Obviously, the closer in time two teams are, the easier the simulation. But you still want to check those simulations. Can anyone simulate the strength ofMessage 1 of 53 , Dec 13 11:56 AMView SourceObviously, the closer in time two teams are, the easier the
simulation. But you still want to check those simulations. Can
anyone simulate the strength of the 1995 Rockets? Most simulators
wouldn't have had them winning the title. So how do you even compare
them with teams in the same year.
not quite sure how to interpret this statement - would you "expect" a simulator to have the rockets win the title more often that season than, say, any other team, simply because they indeed did win the title that year?....
in the 1994-95 regular season the eventual champion rockets outscored their opponents by only 2.1 pts/g, and their record was just 47-35. nine teams had better records, and ten teams outscored their opponents by more points per game, and this is with olajuwon playing most of the season (72 games, 2853 min). if any simulator had the rockets winning the championship more often than those teams with better records and that outscored their opponents by more per game in its simulations, i certainly wouldn't trust that simulator for any kind of statistical accuracy...
heck the bulls that year were also 47-35 but outscored their opponents by 4.8 pts/g - i'd expect a simulator to have them win the title more often the rockets for that season....
every year the nba draft is held with a lottery system. however the team with the most chances for the first pick often does not get the 1st pick, sometimes a team with very little chance gets the 1st pick. does anybody think the system of choosing ballots out of a hat for draft position as flawed? i doubt it. same with winning a title in the playoffs - alot of it is luck. the rockets won the title in 94-95 by outscoring their opponents by just 2.8 pts/g in the playoffs, the 2nd lowest pts/g difference by a championship team since the 1989-90 season (only the 19999-2000 lakers were worse at 2.3 pts/g)....
and if you look at olajuwon's stats for the regular season and the playoffs for actually both the 93-94 and 94-95 seasons, you'll see little difference (i.e. they didn't win the titles both years because olajuwon, their best player, played way over his head in the playoffs versus the reg seas - he was great, yes, but essentially the same player as in the reg seas). the bottom line is they won the close games both years in the playoffs, they were "luckier" than the other teams. this does not mean they weren't a "strong" team. i would certainly consider any team that is capable of winning 50+ games in a season a strong team (and thus a threat to win it all) in the playoffs, especially if everyone is healthy, and in 93-94 nine teams (other than hou) won 50+ games and in 94-95 eight teams did, yet they did not win the title. the bulls won 6 titles in the past decade, and each time they outscored their opponents in the playoffs by over 5 pts/g, twice by over 10 pts/g. i would expect a simulator to have them win the title in those seasons the majority of the time versus any other team...
so i'm not sure what kind of "strength" you would expect a simulator to show for the 94-95 rockets. the bottom line is that they had the 2nd best overall league record in 93-94 and won the title, but had only the league's 10th best reg seas record in 94-95 but still managed to win the title....
... League ... it ... debate... They absolutely are not equal. The talent level of the National League in 1966 was FAR higher than the level of the AA in 1890.Message 53 of 53 , Dec 23 11:10 PMView Source> Is a player who hit .280 in the 1890 American Association (league average:
> .253) really just as good as someone who hit .280 in the 1966 National LeagueThey absolutely are not equal. The talent level of the National League in 1966 was FAR higher than the level of the AA in 1890. The available statistics (most notably the Stephen Jay Gould study, but also the recent Bill James study that he did for the Historical Baseball Abstract) support this. The fact that both leagues happened to hit in the mid-.250s does not change this fact.
> (league average: .256)? That's a ludicrous assertion on the face, and yet it
> seems to be the one you're arguing.
> this has been typical of your responses - you bait for a reply without
> defining your position. you call this "ludicrous" but you do not in any way
> state your side of this. so tell me - if that player is not as good, which
> player is better and what is your reasoning?..
