There isn’t a simple way to make player values look pretty, especially if you’re trying to keep the scoring system/lineup simple. And you don’t really need a study to determine the numbers.
This is how I would approach it.
1. Decide your offensive scoring system and standard lineup. Plug it into a test MFL league and write down the total points for the top overall player and bottom tier starters for each position. For example, if you have a 12 team, start 2 RB league, write down the year end point totals for the #1, #12, #24 players. You can grab more data points if you like but it’s not really necessary.
2. Decide how closely you want the defensive points to mirror the offensive points. Do you want the #1 LB to approximately equal the #1 RB, #5 RB, #16 RB etc.
3. Understanding that a standard 3-4 rush OLB has a totally different statline than a steady 4-3 MLB, decide if you want them about equal or skewed one way or the other. Similarly, understanding that a standard CB has a different statline than a standard SS, make a similar determination in value there.
4. In a spreadsheet, play with scoring values such that the defensive rank lists reflect the relative value to the offensive guys you like and such that the different types of players within a given position rank how you want them.
Two possible solutions, though neither are particularly simple, are to break out CBs, DTs, or OLBs and/or (as was suggested above) make the points per stat different for each group of player, i.e. a DE gets more points per sack than a LB/DB.
To give a few real life examples, here are some 2006 statlines for a couple typical rush linebacker compared to a couple solid but not spectacular MLBs and how they’d compare in different scoring systems – just varying sack values.
All lines = solo/assist/sack/FFandFR/INT/PD
2006 Demarcus Ware 59/15/12/6/1/6
2006 Shaun Phillips (proj) 54/24/12.5/6/0/9
2006 Lofa Tatupu 93/30/1.5/3/1/7
2006 Kirk Morrison 102/26/1/2/2/5
Player Sack=3 Sack=4 Sack=6 Sack=8Ware 194 206 230 254Phillips 195 208 234 258Tatupu 241 243 247 249Morrison 253 254 256 258That’s why it’s generally considered that awarding around 3x tackle per sack is considered neutral. It’s a little closer to 3.5 in some situations, but you get the point.Once you’ve found the right relative distribution within each defensive position on your spreadsheet, then you can compare the tiers to the offensive side and alter the percentages of a defensive stat or two or add a stat like sack yardage to make the distribution among all positions equal.
There really is no way, though, to keep the same scoring system for every defensive player and have the DL distribution similar in points to the other positions. If you want that to happen – and many leagues just leave the middle ranks of the DL relatively low because tweaking the numbers will send the studs way, way up your lists – you’re going to have to make DL sacks or tackles worth fractionally more.
Again, choosing a couple of representative statlines and plugging them in the spreadsheet like the LBs above is the best way to do this. The spreadsheet lets you tweak whatever stat you want and immediately see the effect. And, IMO, a few representative statlines is key because looking at the entire set of statlines and rank lists may give you a skewed data set in any given season. So, I'd use the sheet rather than MFL if you really want to be precise because you'll be playing with a lot of stats and changing the parameters of the MFL sham league will get tedious after awhile.
Hope that helps.
, thats a lot.
, thats a lot.
