2012 vs. 2013 Miami Dolphins: A Statistical Comparison | Page 2 | FinHeaven - Miami Dolphins Forums

2012 vs. 2013 Miami Dolphins: A Statistical Comparison

shouright said:
In terms of the variables that are most strongly correlated with winning, that doesn't show up in the data.

---------- Post added at 01:51 AM ---------- Previous post was at 01:49 AM ----------

No, but I get to have a little more insight about the team than I would otherwise, so I'm not blindsided later by expecting something from it that I probably shouldn't have. ;)
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Yea not being able to stop the run has nothing to do with with winning. I enjoy your different style of posting but much like PFF just because you crunch a number doesn't make it more relevant.
 
FinfanInBuffalo said:
What a weasel.

Was your conclusion that Tannehill was more at fault than an average QB for the sacks based on your "objective evidence" wrong or not? Don't duck the question.
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I think you'll find the relevant responses from me in the thread in which this was already discussed. What we're talking about here is a comparison between the 2012 and 2013 team.
 
When banging your head against a wall isn't enough:
Carmeetswall-1.gif
 
shouright said:
I think you'll find the relevant responses from me in the thread in which this was already discussed. What we're talking about here is a comparison between the 2012 and 2013 team.
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:lol2:

Translation: Shouright has no idea what he is talking about so posting contradicting statements doesn't seem wrong.
 
shouright said:
No the dependent variable is win percentage, which is continuous.
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That's interesting. I'm wondering if a model that tries to predict won/loss would give us a different view on this. Predicting positive outcomes (wins) in X number of attempts could be an interesting exercise. The challenge with any of this type of Analytics is the difficulty in projecting in forward from a game planning standpoint. Eg, "we are going to try to run the ball X times, obtain Y YPA when all is said and done", etc. Do you know if we use stats folk to provide input to the coaching staff such as my overly simplified example above?
 
royalshank said:
That's interesting. I'm wondering if a model that tries to predict won/loss would give us a different view on this. Predicting positive outcomes (wins) in X number of attempts could be an interesting exercise. The challenge with any of this type of Analytics is the difficulty in projecting in forward from a game planning standpoint. Eg, "we are going to try to run the ball X times, obtain Y YPA when all is said and done", etc. Do you know if we use stats folk to provide input to the coaching staff such as my overly simplified example above?
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Here's one example:

http://www.buffalobills.com/news/ar...of-Lyons/3bf96f90-a18a-4845-aaae-2d20cc83d72b
 
royalshank said:
Interesting - let's hope their statisticians are < our statisticians :)
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This must have been disappointing to the forum's resident statistician:

While Lyons’ work will provide additional data to the football department it will be far from the sole determining factor in making football decisions.
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