In sports, great offense is about brilliance. Steve Nash creating passing lanes. Peyton Manning audibling at the line. Sidney Crosby, as I understand it, doing pretty much anything.
Defense, on the other hand, is not so glamorous. It pretty much consists of not making any mistakes. This makes it difficult for casual fans to appreciate defenders who are not on their own team; the MVP of any given game is probably going to be an attacking player, for a moment of brilliance. Only over the course of the season does the defender’s ability to avoid mistakes look as good.
In soccer, which does not have the wealth of statistics available in most American sports, it is even harder to tell.
Sometimes, then, the best way to observe the quality of defensive players is to see what happens when they’re gone. Manchester United and Chelsea, teams with an embarrassingly large number of attacking options, were derailed last season with injuries to defenders. In Nemanja Vidic’s absence, AC Milan’s Kaka sent the Red Devils crashing out of the Champions League. Man U’s second choice defenders were running into each other trying to stop him. Literally. You can see it on YouTube.
Meanwhile, Chelsea had the same problem in both league and European competitions. When John Terry and Ricardo Carvalho are both playing, Petr Cech becomes the best goalkeeper in the world, Frank Lampard becomes a European Footballer of the Year finalist, and Chelsea becomes unstoppable. When they’re not, things are different.
That’s what happened this week. Although they escaped both games with Ws, they looked vulnerable. They gave up two goals to newly-promoted Birmingham at home. They were a post’s width away from being run off the field in the first half at Reading. Unless Terry and Carvalho make miraculous recoveries, Chelsea will be in serious trouble this weekend at Liverpool.
Liverpool, incidentally, was great. The team’s depth was on display, with new signings Fernando Torres and Ryan Babel looking especially good. The Reds’ goal didn’t look threatened at any point; the game-tying goal they did concede was a freak PK on a play that wasn’t really even dangerous. And when that happened, local superman Steven Gerrard cleaned it up by drawing a foul and then dropping the ensuing free kick in between the post, crossbar and keeper’s hand, a space approximately the size of an envelope.
The other team to impress was Manchester City. They got a good bit of offensive creativity from midfielder Elano of Brazil, and wingers Martin Petrov of Bulgaria and Stephen Ireland of Ireland. They have Peter Schmeichel’s son in goal. Most importantly of all, at the back, Richard Dunne and Micah Richards look like a pair that isn’t going to be making a lot of mistakes.
Wednesday, August 15, 2007
Wednesday, August 8, 2007
Mike, On Rooting for A-Rod (MLB)
Editor's Note: This column title begins with the author's name, as will all future guest columns. Of which there will hopefully be many.
I never thought I’d actually get to the point in my life where I’d say this, but I’m rooting for Alex Rodriguez.
Hold on. Before you all chuck rotten vegetables at me, I did not say “New York Yankees.” I refuse to ever root for the bastards of baseball. A-Rod, however, has my full support.
Why?
Because he needs to pass Barry Bonds.
I wrote an article in October of 2005 for this very website that pleaded with Bonds, whom WFAN radio personality Steve Somers refers to simply as “Barroid,” to retire. He was currently at 708 homeruns, and I didn’t want to see him hit 709, much less 715 or 756. Unfortunately, he hit both of those marks, and implied recently that he’s even considering returning for another season after this one because he finds himself less than 100 hits shy of 3,000 for his career. According to Barry Balco, his godfather Willie Mays has always wanted to see Bonds get to that benchmark, even more so than Aaron’s record.
Wake me up when I should care.
Honestly, I’m sick of even talking about this person, but it’s the hot topic in sports, so for my return column, there wasn’t much of a better idea. Here’s the thing: Bonds is a liar. Bonds is a cheat. Bonds is an arrogant, obnoxious individual who cares about no one besides himself. For those reasons, even more than the steroids, I dislike him.
The problem I have is that Bonds was a Hall-of-Famer before he ever used performance enhancing drugs. Look at the numbers he’s amassed: career .298 average, 514 stolen bases, and a .444 OBP. Some of those are a bit inflated because of the ‘roids, but especially with regards to the SB numbers, most are pre-1998, i.e. pre-McGwire and Sosa. Bonds was widely regarded, along with Ken Griffey Jr., as the premier baseball player of his generation. In ’98, however, it was Sosa and McGwire who captivated audiences and garnered the national media attention with the great home run chase, and Bonds couldn’t handle it. Someone told him he could do what those two did, and Barry’s ego being what it is, he went after it.
Don’t get me wrong, there’s a lot of blame to go around with this. Bud Selig and MLB executives for turning a blind eye as the game tried to rebound from the strike, which was partly their fault anyway. The other half of the blame, at least with regards to the strike and disregard for drug testing, goes to Donald Fehr and the Players’ Association. Regardless of that, however, Bonds could still have been just like Cal Ripken Jr. or Tony Gwynn, who were both recently inducted into the Hall, or even like Griffey, who with all the injuries and lack of upper body growth clearly steered clear of the juice. Those guys simply kept their egos in check and relied on their God-given talent to hit a little white ball with a little brown stick. Instead, Barroid found Victor Conte, and the rest, as they say, is history.
So now I root for A-Rod. Griffey sits at 587, but I don’t see him pulling a Bonds and smacking 73 homeruns at age 38, so I think he’s going to fall shy. Alex, however, hit number 500 on the same day Bonds hit 755, leaving him 255 shy of Mr. Large Head (see kids, stay in school and you too can do simple arithmetic). At only 32 years of age, I think it’s a no-brainer to take the over on an A-Rod line of 255 more homeruns in his career. And I really hope it happens, so that all this talk of steroids and asterisks will be unnecessary.
Well, at least until Jose Canseco’s next book.
