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(Jamal Haynes is below the fold)
And we have an oc + qb that get the ball out to receiver in flat. Both have complimented each other AND WHEN WE RUN ( wo rpo) on slant we get good yards.Finally got a decent OL coach.
Elko and Leopold are the 2 that have done the best job based on where they were starting from imo. Johnathan Smith at Oregon State is another that has done a really good job.Just shows what a great job Elko has done
At an individual level it is highly inaccurate, but at an aggregate level it is fairly accurate and directional.Team talent composite is not a very useful metric for measuring anything even remotely detailed. If players were rerated every year it might be a little better, but as it stands, everything is based on their high school ratings which we all know are regularly wrong, sometimes by a lot. Guys like Tariq Carpenter and Keion White, despite being NFL-level talent, count as 2 stars towards the composite, and guys like Antonneous Clayton count as 4/5 stars despite never coming anywhere close to that level of performance.
Problem though is our talent composite was shifted towards skill guys on offense and defense. We did not have the right players to run the offense Collins forced upon us making it seem so much worse.At an individual level it is highly inaccurate, but at an aggregate level it is fairly accurate and directional.
Because Duke has been playing the same weak schedules for decades and not winning at the same rate that Elko has been able to. He took over a team that went 3-9 and immediately went 9-3 against a similar schedule. It was their first winning record since 2018, and their first winning record in the ACC since 2015. They have a pretty good chance to have back to back .500 or greater ACC records for the first time since Cutcliffe did it 3 times in a row from 2013-15. Before that stretch, their last winning record in the ACC was 1994.The fact that everyone talks so favorable of Elmo just goes to show how irrelevant strength of schedule is. Duke plays and beats nobody and they are crowned as something beyond what they are. The only team they beat was a down bad Clemson who was truly atrocious to start the year. I’ve never seen a team more lauded for accomplishing little. They pretty much did the same thing last year, winning a bunch of game against nobody’s. I wonder what people would have said about Collins if he’d have gotten to skate by on easy Duke schedules.
I certainly haven't analyzed their talent, but I think Cutcliffe left Elko some talent when he retired. Much more so than Roof left him.Because Duke has been playing the same weak schedules for decades and not winning at the same rate that Elko has been able to. He took over a team that went 3-9 and immediately went 9-3 against a similar schedule. It was their first winning record since 2018, and their first winning record in the ACC since 2015. They have a pretty good chance to have back to back .500 or greater ACC records for the first time since Cutcliffe did it 3 times in a row from 2013-15. Before that stretch, their last winning record in the ACC was 1994.
Their schedule this year is much tougher than last year’s hence the drop in wins. They played 3 of the top 4 ACC teams (Tech is the only one they missed), plus Clemson, plus Notre Dame, plus UNC. As a college coach you get judged based on what your predecessors did. They are the ones that set the standard for your expectations. Cutcliffe had some solid years based on Duke’s history, especially after taking over for Ted Roof who went 4-42 in 4 full seasons. But I would say nobody has made such a big impact so quickly at Duke as Elko has since Steve Spurrier did in the 80s.
Collins didn’t get the benefit of Duke’s scheduling, but he did inherit a much better overall program with much higher expectations than what he would have at Duke. The historical standard for Tech coaches is to win 7 games a year. If you can do that, you’ll be considered “alright.” Fail to do so and you’ll be considered a failure, do more than that and you’ll be considered a great. Not all schedules are created equally, but neither are all programs or their expectations.
Tech is a hard job. There’s another thread on Jamey Chadwell, and he took a much easier job at Liberty. The theme I see there is that we didn’t put together enough money to hire him, but I think he probably wanted the much easier job and would have taken a lot less for that.*I certainly haven't analyzed their talent, but I think Cutcliffe left Elko some talent when he retired. Much more so than Roof left him.
So, from these charts, should we conclude that if the data is properly parsed along the lines of how teams actually schedule games (G5-P5), our resume is more likely to get worse with a harder schedule?Now, I need to clean this up with some stats. Maybe this is why the “make the schedule easier” vs “you gotta schedule big teams to build a program” argument never settles out.
There is one easy thing I see from this—P5 is one cluster of difficulty, and G5 is another one. It’s two different leagues. (This is where people say “oh, duh”, but the blue-green and the red clusters could be squished together a lot more. Maybe it’s the conferences and all the in conference games, but there’s a real separation between the two “leagues”.So, from these charts, should we conclude that if the data is properly parsed along the lines of how teams actually schedule games (G5-P5), our resume is more likely to get worse with a harder schedule?
This is why we stratify data. Overall, it looks like the harder the schedule the better the resume'. However, when you stratify and look within the constraints of the two strata, you see both actually decline. I'd wager if he produced a GoF metric, the two latter charts will both produce better fits than the one composite chart.There is one easy thing I see from this—P5 is one cluster of difficulty, and G5 is another one. It’s two different leagues. (This is where people say “oh, duh”, but the blue-green and the red clusters could be squished together a lot more. Maybe it’s the conferences and all the in conference games, but there’s a real separation between the two “leagues”.
Then it gets into what you do with the data. Normally, you’d do the first chart. If you were only looking at P5 teams, you’d get a different result. There probably aren’t enough games played between the G5 and P5 teams to justify having one big regression between them (just a guess). I also wonder how good a metric “strength of schedule” is if we don’t have enough games between the G5 and P5 teams.
Also, Nate Manzo didn’t give a correlation coefficient or a hypothesis test. Without those, I kinda guess “meh, it’s probably not that strong a relationship” based on just my preconceptions. But, I can see how people would find the examples to justify their arguments of “schedule HARDER” vs “No! Schedule EASIER!”.
Agree, which is why I've circled back to "inconclusive". Even if we isolate P5/G5, there doesn't appear to be a very strong correlation between the variables.There is one easy thing I see from this—P5 is one cluster of difficulty, and G5 is another one. It’s two different leagues. (This is where people say “oh, duh”, but the blue-green and the red clusters could be squished together a lot more. Maybe it’s the conferences and all the in conference games, but there’s a real separation between the two “leagues”.
Then it gets into what you do with the data. Normally, you’d do the first chart. If you were only looking at P5 teams, you’d get a different result. There probably aren’t enough games played between the G5 and P5 teams to justify having one big regression between them (just a guess). I also wonder how good a metric “strength of schedule” is if we don’t have enough games between the G5 and P5 teams.
Also, Nate Manzo didn’t give a correlation coefficient or a hypothesis test. Without those, I kinda guess “meh, it’s probably not that strong a relationship” based on just my preconceptions. But, I can see how people would find the examples to justify their arguments of “schedule HARDER” vs “No! Schedule EASIER!”.
On right now on CBS.