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Definitive IDP Positions (1 Viewer)

Jiggyonthehut

Footballguy
Well, let me state my intentions. After seeing my IDP players go one way or another, I decided to attempt to take matters into my own hands and create a matchup sheet that shows what each positional LB (ie. SLB, MLB, WLB) averages, tackle-wise, against every offense in the NFL. My plans were to make two seperate sheets in excel, one for 3-4 defenses and one for 4-3 defenses. However, I ran into major problems- NFL.com simply does not provide definitve LB positions and I often see LB's slated in multiple positions (Take for example most of the New England Linebackers) or not-exactly-accurate positions (Morrison as a 3rd string MLB). It bears saying that it is a problem more with the 3-4 schemes, but in order for my numbers not to be skewed higher, Id like to know which LB's play were most of the time.If anyone can provide this information, Id be most grateful. I plan on sharing this information with the IDP'ers here as an extra from myself if there are no objections to the FBG.com staffers. So if you all could compile a list or direct me to one, I think we both end up winning here. Let me know please.

 
Neat... I have a request, as long as you're putting together the data:

I prefer to see this type of data presented as "what a team allows to a player at each postition compared to what that player's average score is" - like the data in the FP matchups that FBG does.

An issue with LBs is whether they're in on nickel packages or not. I suggest ignoring that because there just won't be enough useful data if you break it down too far.

 
compared to what that player's average score is" - like the data in the FP matchups that FBG does.

An issue with LBs is whether they're in on nickel packages or not. I suggest ignoring that because there just won't be enough useful data if you break it down too far.
Youll have to explain that to me- im not quite sure im following what you are requesting. As for the nickel packages, I have the feeling that if I do include them, it wont really make an appreciable difference- so Im not worried if I accidentally do once or twice- but youre right Im definately trying to steer clear from it to be as accurate as possible. If there was any confusion as to my first post, the format will be the following: 2 excel sheets, one for 3-4 defenses and one for 4-3 (however the 3-4 is basically useless thus far in the season, most teams aside from San Diego have only faced one such defense thus far and so its not a good sampling)

 
This is a great idea - would you share this information with the rest of us? I sure could use some helpful matchup advice to follow. :yes:

 
compared to what that player's average score is" - like the data in the FP matchups that FBG does.

An issue with LBs is whether they're in on nickel packages or not.  I suggest ignoring that because there just won't be enough useful data if you break it down too far.
Youll have to explain that to me- im not quite sure im following what you are requesting. As for the nickel packages, I have the feeling that if I do include them, it wont really make an appreciable difference- so Im not worried if I accidentally do once or twice- but youre right Im definately trying to steer clear from it to be as accurate as possible. If there was any confusion as to my first post, the format will be the following: 2 excel sheets, one for 3-4 defenses and one for 4-3 (however the 3-4 is basically useless thus far in the season, most teams aside from San Diego have only faced one such defense thus far and so its not a good sampling)
This is tough to explain for some reason.If Ray Lewis scores an average of 20 FP/game, but against KC he scores 28

AND Brad Kassell scores an average of 5 FP/game, but against KC he scores 13

then KC is allowing 8 more FPs to opposing MLBs than those MLBs score on average.

At the same time, if Mike Peterson scores an average of 20 FP/game, and against Chicago he scores 20 FP

AND Brian Urlacher scores an average of 21 FP/game, and against Chicago he scores 21 FP

then Chicago is allowing 0 more FPs to opposing MLBs than those MLBs score on average.

That's how I would like to see the data presented, because if you just tell us what teams allow on average to opposing MLBs, KC and Chicago both allow 20.5 FP/game. However, you want your guy playing KC in this example.

 
Ah i do see what you are getting at here and it sounds like an excellent idea.In order to do that, Ill have to do BOTH the method of finding out what opposing WLB, MLB and SLB score against a particular team and then the indivudual breakdown of how much the average player does against said team vs. their average score. Just might take a bit more time to completeVery good suggestion- not only can you see the stats by team, you can compare similar matchups this method. :thumbup: Ill get to work on it very soon.

 
compared to what that player's average score is" - like the data in the FP matchups that FBG does.

An issue with LBs is whether they're in on nickel packages or not.  I suggest ignoring that because there just won't be enough useful data if you break it down too far.
Youll have to explain that to me- im not quite sure im following what you are requesting. As for the nickel packages, I have the feeling that if I do include them, it wont really make an appreciable difference- so Im not worried if I accidentally do once or twice- but youre right Im definately trying to steer clear from it to be as accurate as possible. If there was any confusion as to my first post, the format will be the following: 2 excel sheets, one for 3-4 defenses and one for 4-3 (however the 3-4 is basically useless thus far in the season, most teams aside from San Diego have only faced one such defense thus far and so its not a good sampling)
This is tough to explain for some reason.If Ray Lewis scores an average of 20 FP/game, but against KC he scores 28

AND Brad Kassell scores an average of 5 FP/game, but against KC he scores 13

then KC is allowing 8 more FPs to opposing MLBs than those MLBs score on average.

At the same time, if Mike Peterson scores an average of 20 FP/game, and against Chicago he scores 20 FP

AND Brian Urlacher scores an average of 21 FP/game, and against Chicago he scores 21 FP

then Chicago is allowing 0 more FPs to opposing MLBs than those MLBs score on average.

That's how I would like to see the data presented, because if you just tell us what teams allow on average to opposing MLBs, KC and Chicago both allow 20.5 FP/game. However, you want your guy playing KC in this example.
I see two potential problems with this. First, if Brian Urlacher scores any FP's against Chicago I'm guessing he'll be looking for a new job. :P Second, this is entirely dependent on how a particular league scores. For instance, in my league (see scoring below) for anyone to score 28 FP in a single game they would have to have like 15 solo tackles, 3 int, a sack and a couple of fumble recoveries. Our league is very tackle oriented where other league reward big plays more. To me it would be more helpful just to see raw data. Then I can put that raw data into my own spreadsheet that converts it into scores.
 
yes, I am only doing tackle data with this work- sacks and TO's would have to be seperate to keep it objective and fact based.For the record I plan on using 1 pt/ tackle and .5/assist as that is what Ive seen most leagues- including my own- use. And its quite simple that way: for example a score of 15.6 means roughly 15 solos and 1 assist or 14 and 3 and thus forth- you use what numbers you feel most comfortable with. It would simply be too hard for me to equate solos and assists as equals.PS: Im seriously considering doing solos and assists seperate to get accurate numbers in both. I relalize the logic faliure in having tackles as 1 and .5 but it sure makes work a hell of a lot longer.

 
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