> you are saying they are NOT equal, but totally avoiding the actual debate...
i've read james' first historical abtract (1985,1988) numerous times - its a great read. i've also read all of his single season abtracts prior to 1988 - they too were great reads. but while being a sabermetrician, he is not a statistician. i got this off a baseball stats analysts website (these are not my words) about his recent historical abstract:
"....Is it arrogance that leads James to feel as though he doesn't need to support his opinions? I have no idea, although I think that there's plenty of evidence in the new edition to indicate that the answer to that question is "yes." On the other hand, perhaps there's a more innocent explanation, like James' publisher demanding cuts of some of his analysis in order to make the work more accessible to the average, non-stathead fan. Whatever the reason, this problem makes the playing ratings portion of the new edition pretty much worthless, and puts a dent (maybe even a serious one) in James' reputation as an analyst.
and i found similar "opinions" about james elsewhere....
so having said that, and also having not read james' most recent diatribe about how players are better today than yesterday, are you going to summarize what he said for i and others here to read to support your position, or are you simply going to quote him as someone who supports your views without stating what he said?...
second, i haven't read gould's book but found numerous reviews of the book written on the internet. as far as i can tell from these reviews and written interviews of gould on the internet his basic premise about batting average is that (these are gould's words):
"...When you do that, you realize the following: The average batting average has never changed. It's always been around 260. It fluctuates back and forth, but it stays around 260. And that's not an absolute measure like running a mile or throwing a javelin; 260 is a balance between hitting and pitching. The fact that it's stayed 260 only shows that the balance has been maintained. I say it's been maintained as everyone has gotten better. Hitting's gotten better. Pitching's gotten better. Everything's gotten better. The balance remains the same. Now as everything gets better, the variation shrinks. That's all that happens...."
his contention is that the standard deviation shrinking with time is an indication of an overall increase in talent - for batting average. i read several interviews with him on the internet, and they were all done the year of the book or the year after (1996/1997 - the book being "life's grandeur"), in which he was asked about other baseball records and their possibility of being broken, and he was also quoted as saying the season home run record wouldn't be broken. well we've seen it broken 6 times in the past 5 years, by 3 different people...
we "baseball experts" all know how worthless batting average is as an indication of a baseball players true "worth". so tell me - what did gould say about slugging percentage? bonds just broke ruth's single season record held since the 1920s. is this an indication then that players were better in between when these marks were set? because no one got close to them and thus the standard deviation for that stats for the league was less variable and thus by gould's definition the league was better?...
tell me - did gould do a study of numerous aspects of baseball, and compare standard deviations thru time - or just batting average? everything i can see from reading reviews of his book was he only looked at batting average - is this true? if i'm wrong and he did, please inform me. but if he did just one, batting average, how do we know he he didn't use it as an example simply because it backed up his theory?...
> if you are asserting that the 1966 NL player is better, you are totallySo what you're saying is that there is no way to compare, then? Thanks for agreeing with me.
> forgetting to consider the logic of not just what would the 1890 hitter do in
> 1966, but what the 1966 hitter would do back in 1890 - under the conditions
> of the game as it was played in 1890. did they even use mits back then (if
> they did they were certainly of worse quality than the mits of 1966)? could
> the 1966 player even field with the type of mits they used back then? back in
> 1890 very few new balls were used in a single game, in 1966 after any ball
> went into the stands a new ball was put into play. based on that alone one
> could easily say that the 1966 .280 hitter would have a tougher time hitting
> under the conditions in 1890....
sure there is - the league batting avg was the same and the players hit the same - you know what i am going to say...they are the same (not knowing their OB%s and SLG%s, of course)...
was, quote "....the standard deviation has decreased and thus the variabilyty decreasing is indicative of overlal better play..." your only reason for saying the 1966 hitter was better than the 1890, or do you have other "evidence"...
fyi - as one who is a geologist that has the utmost respect for gould and his punctuated equilibria theories, he could stand a good lesson in sports. i notice he hasn't (and i guess won't at this point) done any similar analysis forhockey, basketball, or football...
back to basketball -
you can do all the standard deviations for basketball FG% you want, but if you want to prove your contention that the league has gotten better with time because variability has decreased, don't you think you'd have to look at many more or even all the different stats, not just FG%?...