I never thought I’d actually get to the point in my life where I’d say this, but I’m rooting for Alex Rodriguez.
Hold on. Before you all chuck rotten vegetables at me, I did not say “New York Yankees.” I refuse to ever root for the bastards of baseball. A-Rod, however, has my full support.
Why?
Because he needs to pass Barry Bonds.
I wrote an article in October of 2005 for this very website that pleaded with Bonds, whom WFAN radio personality Steve Somers refers to simply as “Barroid,” to retire. He was currently at 708 homeruns, and I didn’t want to see him hit 709, much less 715 or 756. Unfortunately, he hit both of those marks, and implied recently that he’s even considering returning for another season after this one because he finds himself less than 100 hits shy of 3,000 for his career. According to Barry Balco, his godfather Willie Mays has always wanted to see Bonds get to that benchmark, even more so than Aaron’s record.
Wake me up when I should care.
Honestly, I’m sick of even talking about this person, but it’s the hot topic in sports, so for my return column, there wasn’t much of a better idea. Here’s the thing: Bonds is a liar. Bonds is a cheat. Bonds is an arrogant, obnoxious individual who cares about no one besides himself. For those reasons, even more than the steroids, I dislike him.
The problem I have is that Bonds was a Hall-of-Famer before he ever used performance enhancing drugs. Look at the numbers he’s amassed: career .298 average, 514 stolen bases, and a .444 OBP. Some of those are a bit inflated because of the ‘roids, but especially with regards to the SB numbers, most are pre-1998, i.e. pre-McGwire and Sosa. Bonds was widely regarded, along with Ken Griffey Jr., as the premier baseball player of his generation. In ’98, however, it was Sosa and McGwire who captivated audiences and garnered the national media attention with the great home run chase, and Bonds couldn’t handle it. Someone told him he could do what those two did, and Barry’s ego being what it is, he went after it.
Don’t get me wrong, there’s a lot of blame to go around with this. Bud Selig and MLB executives for turning a blind eye as the game tried to rebound from the strike, which was partly their fault anyway. The other half of the blame, at least with regards to the strike and disregard for drug testing, goes to Donald Fehr and the Players’ Association. Regardless of that, however, Bonds could still have been just like Cal Ripken Jr. or Tony Gwynn, who were both recently inducted into the Hall, or even like Griffey, who with all the injuries and lack of upper body growth clearly steered clear of the juice. Those guys simply kept their egos in check and relied on their God-given talent to hit a little white ball with a little brown stick. Instead, Barroid found Victor Conte, and the rest, as they say, is history.
So now I root for A-Rod. Griffey sits at 587, but I don’t see him pulling a Bonds and smacking 73 homeruns at age 38, so I think he’s going to fall shy. Alex, however, hit number 500 on the same day Bonds hit 755, leaving him 255 shy of Mr. Large Head (see kids, stay in school and you too can do simple arithmetic). At only 32 years of age, I think it’s a no-brainer to take the over on an A-Rod line of 255 more homeruns in his career. And I really hope it happens, so that all this talk of steroids and asterisks will be unnecessary.
Well, at least until Jose Canseco’s next book.
Monday, August 6, 2007
On the best 100 NBA players of the 2000s (NBA)
As promised, I am using my value rating system to determine the best players in the recent years of the NBA. Before I get into it, a couple of definitions.
First, recent. By recent I mean the 2000’s. For the ratings that follow, I am exclusively using the 1999-2000 through 2006-2007 seasons. So Michael Jordan, for the purposes of this list, played only two seasons, both for Washington. This is the cutoff point because so far, that is all I have calculated. I decided after the lockout season was a good cutoff point for now.
Second, best. Is it a measure of how dominant a player was in his prime? Of how long his prime lasted? Of how long he lasted?
Probably a combination. Borrowing heavily from Bill James’ system in the Historical Baseball Abstract, I have defined three measures, using my Value Score (VS) system.
(1) Total Value Score.
(2) Value Score per 82 games.
(3) Value Score of Best 3 Consecutive Seasons
The first two measures consider a player’s entire body of work over the time period. The overall total rewards durability and consistency, and also encourages conservative ratings for young players who may only have a few years. The per-82 rewards pure quality, ignoring injuries or youth. The top 3 seasons is in there to measure how good the player was at his best. By the way, if someone hasn’t played three seasons, their total is still divided by three. I don’t want to get too far ahead of myself on rating rookies and sophs.
I drew the line for consideration at any player who had reached a Value Score of 20 or greater in any of the eight seasons. 119 players fit this criterion. Once I had this pool of players, I normalized each of the three categories, to ensure the three dimensions were weighted equally. By adding up the z-scores by player, I determined my 100 Top Players of the 2000s.
One more thing. Value Scores are only for the regular season, but greatness is often defined in the playoffs. How does that factor in? I made adjustments for the postseason, both up and down. For example, in the 2006-2007 season, the Spurs were the highest adjusted team, credited with 11 extra wins for winning the NBA title. The Mavericks had the largest negative change, penalized 6 wins for their first-round loss to Golden State. Players on teams which missed the playoffs receive no adjustments. I didn’t decide on this method until after I coded the list, so it’s only up for the top 20. So just imagine somebody like Tony Parker is a few spots higher than he is.
Oh yeah, one absolute final last thing. There are a couple players who haven’t ever broken 20 VS, but whose consistency should put them in the top 100 anyway. Unfortunately, they got sorted out, and I don’t feel like looking back through to make sure I catch everybody, so for now I’ll just extend my apologies to Shane Battier, Mike Miller, and probably some others. If your favorite solid player didn’t make the list, that’s probably why.
