Welcome Drue Tranquill, ILB, Notre Dame

[Fleet]

Are these the SPARQ ratings that I keep hearing about?

Those are Draftscouts combine and proday numbers.

[Xenos]

Those are Draftscouts combine and proday numbers.

Okay thanks! I keep hearing about how SPARQ played a role in some of the defensive choices that we made because of Bradley and the Seattle connection.

[Formula 21]

I'm pretty happy to have a real backup mlb.

[Xenos]

The more I read about Drue, the more I like this pick. Just hoping he can stay healthy.

[Fleet]

Okay thanks! I keep hearing about how SPARQ played a role in some of the defensive choices that we made because of Bradley and the Seattle connection.

Possible. But i just have a lot of experience with Scout. Those numbers havnt changed in i dont know how many years. Its sad that its a pure pay site these days. I used to be friends with the former owner Jon Cooney. Son of Frank. Who is a big name in the scouting industry.

Im still trying to get access to the site.

[Formula 21]

Tranquill has the 26th best lb score in its history at 98.7. That means his athleticism is in the 98.7 percentile. Theres some pretty great lbs ahead of him, but also some unknowns.

Year	Pos	Name	School	ATRAS	RAS
2018	LB	Lorenzo Carter	Georgia	10	10
2012	LB	Luke Kuechly	Boston College	9.99	10
2006	LB	Manny Lawson	North Carolina State	9.99	10
2018	LB	Leighton Vander Esch	Boise State	9.98	10
2002	LB	Raonall Smith	Washington State	9.98	10
2011	LB	Von Miller	Texas A&M	9.97	10
2007	LB	Zak DeOssie	Brown	9.97	10
2013	LB	Paul Worrilow	Delaware	9.96	9.9
2012	LB	Bruce Irvin	West Virginia	9.96	10
2011	LB	Martez Wilson	Illinois	9.95	9.9
2009	LB	Jason Williams	Western Illinois	9.95	9.9
2015	LB	Stephone Anthony	Clemson	9.94	9.9
2008	LB	Stanford Keglar	Purdue	9.94	9.9
2006	LB	John Chick	Utah State	9.93	9.9
2000	LB	Brian Urlacher	New Mexico	9.93	10
2017	LB	T.J. Watt	Wisconsin	9.92	9.9
2014	LB	Ryan Shazier	Ohio State	9.92	9.9
2012	LB	Miles Burris	San Diego State	9.91	9.9
2002	LB	Scott Fujita	California	9.91	10
2018	LB	Kendall Donnerson	Southeast Missouri	9.9	9.9
2017	LB	Dylan Cole	Missouri State	9.9	9.9
2013	LB	Jeremiah Green	Nevada	9.89	9.9
2007	LB	Quincy Black	New Mexico	9.89	9.8
2019	LB	Quinton Bell	Prarie View A&M	9.88	9.9
2006	LB	Thomas Howard	UTEP	9.88	9.9
2019	LB	Drue Tranquill	Notre Dame	9.87	9.9

[Steve]

Hard to know what to make of them, if this is really the top 26 of all time. The list has a lot of names that really didn't do anything as players. I don't know how it is calculated so it's not clear what it is supposed to mean.

[Boltjolt]

Hard to know what to make of them, if this is really the top 26 of all time. The list has a lot of names that really didn't do anything as players. I don't know how it is calculated so it's not clear what it is supposed to mean.

That's what I was thinking,.... another useless stat lol.

[Formula 21]

Hard to know what to make of them, if this is really the top 26 of all time. The list has a lot of names that really didn't do anything as players. I don't know how it is calculated so it's not clear what it is supposed to mean.

https://sidelionreport.com/2015/06/13/ras-relative-athletic-scores-explained/

RAS: Relative Athletic Scores Explained

by Kent Platte 3 years ago
You've seen it mentioned here before and anyone that follows me on Twitter (@MathBomb), the RAS. It stands for Relative Athletic Score, and I use it to show either a present NFL player or a NFL draft prospect's measurements in relation to their position group. The simple explanation for RAS is that it is a relative score that can show any measurement on a scale of 0-10 where 5.00 is always the average for that position group. We've already shown that the Detroit Lions have the smartest fan base, however, so you probably want more explanation than that, so here is some detail of how I developed the RAS and how it works.

Why Do It? Are 40 Times Not Good Enough?!?!

The short answer to this is no, no they are not. A longer answer is that I developed this score as a way of showing the difference between a 4.52 40 time for a cornerback and that of a defensive end. If you tell a layman that a player ran a 4.52, most won't know what that means. Common rebuttal is "Is that good?" And what's the answer? "Well, yes, I mean for some positions, but it's kind of average for others and not so great for others.

