I need to keep on working on it. It is something I am working on with my oldest son, and he is just as interested in it, which makes it all the more enjoyable.
Reality, I hope things are going well for you!
ziggy
As regards ex-wife #2, well we barely speak, and we have no relationship. I am doing better with regards to my divorce, but the deep bitterness remains. My counselor said to me a couple of years ago that perhaps I am holding onto the bitterness because that is all I have left. Perhaps that is the case, but I will never allow her to "F" me ever again. If my bitterness is my defense mechanism to keep that from happening I am content with it. I am alone and I am content with that at this point. I keep everyone at arms length, with the exception of my children. Maybe I am creating lonely future for myself, but I will deal with the future, in the future.
As far as the rest of things, I am working hard, using a number of the things I learned in my MBA everyday in my work life. I get great satisfaction from that.
In my off times I have been working on a project that I has interested me for a long time. It is about evaluating NBA draft prospects. I have learned a lot, and expect to learn a lot more. I hope at some point to write a blog. I could probably start now, but I want refine my tools and ideas more. Every time I think I am making a breakthrough I look at it a different way, and my models and concepts start to change. Each time that I happens I think things improve, but I need to keep on working on it. It is something I am working on with my oldest son, and he is just as interested in it, which makes it all the more enjoyable.
Reality, I hope things are going well for you!
ziggy
11
NBA Discussion / Merry Christmas all,,
« on: December 24, 2012, 11:52:39 PM »
Ho ho ho!! Have a great Christmas everyone!!
12
NBA Discussion / Re: I am bummed, my Ducks gagged on a soggy piece of bread
« on: December 24, 2012, 11:51:40 PM »What is this I hear about violations? It's sounds ominous!
Yeah they will some sanctions, no doubt. The crimes aren't as bad as Reggie Bush and USC but his crimes were his, not the staff. The Ducks crimes are not as bad, but it involves the coaches, so the penalties could be just as severe. It was a great run while it lasted.
14
NBA Discussion / I am bummed, my Ducks gagged on a soggy piece of bread
« on: November 19, 2012, 02:52:26 AM »
It was theirs for the taking, but Standford stepped up and we gagged. Well at least USC chocked it 
.
.
15
NBA Discussion / Re: Mike Brown
« on: November 03, 2012, 05:41:00 PM »
Ok Dan take a deep breath and step away from the weapons. Remember this always "Serenity Now, Serenity Now, Serenity Now".
After watching my Blazers light them up, it seems to me the defense is a bigger issue than the offense.
After watching my Blazers light them up, it seems to me the defense is a bigger issue than the offense.