Any more questions? OK then, here’s the chart, with some notes afterward (if the chart appears in an awkward format, sorry. I am working on it):
# Fname Lname
1 Kevin Garnett
2 Tim Duncan
3 Shaquille O'Neal
4 Jason Kidd
5 Dirk Nowitzki
6 LeBron James
7 Kobe Bryant
8 Steve Nash
9 Tracy McGrady
10 Ben Wallace
11 Shawn Marion
12 Gary Payton
13 Allen Iverson
14 Dwyane Wade
15 Chauncey Billups
16 Paul Pierce
17 Karl Malone
18 Stephon Marbury
19 Elton Brand
20 Chris Webber
21 Ray Allen
22 Vince Carter
23 John Stockton
24 Andre Miller
25 Steve Francis
26 Gilbert Arenas
27 Sam Cassell
28 Mike Bibby
29 Rasheed Wallace
30 Antoine Walker
31 Baron Davis
32 Lamar Odom
33 Pau Gasol
34 Jason Terry
35 Tony Parker
36 Andrei Kirilenko
37 Jermaine O'Neal
38 Marcus Camby
39 Michael Finley
40 Brad Miller
41 Dwight Howard
42 Yao Ming
43 Predrag Stojakovic
44 David Robinson
45 Jerry Stackhouse
46 Shareef Abdur-Rahim
47 Eddie Jones
48 Rashard Lewis
49 Anthony Mason
50 Chris Paul
51 Jamal Mashburn
52 Chris Bosh
53 Brent Barry
54 Richard Jefferson
55 Dikembe Motombo
56 Terrell Brandon
57 Darrell Armstrong
58 Manu Ginobili
59 Kirk Hinrich
60 Antwan Jamison
61 Latrell Sprewell
62 Reggie Miller
63 Jalen Rose
64 PJ Brown
65 Jason Williams
66 Amare Stoudamire
67 Damon Stoudamire
68 Nick Van Exel
69 Eric Snow
70 Doug Christie
71 Vlade Divac
72 Joe Johnson
73 Donyell Marshall
74 Carlos Boozer
75 Wally Szczerbiak
76 Michael Redd
77 Mehmet Okur
78 Tayshaun Prince
79 Andre Iguodala
80 Jason Richardson
81 Ron Artest
82 Scottie Pippen
83 Glenn Robinson
84 Antonio Davis
85 Allan Houston
86 Carmelo Anthony
87 Josh Howard
88 Derek Anderson
89 Mark Jackson
90 Luol Deng
91 Larry Hughes
92 Tyson Chandler
93 Rafer Alston
94 Alonzo Mourning
95 Drew Gooden
96 Grant Hill
97 Zach Randolph
98 Tim Hardaway
99 Brian Grant
100 Udonis Haslem
#1 All right. Garnett over Duncan? I can explain. There are five points I want to stress in regards to that decision.
1. It was very close.
2. The system rewards peak performance, and Garnett’s peak is the highest of the decade. KG used to win a lot of games with a minimal supporting cast. Consider that Minnesota won 58 games with Trenton Hassell, Fred Hoiberg and Mark Madsen in key roles. Or, better yet, they won 51 games the year before with Troy Hudson as the second best player on the team.
3. Durability played a role. Not that Duncan isn’t reliable, but Garnett averaged more than 80 games a season over the eight years, including six straight of 81 or more.
4. Over the course of their careers overall, Duncan would/will probably be ahead of Garnett. Remember, the Spurs won the title the year before the study began, and Duncan is slightly better than Garnett right now.
5. Don’t forget, it was very close.
I do not think there is much of an argument they should not be the top two.
#3 Shaq outdoes everyone outside those two, despite his recent injuries and the fact that a substantial portion of his prime came in the previous decade. Considering what a force of nature he was at his best, I think this is reasonable.
#7 That ranking also makes this one reasonable. There should be little doubt, really, that Kobe Bryant was the sidekick on the Lakers’ championship teams. Look at how far Shaq helped carry the Florida teams both before and since. After Shaq, Kobe has really performed as just another gunner, not good enough to carry a weak supporting cast much over .500. As far as the regular season is concerned, there isn't much evidence to put him ahead of Tracy McGrady, and even Kobe’s playoff success is tempered by the fact that during those runs, the best player on his team was somebody else. In contrast, there has rarely been a question of the best player on Kidd and Nowitzki’s teams, and there has been absolutely no question on LeBron’s. All of these teams have won a bunch of games and made a Finals appearance, which is far more than the post-Shaq Lakers can say. Also, while he is undoubtedly not as big a factor as Kobe, Lamar Odom’s contributions to the current Lakers are underestimated. The rumored Jermaine O’Neal trade, giving up Odom and Bynum, would not have been wise.
#11 I think it is worth noting that Shawn Marion was an established star even in the B.N. era. Nash is a great player, and fun to watch, but Marion has been almost as indispensable to these Suns. It would have been interesting to see what would have happened had he gone elsewhere.
#13 Iverson would have cracked the top ten if he could stay healthy a little better.
#17, #23 The fact that both of these Utah guys made the Top 25, in just five and four seasons at the end of their careers, shows how amazing they were.
#36 Kirilenko will be an interesting one to follow. His 03-04 through 05-06 seasons were worthy of a rising superstar, but last year was a major hiccup. If he finds his form, the Jazz will be extremely good for the foreseeable future.
#41 Not quite the trajectory of LeBron and Wade, but Howard will push the edges of the top 25 with another season like last year in 2007-08.
#50 Speaking of trajectory…let me tell you how good Chris Paul’s rookie year was. Not better than LeBron’s, Carmelo’s, or Wade’s. Not better than Howard’s, or Okafor’s, or Deron Williams’, or anybody’s. Not better; better. A LOT better. If not for injury, he would have had the best first two years of anyone in the sample; as it is he trails only King James. In short, this guy should never have fallen to fourth.