> i guess the 1962-63 league overall free throw shooting percentage of .727 is
> also not equal to the 1998-99 league overall free throw shooting percentageWhich can be easily explained away by two things: one, free throw shooting as a skill has not significantly improved since the 1960s because there was no reason for it to do so,
> of .728 because of the "different" defenses too....
come again??? there was no reason for FT shooting to improve?? sorry - but there is every reason for FT shooting to improve, just as there is every reason for FG shooting to improve. the only way one wins games in the nba is by scoring as scoring is the parameter used to determine wins and losses, and if you improve your shooting %s (free throws and shot attempts from the field) you stand a great chance to score more than if you do not improve them - no matter how you improve them.....
the fact that FT% has not improved, rather neither increased nor decreased significantly since 1954-55, yet players have come and gone, is indicative of a similar process that has not changed (the different values for overall yearly FT% being random fluctuations but always near the 74.8% average), despite 2586 different players having played in the league in 47 years since 54-55...
and two, any small increases that were made in this particular skill over that time have been counterbalanced by selection bias; because defense and other non-shooting-related skills are valued more highly now than they were in the past,
"defense and other non-shooting skills valued more highly now than in the past"? a pure assumption not based in any fact whatsoever......lets see some evidence to back up this pure assumption...
Okay, some numbers. Here are the standard deviations of FT% and 2ptFG% since 1947. My
populations include all players with more than 30 attempts.
Season FT% 2FG%
1947 9.6% 4.3%
1948 9.2% 3.9%
1949 8.9% 5.2%
1950 8.3% 4.8%
1951 8.3% 5.6%
1952 8.3% 5.3%
1953 7.7% 5.0%
1954 8.2% 4.8%
1955 7.8% 4.8%
1956 7.9% 4.2%
1957 7.3% 3.9%
1958 8.8% 4.3%
1959 8.0% 4.1%
1960 9.6% 4.8%
1961 9.3% 4.8%
1962 8.8% 5.2%
1963 9.6% 5.4%
1964 9.0% 5.2%
1965 9.7% 5.1%
1966 10.0% 4.4%
1967 10.1% 5.5%
1968 10.4% 5.6%
1969 10.1% 5.4%
1970 7.9% 5.4%
1971 9.5% 5.2%
1972 10.5% 5.5%
1973 9.2% 6.2%
1974 9.0% 4.3%
1975 9.8% 4.2%
1976 8.9% 4.9%
1977 8.4% 5.2%
1978 8.3% 4.5%
1979 9.5% 5.0%
1980 9.2% 5.1%
1981 9.3% 5.9%
1982 9.3% 5.1%
1983 9.0% 5.3%
1984 9.0% 5.7%
1985 8.7% 5.5%
1986 10.4% 5.4%
1987 9.1% 5.1%
1988 9.1% 5.4%
1989 10.0% 5.0%
1990 10.0% 5.9%
1991 10.1% 5.2%
1992 9.0% 5.3%
1993 9.0% 4.9%
1994 9.6% 5.3%
1995 10.3% 5.5%
1996 10.3% 5.4%
1997 10.3% 5.8%
1998 11.0% 5.5%
1999 11.4% 5.7%
2000 10.3% 5.4%
2001 10.8% 5.9%
2002 10.7% 5.0%
Looks to me like a general increase in variation. Whether that constitutes "dilution"
is another matter. The increase is even more apparent if you only look at the top and
bottom 30 players in each category (a reasonable sample, no?).
if you see a general increase it is ever ever so slight - i see similar values from the early 1950s and the late 1990s and variations in between, with no general trend, but random fluctuations...
i would however love to see this for other stats to see if any general trends do appear...