RAS makes it much easier to explain this disparity by position. That same 40 time, 4.52, is a 4.21 out of 10.00 for a receiver, or slightly below average. It's an 8.00 out of 10.00 for a tight end, clearly well above average. It's a 9.82 for a defensive end, or downright elite. Most fans can't recite the average for every position off the top of their head (And if you can, bravo!), so answering whether a score is good or not based on 40 time requires some googling to know for sure. With RAS, it's simple to understand that 5.00 is average, below that is bad, above that is good. Easy.

With RAS, it's simple to understand that 5.00 is average, below that is bad, above that is good. Easy.


It isn't just 40 time, though, I did this for every measurement I could. In its present incarnation, RAS encompasses ten different measurements. Height and weight to cover physical makeup; 40 yard dash and the 20/10 yard splits to cover speed and acceleration; vertical and broad jump to show burst; shuttle and 3 cone to show agility; and bench to show upper body strength. But wait, that still doesn't give us the whole picture! We can't be expected to explain 10 different scores just to know whether we should call someone a good athlete or not! That's right, which is why we have to find that one number to do all that. That's where the RAS Grade comes in.



The RAS Grade
Putting measurements on an easy to understand 0-10 scale is a neat trick, but it doesn't really mean anything on its own. Originally, I used an average of the 10 individual scores. This score was adequate for what I used it for, but it wasn't very user-friendly. 5.00 wasn't really average for most positions, and there were no scores over 8.5 or under 2, so it wasn't truly doing what I wanted it to do.
To accomplish my goal of making a user-friendly metric that anyone can use to show how athletic a player is, I just took the averages for each position and used an old statistical trick called "Weighting for density". Essentially I ranked the qualifying RAS scores from 0 to 10, where 5.00 will again be the middle, 10.00 will be the top score for that position (Like our friend Calvin Johnson in the picture above), and 0.00 will be the dead bottom.
would it matter? In general, athletic ability has a positive correlation to success in the NFL while a lack of athletic ability tends to correlate to the opposite. RAS just puts a number on those sorts of things, and allows us to look at it from a mathematical perspective. I've been pretty successful in using it to gauge draftability and even draft status so far, as it has a much stronger correlation to draft status than it does actual NFL success. Byron Jones, for instance, considered a late 2nd to early 3rd round pick by many during the draft process jumped up charts when he had a monster of a combine. His RAS score actually topped all cornerbacks in my database, and 11 out of the top 20 corners by RAS went in the 1st round, with the remaining 9 going in the 2nd or 3rd. The final RAS Grade calculation allows us to show who had the best overall measurements for a position group, rating a 10.00 out of 10.00. By attaching a number to a player's athleticism, we can use their measurements to realistically compare success at an NFL level to how athletic a player is. Sure, we could do that individually before, pointing out the athletic phenoms that succeed. Players like Brandon Flowers (1.23 RAS Grade), Vontaze Burfict (0.07 RAS Grade), and Antonio Brown (0.62 RAS Grade) would never get the recognition they deserve for really defying the odds, however. Having a higher RAS Grade tends to correlate to NFL success, but it isn't a requirement. The odds are just higher.

[Boltjolt]

https://sidelionreport.com/2015/06/13/ras-relative-athletic-scores-explained/

RAS: Relative Athletic Scores Explained

by Kent Platte 3 years ago
You've seen it mentioned here before and anyone that follows me on Twitter (@MathBomb), the RAS. It stands for Relative Athletic Score, and I use it to show either a present NFL player or a NFL draft prospect's measurements in relation to their position group. The simple explanation for RAS is that it is a relative score that can show any measurement on a scale of 0-10 where 5.00 is always the average for that position group. We've already shown that the Detroit Lions have the smartest fan base, however, so you probably want more explanation than that, so here is some detail of how I developed the RAS and how it works.

Why Do It? Are 40 Times Not Good Enough?!?!

The short answer to this is no, no they are not. A longer answer is that I developed this score as a way of showing the difference between a 4.52 40 time for a cornerback and that of a defensive end. If you tell a layman that a player ran a 4.52, most won't know what that means. Common rebuttal is "Is that good?" And what's the answer? "Well, yes, I mean for some positions, but it's kind of average for others and not so great for others.