#66, #81 In fairness to Mr. Stoudamire, I should probably have counted 04-05 and 06-07 as consecutive seasons, considering he only played two games in between due to the knee injury. This would raise him about ten spots on the list. If I skipped over the Artest suspended season, it would have a smaller but similar effect. But since he decided to do that right as he and the Pacers were on their way up, that whole idea is a lot more speculative.
#72, #76, #83, #85, #86, #91 Proof that the system expects some quality supporting numbers to go with the points.
#92 Proof that the system does appreciate the numbers other than the points.
#105 Not listed, but this is the position MJ earned for his two Wizards’ seasons.
In the future, I hope to expand these ratings back into the 1990’s, and beyond.
On the Statistical Rating of Basketball Players (NBA)
As some of you may remember, I once posted on my old site a rating of the greatest baseball players of all time, by position. As some fewer of you, such as my grandfather, may remember, I never finished posting it. This is because I got bored, because was basically just updating the results from my Bill James book to account for people like Albert Pujols, who were not yet established when that book came out.
Well, this is something new. In a lifetime of trying to make up statistical ratings for baseball and then basketball players, I think this one represents a major breakthrough. The inspiration for these ratings came from a study I did on assists, and from some ideas in baseball player evaluation.
Baseball has a statistic called VORP. This stands for Value Over Replacement Player, which is pretty self-explanatory. The idea is that a player’s value isn’t measured from zero or from average, but from the edge of the major leagues. Basically, how much better is a guy than the next guy the team could bring up (practically) for free from Triple-A? For the categories I am discussing, I have estimated the replacement level empirically from the statistics of end-of-the-bench NBA players.
Anyway, basketball statistics can be measured in this fashion. I considered the standard statistics: points, rebounds, assists, blocks, steals, turnovers, fouls, and shooting efficiency, and then I jumped through a few hoops to determine the proper weights for the relationship between them. Most of it is pretty straightforward, but here are two things that I have handled differently than is usually seen:
First, scoring and assists. Using assists and shooting percentages, I mathematically estimated the effect of a Good Pass on shooting efficiency. A Good Pass is defined to be a pass that will be credited as an assist if the ensuing shot is made. I also estimated the number of Good Passes made and received by each player.
This has two benefits. First, by determining the effect on points per shot, we can calculate exactly how valuable a Good Pass is. Secondly, by determining the number of Good Passes received, we can set a different boundary for replacement scoring efficiency for every individual player. For example, not only can we credit Steve Nash for creating easy shots for his teammates, but we can also credit him for not having the ability to receive passes from himself. In general, this compensates guards for creating their own shots, something many statistical measurements do not.
Second, turnovers. Many statistical systems subtract absolute turnovers, which is also biased against guards. Given the amount of time he spends with the ball in his hands, a point guard with three turnovers in a game has almost certainly protected the ball better than a center with two. My solution is to consider turnovers as a percentage of possessions. Since the vast majority of possessions end in a shot or a turnover, this is easy to calculate. However, the point is to recognize those who handle the ball, not those who take a lot of shots. If a guard drives and kicks the ball to an open shooter, it is really the passer, not the shooter, who avoided a turnover on the play. So the number of player possessions, for these purposes, is: Turnovers + Shots + Good Passes Made – Good Passes Received.
Now, after combining each player’s contributions in all areas, I had a choice to determine what to do with the ensuing raw scores. One method is to normalize for pace, and then rate players on some sort of per-minute basis directly from that point. This is a perfectly good way to go about things.
However, I chose to borrow another baseball idea. Bill James introduced the concept of Win Shares, which directly relate player success to team wins. If the New York Yankees win 90 games, their players are credited with exactly 270 Win Shares. I think the explicit correlation of team success to player value is a good method.
However, my number—which I’m for the moment calling a Value Score (VS), although I am declaring open season for a catchier name—is not directly analogous to a Win Share. James goes through a lot of trouble to show that Win Shares are not biased toward players on good or bad teams; if a player gets traded from the Red Sox to the Royals or vice versa, his Win Shares won’t be biased. In basketball, where there is much more interaction between players, I did not find that to be true. So in my system, a 60 win team will have a higher total Value Score than a 30 win team, but it will not be not twice as large. It will be closer to one and a half.
I did keep the numbers in the general ballpark of Win Shares, so the following intuition that baseball stat geeks may already know will still hold. A 10 VS season indicates a player is a solid starter, a 20 VS season denotes a minor star, a 30 VS player will be an All-Star and tends to be in the MVP discussion, and a 40 VS player is probably the best player in the league.
This system passes three important tests. First, as mentioned above, a player’s rating does not change excessively when he moves to a team of greater or lesser quality. This is consistent with the idea that the number captures a player’s inherent value. Second, the system is fair to players at all positions. Because of the ambiguity that comes from the majority of players who play multiple spots, I like to divide players into four classifications: guard (PG/SG), swingman (SG/SF), forward (SF/PF), and post (PF/C). (Note: The assigned position has no effect on ranking players, but only for my own organizational purposes. You could use whatever designation you like without changing the numbers). In the eight seasons for which I have ratings, 117 players have had at least one season of a 20 or higher VS. Of these, 32 were guards, 31 swingmen, 29 forwards and 25 posts. Third, the system provides results that are generally consistent with observed excellence.
I would also like to contrast this method of player evaluation with two notable statistical measures: John Hollinger’s Player Efficiency Rating, and Wins Produced, created by the authors of the sports economics book The Wages of Wins.
