This is a moderated phorum for the CIVILIZED discussion of the Miami Dolphins. In this phorum, there are rules and moderators to make sure you abide by the rules. The moderators for this phorum are JC and Colonel.
BTW, I have never advocated trading down from no. 8. I think it would be stupid to do so given the talent that would be available at 8 in all positions, Floyd, Reiff possibly, Ingram or Coples.
ChyrenB Wrote:
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> BTW, I have never advocated trading down from no.
> 8. I think it would be stupid to do so given the
> talent that would be available at 8 in all
> positions, Floyd, Reiff possibly, Ingram or
> Coples.
But, with the 15 or so "studs" (Crowder's term) available if Miami traded down no further than 15, Miami could still get a good player, along with an additional 2nd round pick.
Crowder52 Wrote:
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> Yes he is defintely reading this site, I think
> alot of them do, to get a feel for ideas for
> stories... Alot of stories I see in local papers
> fall a couple days behind a good topic here...
> that being said I thought this commenters argument
> as to the validity was pretty strong as well, so I
> though i would share it
>
> THe bigger myth is that statistics outside of
> controlled experiments mean much of anything -
> except revealing spurious correlations. Take your
> 2nd round QB numbers. Even your adapted numbers
> mean nothing. Any accuracy would demand far more
> data. You cannot compare success rates unless you
> also knew (for example): how strong was the team
> they went to, what was their opponents records,
> who were the starting QBs in front of them and how
> long did they block the draft choice from playing,
> how good were the coaches, did they play in
> cold/warm weather, etc. You can certainly run
> analysis that takes these kinds of things into
> account (e.g. multiple regression), but you NEVER
> see that in sports discussions. The other problem
> is that even though everyone knows there is
> missing data, they tend to discount how much it
> distorts the accuracy of their interpreation.
> Without the data from a single key variable the
> conclusions are not just 'a little bit'
> inaccurate, they often are totally meaningless.
> The tendency when we cannot get the 'right' data
> is to pretend the almost right data is nearly just
> as good. It is not. It is nearly impossible to
> know if it means anything. Having said that,
> thanks for the interesting piece
Thanks for sharing Crowder. That is a great comment. It is impossible to conclude a direct correlation with so many uncontrolled variables.
That's why they say: There are lies, damn lies, and statistics.
Crowder52 Wrote:
-------------------------------------------------------
> Yes he is defintely reading this site, I think
> alot of them do, to get a feel for ideas for
> stories... Alot of stories I see in local papers
> fall a couple days behind a good topic here...
> that being said I thought this commenters argument
> as to the validity was pretty strong as well, so I
> though i would share it
>
> THe bigger myth is that statistics outside of
> controlled experiments mean much of anything -
> except revealing spurious correlations. Take your
> 2nd round QB numbers. Even your adapted numbers
> mean nothing. Any accuracy would demand far more
> data. You cannot compare success rates unless you
> also knew (for example): how strong was the team
> they went to, what was their opponents records,
> who were the starting QBs in front of them and how
> long did they block the draft choice from playing,
> how good were the coaches, did they play in
> cold/warm weather, etc. You can certainly run
> analysis that takes these kinds of things into
> account (e.g. multiple regression), but you NEVER
> see that in sports discussions. The other problem
> is that even though everyone knows there is
> missing data, they tend to discount how much it
> distorts the accuracy of their interpreation.
> Without the data from a single key variable the
> conclusions are not just 'a little bit'
> inaccurate, they often are totally meaningless.
> The tendency when we cannot get the 'right' data
> is to pretend the almost right data is nearly just
> as good. It is not. It is nearly impossible to
> know if it means anything. Having said that,
> thanks for the interesting piece