RAS makes it much easier to explain this disparity by position. That same 40 time, 4.52, is a 4.21 out of 10.00 for a receiver, or slightly below average. It's an 8.00 out of 10.00 for a tight end, clearly well above average. It's a 9.82 for a defensive end, or downright elite. Most fans can't recite the average for every position off the top of their head (And if you can, bravo!), so answering whether a score is good or not based on 40 time requires some googling to know for sure. With RAS, it's simple to understand that 5.00 is average, below that is bad, above that is good. Easy.

With RAS, it's simple to understand that 5.00 is average, below that is bad, above that is good. Easy.


It isn't just 40 time, though, I did this for every measurement I could. In its present incarnation, RAS encompasses ten different measurements. Height and weight to cover physical makeup; 40 yard dash and the 20/10 yard splits to cover speed and acceleration; vertical and broad jump to show burst; shuttle and 3 cone to show agility; and bench to show upper body strength. But wait, that still doesn't give us the whole picture! We can't be expected to explain 10 different scores just to know whether we should call someone a good athlete or not! That's right, which is why we have to find that one number to do all that. That's where the RAS Grade comes in.



The RAS Grade
Putting measurements on an easy to understand 0-10 scale is a neat trick, but it doesn't really mean anything on its own. Originally, I used an average of the 10 individual scores. This score was adequate for what I used it for, but it wasn't very user-friendly. 5.00 wasn't really average for most positions, and there were no scores over 8.5 or under 2, so it wasn't truly doing what I wanted it to do.
To accomplish my goal of making a user-friendly metric that anyone can use to show how athletic a player is, I just took the averages for each position and used an old statistical trick called "Weighting for density". Essentially I ranked the qualifying RAS scores from 0 to 10, where 5.00 will again be the middle, 10.00 will be the top score for that position (Like our friend Calvin Johnson in the picture above), and 0.00 will be the dead bottom.
would it matter? In general, athletic ability has a positive correlation to success in the NFL while a lack of athletic ability tends to correlate to the opposite. RAS just puts a number on those sorts of things, and allows us to look at it from a mathematical perspective. I've been pretty successful in using it to gauge draftability and even draft status so far, as it has a much stronger correlation to draft status than it does actual NFL success. Byron Jones, for instance, considered a late 2nd to early 3rd round pick by many during the draft process jumped up charts when he had a monster of a combine. His RAS score actually topped all cornerbacks in my database, and 11 out of the top 20 corners by RAS went in the 1st round, with the remaining 9 going in the 2nd or 3rd. The final RAS Grade calculation allows us to show who had the best overall measurements for a position group, rating a 10.00 out of 10.00. By attaching a number to a player's athleticism, we can use their measurements to realistically compare success at an NFL level to how athletic a player is. Sure, we could do that individually before, pointing out the athletic phenoms that succeed. Players like Brandon Flowers (1.23 RAS Grade), Vontaze Burfict (0.07 RAS Grade), and Antonio Brown (0.62 RAS Grade) would never get the recognition they deserve for really defying the odds, however. Having a higher RAS Grade tends to correlate to NFL success, but it isn't a requirement. The odds are just higher.

Thanks for that, but my ADD doesn't allow me to read it all at once lol.
Im looking at it and thinking, WTF is he talking about?

[Xenos]

Thanks for that, but my ADD doesn't allow me to read it all at once lol.
Im looking at it and thinking, WTF is he talking about?

I skimmed through it quickly but he's trying to explain stats and context, and how his formula can help provide guidelines on the success of a lot of NFL players. For example, a fast 40 time isn't as important for a receiver as it is for a corner. There are exceptions of course.

[Steve]

It strikes me he is just trying to make a 0 to 10 point scale to just how good of an athlete a player is. He normalizes it for each position so that 5.0 is average for NFL prospects.

The thing that I don't get is he says that RAS tends to correlates to NFL success. OK.....what does that mean. I can do the correlation, but what is success? Is it getting drafted? Is it starting (I still don't know what people mean by starting players, but whatever..) .....Is it overall play for their position (pro bowl .... all pro....HOF.... ).

This is some of the Moneyball nonsense that is so popular. Trying to get things to one number that means something by itself. IN a game of 11 moving pieces, that is split into plays with a million situations, how can 1 number really sum things up?

Moneyball works in baseball because it is easy to isolate things. If things are very, very simple, statistics do closely suggest that that correlation and causation are the same things (they aren't but they are close).

Football, there are so many things going on at once, it is impossible. In complex physical systems, a scientist would never use statistics unless he could complete isolating the conditions so his statistics really do isolate things. If you can't, why would you think using statistics is a good idea. At least in the boiling everything down to one number sense.