The Wages of Wins’ method is based on regression analysis, and the statistics are weighted to maximize the relationship of the statistics to team wins. This is perfect in baseball offense, wherein players each bat with the intent of maximizing production and minimizing outs, and—this is important—take turns hitting. But in basketball, in which anyone can take any shot, the application of team logic to player logic is not quite as effective. Yes, the team wants to maximize its shooting percentage, but the team doesn’t maximize its shooting percentage by maximizing every player’s shooting percentage. Rather, it accomplishes this by taking its best option each possession. On a possession when the team cannot get an easy shot at all, the best scorers on the team will be disproportionately likely to take that difficult shot.
Consider this analogy. Suppose, in baseball, a team could reset its lineup before the ninth inning of a close game. A team would obviously choose to bat its best hitters against the opposing closer (ace reliever), which would then lower their batting averages. So the team batting average would be maximized, but the best hitters’ individual averages would not be maximized. We might still want to measure the best hitters by batting average, but since there is self-selection, we would also have to adjust for total at-bats.
The Wages of Wins does not make this adjustment. Therefore, while I agree with the authors’ conclusions in general, which is that players who score a lot tend to be overrated, I think their system overcompensates away from scorers. In short, I agree that Allen Iverson was not really the best player in the league in his MVP season, but I do not believe there were 90 better players in the NBA that year.
My differences with John Hollinger’s PER system are more philosophical than technical. His is a per-minute system, thus measuring efficiency. My system examines aggregates. If two players of apparently similar effectiveness receive significant differences in playing time, PER is the way to see their production matches. My system rewards the greater number of minutes, which limits its versatility but does allow it to credit players who play more minutes than their stats would seem to justify, such as defensive stoppers. With PER, you just have to know.
Also, both systems I have mentioned examine absolute turnovers as discussed above, rather than crediting players who always have the ball in their hands.
In my next post, I am going to look at the NBA’s best recent players, according to the VS system.
Well, this is something new. In a lifetime of trying to make up statistical ratings for baseball and then basketball players, I think this one represents a major breakthrough. The inspiration for these ratings came from a study I did on assists, and from some ideas in baseball player evaluation.
Baseball has a statistic called VORP. This stands for Value Over Replacement Player, which is pretty self-explanatory. The idea is that a player’s value isn’t measured from zero or from average, but from the edge of the major leagues. Basically, how much better is a guy than the next guy the team could bring up (practically) for free from Triple-A? For the categories I am discussing, I have estimated the replacement level empirically from the statistics of end-of-the-bench NBA players.
Anyway, basketball statistics can be measured in this fashion. I considered the standard statistics: points, rebounds, assists, blocks, steals, turnovers, fouls, and shooting efficiency, and then I jumped through a few hoops to determine the proper weights for the relationship between them. Most of it is pretty straightforward, but here are two things that I have handled differently than is usually seen:
First, scoring and assists. Using assists and shooting percentages, I mathematically estimated the effect of a Good Pass on shooting efficiency. A Good Pass is defined to be a pass that will be credited as an assist if the ensuing shot is made. I also estimated the number of Good Passes made and received by each player.
This has two benefits. First, by determining the effect on points per shot, we can calculate exactly how valuable a Good Pass is. Secondly, by determining the number of Good Passes received, we can set a different boundary for replacement scoring efficiency for every individual player. For example, not only can we credit Steve Nash for creating easy shots for his teammates, but we can also credit him for not having the ability to receive passes from himself. In general, this compensates guards for creating their own shots, something many statistical measurements do not.
Second, turnovers. Many statistical systems subtract absolute turnovers, which is also biased against guards. Given the amount of time he spends with the ball in his hands, a point guard with three turnovers in a game has almost certainly protected the ball better than a center with two. My solution is to consider turnovers as a percentage of possessions. Since the vast majority of possessions end in a shot or a turnover, this is easy to calculate. However, the point is to recognize those who handle the ball, not those who take a lot of shots. If a guard drives and kicks the ball to an open shooter, it is really the passer, not the shooter, who avoided a turnover on the play. So the number of player possessions, for these purposes, is: Turnovers + Shots + Good Passes Made – Good Passes Received.
Now, after combining each player’s contributions in all areas, I had a choice to determine what to do with the ensuing raw scores. One method is to normalize for pace, and then rate players on some sort of per-minute basis directly from that point. This is a perfectly good way to go about things.
However, I chose to borrow another baseball idea. Bill James introduced the concept of Win Shares, which directly relate player success to team wins. If the New York Yankees win 90 games, their players are credited with exactly 270 Win Shares. I think the explicit correlation of team success to player value is a good method.
However, my number—which I’m for the moment calling a Value Score (VS), although I am declaring open season for a catchier name—is not directly analogous to a Win Share. James goes through a lot of trouble to show that Win Shares are not biased toward players on good or bad teams; if a player gets traded from the Red Sox to the Royals or vice versa, his Win Shares won’t be biased. In basketball, where there is much more interaction between players, I did not find that to be true. So in my system, a 60 win team will have a higher total Value Score than a 30 win team, but it will not be not twice as large. It will be closer to one and a half.
I did keep the numbers in the general ballpark of Win Shares, so the following intuition that baseball stat geeks may already know will still hold. A 10 VS season indicates a player is a solid starter, a 20 VS season denotes a minor star, a 30 VS player will be an All-Star and tends to be in the MVP discussion, and a 40 VS player is probably the best player in the league.
This system passes three important tests. First, as mentioned above, a player’s rating does not change excessively when he moves to a team of greater or lesser quality. This is consistent with the idea that the number captures a player’s inherent value. Second, the system is fair to players at all positions. Because of the ambiguity that comes from the majority of players who play multiple spots, I like to divide players into four classifications: guard (PG/SG), swingman (SG/SF), forward (SF/PF), and post (PF/C). (Note: The assigned position has no effect on ranking players, but only for my own organizational purposes. You could use whatever designation you like without changing the numbers). In the eight seasons for which I have ratings, 117 players have had at least one season of a 20 or higher VS. Of these, 32 were guards, 31 swingmen, 29 forwards and 25 posts. Third, the system provides results that are generally consistent with observed excellence.
I would also like to contrast this method of player evaluation with two notable statistical measures: John Hollinger’s Player Efficiency Rating, and Wins Produced, created by the authors of the sports economics book The Wages of Wins.
The Wages of Wins’ method is based on regression analysis, and the statistics are weighted to maximize the relationship of the statistics to team wins. This is perfect in baseball offense, wherein players each bat with the intent of maximizing production and minimizing outs, and—this is important—take turns hitting. But in basketball, in which anyone can take any shot, the application of team logic to player logic is not quite as effective. Yes, the team wants to maximize its shooting percentage, but the team doesn’t maximize its shooting percentage by maximizing every player’s shooting percentage. Rather, it accomplishes this by taking its best option each possession. On a possession when the team cannot get an easy shot at all, the best scorers on the team will be disproportionately likely to take that difficult shot.
Consider this analogy. Suppose, in baseball, a team could reset its lineup before the ninth inning of a close game. A team would obviously choose to bat its best hitters against the opposing closer (ace reliever), which would then lower their batting averages. So the team batting average would be maximized, but the best hitters’ individual averages would not be maximized. We might still want to measure the best hitters by batting average, but since there is self-selection, we would also have to adjust for total at-bats.
The Wages of Wins does not make this adjustment. Therefore, while I agree with the authors’ conclusions in general, which is that players who score a lot tend to be overrated, I think their system overcompensates away from scorers. In short, I agree that Allen Iverson was not really the best player in the league in his MVP season, but I do not believe there were 90 better players in the NBA that year.
My differences with John Hollinger’s PER system are more philosophical than technical. His is a per-minute system, thus measuring efficiency. My system examines aggregates. If two players of apparently similar effectiveness receive significant differences in playing time, PER is the way to see their production matches. My system rewards the greater number of minutes, which limits its versatility but does allow it to credit players who play more minutes than their stats would seem to justify, such as defensive stoppers. With PER, you just have to know.
Also, both systems I have mentioned examine absolute turnovers as discussed above, rather than crediting players who always have the ball in their hands.
In my next post, I am going to look at the NBA’s best recent players, according to the VS system.
Sunday, July 29, 2007
On National Champions (NCAAF)
If you are a college football fan, and you want to know if your team has a chance at the national title, there are only two things you need to look for. First, you need a veteran, talented defense. Second, you need a returning quarterback to lead your offense. If a running back is hands-down the most important offensive player, that is not a good sign. First, let’s look at how the last six champions fit the profile.
2006 Florida returned six defensive starters off a team that allowed 18.8 points per game, and Chris Leak, who had been starting since his freshman season.
2005 Texas was a perfect fit. They had nine starters returning on a defense that had allowed 17.9 points per game, and they also had Vince Young. They squeezed past Ohio State in the Horseshoe, USC in the Rose Bowl, and crushed everybody in between.
2004 USC returned six starters from a defense that had allowed 18.4 points per game, and Matt Leinart.
2003 LSU returned six defensive starters and Matt Mauck. They navigated the always-brutal SEC with a single loss, and pulled out three close games against Top 15 teams.
2002 Ohio State returned seven defensive starters, who were great, but Clarett was definitely their offensive star. They are a little bit of an exception. However, it is worth pointing out that it was Krenzel who stepped up and saved several late-season games that needed saving.
2001 Miami, led by Ken Dorsey and eight returning defensive starters, pretty much crushed everything in their path. They scored 43 points a game and allowed just ten. Also, if you don’t buy the interference call the next year, they fit again and perfect the system.
The list keeps going with Oklahoma and Huepel, FSU and Weinke, but I think we’re far enough. The theory is pretty sound. Winning the national championship, in football, is about winning the three or four games against teams almost as good as you are. Running teams tend to push around weak teams, and don’t always have a good Plan B when they come across a bigger, faster defensive front that can stack against the run and make them pass. On the other side of the ball, veteran defenses are less likely to fold when the talent and coaching level they play against jumps.
I think a good rule of thumb is that for a qualifying defense, a team must have at least six of eleven starters returning, and have given up less than 20 points per game. The “star quarterback” is a little more subjective. I also expect a team’s talent to have shown in the previous season: I have defined this broadly to mean they were ranked at any point. Now, who fits?
The SEC is lacking a good candidate. LSU and Arkansas have the defenses, but not the QBs, and Tennessee has a quarterback but lost over half the D. Florida lost both—although with just three defensive senior starters and a learning year for Tebow, they’ll be geared back up for 2008. With a blue chip true sophomore quarterback and a young defense, Georgia looks likewise a year away. Auburn almost fits, but Brandon Cox doesn’t really count as a star QB. Also, cruelly, the Tigers have all four of their toughest conference opponents (Florida, Arkansas, LSU, Georgia) on the road. The best fit may actually be South Carolina, with Blake Mitchell and ten defensive starters returning from an outfit that allowed just 18.7 points per game. But since they spent all of last season unranked, I can’t see they have the talent level to emerge. Basically, the SEC goes eight deep without much real separation.
The Big Ten is also short on good fits. Ohio State loses Smith, and Michigan loses the defense. Wisconsin is more tied to RB PJ Hill than ever, since QB Stocco graduated. The Badgers are a perfect example of where running back teams can struggle. Their rush yards during a six-game stretch last season went 287, 12, 209, 307, 208, 241. Which of these games is not like the others? The Michigan game, of course, which ended up being the only one in between Wisconsin and a perfect season. But once the Wolverines had clamped down on the run, Wisconsin didn’t have any answers.
The one Big Ten team who does fit the profile is Penn State. There are signs that Anthony Morelli is going to live up to his considerable potential, and the defense should be very strong for the fourth straight year. With Notre Dame and Michigan in September, we will at least find out quickly.
The Big 12 also has a lone star team. Oklahoma doesn’t have an established quarterback, A&M is intriguing but doesn’t quite fit, and of course the entire North division is a mess, just as it has always been since the decline and fall of the Nebraskan Empire. All of which leaves us with Colt McCoy and the Texas Longhorns. While Colt is healthy, they are exceedingly dangerous, and while their biggest weakness is the secondary, both Oklahoma and Texas A&M are running teams. Barring a sophomore slump for McCoy, Texas has a great shot at running the Big 12.
The ACC has some potential. Miami, Florida State, and Boston College fit the ideal. Kyle Wright and Miami have been huge disappointments for a couple years running now, but this year’s team is reminiscent of Carson Palmer’s 2002 USC Trojans that turned that program back around. FSU is in a similar situation, with Drew Weatherford and Co needing to put together a solid, consistent season. Both squads need to do better with turnovers and close games, and both should. Boston College is the most often overlooked. They have put together three straight three-loss seasons, and this year they bring back all but two starters off a defense that held opponents to under 16 ppg last year. Add in seven offensive starters, including the leading passer, rusher and receiver as well as three senior linemen, BC should do very well. But then, why did Tom O’Brien leave?
Also, Virginia Tech is probably the best team in the conference; they return eight starters on each side of the ball, and their defense will be terrifying. However, with Branden Ore leading the offense from RB, and with iffy Sean Glennon behind center, I don’t think they are a national title contender. Add in solid squads like Clemson, Maryland and Georgia Tech, and the ACC will, like the SEC be a deep, entertaining conference this season.
The Pac-10 basically comes down to USC and that’s it. Shocking. With John David Booty and ten defensive starters, they have to be the national favorite. As a side note, Oregon is close to the ideal, except RB Jonathan Stewart is their star. Either way, with USC around, they’re only a side note.
The Big East is poised to follow up its strong run of last season. Brian Brohm and Louisville are the worthiest contender; West Virginia and Rutgers are all about running. It is very possible, since WVU gets Louisville at home, that the Mountaineers could run the regular season. However, I think they would be in a lot of trouble against their BCS title game opponent.
Outside the BCS, there are as usual no real title candidates.
In rough order, I would put the chances of the teams like this:
Favorite: USC
Contender: Texas
Louisville
Dark Horse: Miami, FL
Boston College
Penn State
Florida State
And, just for fun, I’ll throw in some conference predictions:
SEC: Florida over LSU
Big Ten: Michigan
Big 12: Texas over Nebraska
ACC: VT over BC
P10: USC
Big East: WV
BCS games:
Title: USC over WV
Rose: Michigan over LSU
Orange: Louisville over VT
Fiesta: Texas over Hawaii
Sugar: Florida over Penn St.
2006 Florida returned six defensive starters off a team that allowed 18.8 points per game, and Chris Leak, who had been starting since his freshman season.
2005 Texas was a perfect fit. They had nine starters returning on a defense that had allowed 17.9 points per game, and they also had Vince Young. They squeezed past Ohio State in the Horseshoe, USC in the Rose Bowl, and crushed everybody in between.
2004 USC returned six starters from a defense that had allowed 18.4 points per game, and Matt Leinart.
2003 LSU returned six defensive starters and Matt Mauck. They navigated the always-brutal SEC with a single loss, and pulled out three close games against Top 15 teams.
2002 Ohio State returned seven defensive starters, who were great, but Clarett was definitely their offensive star. They are a little bit of an exception. However, it is worth pointing out that it was Krenzel who stepped up and saved several late-season games that needed saving.
2001 Miami, led by Ken Dorsey and eight returning defensive starters, pretty much crushed everything in their path. They scored 43 points a game and allowed just ten. Also, if you don’t buy the interference call the next year, they fit again and perfect the system.
The list keeps going with Oklahoma and Huepel, FSU and Weinke, but I think we’re far enough. The theory is pretty sound. Winning the national championship, in football, is about winning the three or four games against teams almost as good as you are. Running teams tend to push around weak teams, and don’t always have a good Plan B when they come across a bigger, faster defensive front that can stack against the run and make them pass. On the other side of the ball, veteran defenses are less likely to fold when the talent and coaching level they play against jumps.
I think a good rule of thumb is that for a qualifying defense, a team must have at least six of eleven starters returning, and have given up less than 20 points per game. The “star quarterback” is a little more subjective. I also expect a team’s talent to have shown in the previous season: I have defined this broadly to mean they were ranked at any point. Now, who fits?
The SEC is lacking a good candidate. LSU and Arkansas have the defenses, but not the QBs, and Tennessee has a quarterback but lost over half the D. Florida lost both—although with just three defensive senior starters and a learning year for Tebow, they’ll be geared back up for 2008. With a blue chip true sophomore quarterback and a young defense, Georgia looks likewise a year away. Auburn almost fits, but Brandon Cox doesn’t really count as a star QB. Also, cruelly, the Tigers have all four of their toughest conference opponents (Florida, Arkansas, LSU, Georgia) on the road. The best fit may actually be South Carolina, with Blake Mitchell and ten defensive starters returning from an outfit that allowed just 18.7 points per game. But since they spent all of last season unranked, I can’t see they have the talent level to emerge. Basically, the SEC goes eight deep without much real separation.
The Big Ten is also short on good fits. Ohio State loses Smith, and Michigan loses the defense. Wisconsin is more tied to RB PJ Hill than ever, since QB Stocco graduated. The Badgers are a perfect example of where running back teams can struggle. Their rush yards during a six-game stretch last season went 287, 12, 209, 307, 208, 241. Which of these games is not like the others? The Michigan game, of course, which ended up being the only one in between Wisconsin and a perfect season. But once the Wolverines had clamped down on the run, Wisconsin didn’t have any answers.
The one Big Ten team who does fit the profile is Penn State. There are signs that Anthony Morelli is going to live up to his considerable potential, and the defense should be very strong for the fourth straight year. With Notre Dame and Michigan in September, we will at least find out quickly.
The Big 12 also has a lone star team. Oklahoma doesn’t have an established quarterback, A&M is intriguing but doesn’t quite fit, and of course the entire North division is a mess, just as it has always been since the decline and fall of the Nebraskan Empire. All of which leaves us with Colt McCoy and the Texas Longhorns. While Colt is healthy, they are exceedingly dangerous, and while their biggest weakness is the secondary, both Oklahoma and Texas A&M are running teams. Barring a sophomore slump for McCoy, Texas has a great shot at running the Big 12.
The ACC has some potential. Miami, Florida State, and Boston College fit the ideal. Kyle Wright and Miami have been huge disappointments for a couple years running now, but this year’s team is reminiscent of Carson Palmer’s 2002 USC Trojans that turned that program back around. FSU is in a similar situation, with Drew Weatherford and Co needing to put together a solid, consistent season. Both squads need to do better with turnovers and close games, and both should. Boston College is the most often overlooked. They have put together three straight three-loss seasons, and this year they bring back all but two starters off a defense that held opponents to under 16 ppg last year. Add in seven offensive starters, including the leading passer, rusher and receiver as well as three senior linemen, BC should do very well. But then, why did Tom O’Brien leave?
Also, Virginia Tech is probably the best team in the conference; they return eight starters on each side of the ball, and their defense will be terrifying. However, with Branden Ore leading the offense from RB, and with iffy Sean Glennon behind center, I don’t think they are a national title contender. Add in solid squads like Clemson, Maryland and Georgia Tech, and the ACC will, like the SEC be a deep, entertaining conference this season.
The Pac-10 basically comes down to USC and that’s it. Shocking. With John David Booty and ten defensive starters, they have to be the national favorite. As a side note, Oregon is close to the ideal, except RB Jonathan Stewart is their star. Either way, with USC around, they’re only a side note.
The Big East is poised to follow up its strong run of last season. Brian Brohm and Louisville are the worthiest contender; West Virginia and Rutgers are all about running. It is very possible, since WVU gets Louisville at home, that the Mountaineers could run the regular season. However, I think they would be in a lot of trouble against their BCS title game opponent.
Outside the BCS, there are as usual no real title candidates.
In rough order, I would put the chances of the teams like this:
Favorite: USC
Contender: Texas
Louisville
Dark Horse: Miami, FL
Boston College
Penn State
Florida State
And, just for fun, I’ll throw in some conference predictions:
SEC: Florida over LSU
Big Ten: Michigan
Big 12: Texas over Nebraska
ACC: VT over BC
P10: USC
Big East: WV
BCS games:
Title: USC over WV
Rose: Michigan over LSU
Orange: Louisville over VT
Fiesta: Texas over Hawaii
Sugar: Florida over Penn St.
Monday, July 9, 2007
On Future Topics
I am going to be away from internet connectivity for a while, but look for new features on or after July 21 on the subjects of: statistically rating NBA players, NBA free agency, major league ballparks, possibly more hockey depending on how much attention I decide the Sabres merit, and also one or two posts beyond the admittedly wide world of sports.
Thursday, July 5, 2007
On the Ticking Time Bomb Nature of Liking Buffalo Sports Teams (General)
Through rookie pay scales, arbitration, and restricted free agency, sports leagues tend to restrict salaries for incoming players. This is because the collective bargaining agreements, which allow for the regulation of this sort of thing, naturally act in the interest of players who are already in the league. As a result, the available supply of talented players is pushed down. Players generally are near, at, or just beyond their peak years when they are finally eligible to become unrestricted free agents, and can thus begin to demand long contracts with high salaries. Therefore, it is usually not optimal strategy for teams, especially small-market teams, to sign such players.
That said, this is terrible. Drury and Briere, in one day? To East teams? Then Zubrus? Who rubbed salt in the wound by saying it was a hockey decision and he only wanted to win?
My friend JP put it best: only in Buffalo could a team lose two captains in one day. To no other city could that ever, ever happen. Ever.
I still believe the Sabres will be able to lock in Vanek and Roy, that Connolly will be healthy and effective, that Miller will help them win games they shouldn’t, but still, this is just awful. And may God help us if we face Drury and the Rangers in the playoffs.
At least the Bills re-signed their All-Pro. Punter.
That said, this is terrible. Drury and Briere, in one day? To East teams? Then Zubrus? Who rubbed salt in the wound by saying it was a hockey decision and he only wanted to win?
My friend JP put it best: only in Buffalo could a team lose two captains in one day. To no other city could that ever, ever happen. Ever.
I still believe the Sabres will be able to lock in Vanek and Roy, that Connolly will be healthy and effective, that Miller will help them win games they shouldn’t, but still, this is just awful. And may God help us if we face Drury and the Rangers in the playoffs.
At least the Bills re-signed their All-Pro. Punter.
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