by **greenandgold** » Fri Dec 08, 2006 7:57 pm

I've got a method that I have been working on for the last couple of seasons and I think it is good now. It is position and scoring specific for roto leagues and has a way to rate the value of a SB to a HR to a high average. It is kind of involved so if you have any questions let me know.

The idea is to make an average team, constructed by creating an average player in each position and putting the together. I do this by averaging R, HR, SB, RBI, H, AB over the "top" 20 at each position (top 60 for OF) to get the average player and from here I can calculate the stats of my average team. There is a recursive step to calculate the "top" players at each position, for an initial ranking I just use OPS. This idea is that in a typical league only the top 20 players are used at each position so the rest can be forgotten.

Once I have the average team I calculate how adding a specific player to the team (say Pujols) will change the team stats, so in this case subtract the average 1st baseman stats and add in Pujols stats. This allows me to compute how much Pujols (or any other player) will impact the average team.

Next I decide on my roto targets (right now I am using 1000/260/1000/150/.310). Once I have these I compute how close I get to these stats by having Puljos on the team and a way to rate them. I add all 5 of these things up to get a total rank and sort on this total rank to find the "top" players (this is the recursive step).

For Pujols I have

.0713 /.1535 /.0810 /.0809 /.2750

which can be read as Pujols gives me about 7% of needed runs over the average 1st baseman, 15% of homers over the average 1st baseman, 8% RBI, 8% SB, and about a third of my needed average.

For comparison, I give Carl Crawford

.0280 /-.0481 /-.0101 /.8609 /.1693

so he helps TONS in steals but he actually has lower HR and RBI stats then the average OF.

It's not really a projection formula but instead tells you how much a player is worth in a 5x5 roto league in a way that is weighted for position and scoring - for projection I just do some weighted 3 year average and adjust based on who I think will breakout/slump.

The main problem is that it gives high rankings to people who do really well in one catagory but maybe not so good in others. People like Pierre/Roberts/Roberts/Figgins are high because of their SB totals and players with high average get ranked high too. Likewise, people with low average are ranked really low (Dunn and Glaus). If I raise my target average and target SB then this problem is less but I feel bad doing that because it adds my bias instead of just going with targets that will win a league.

Here are a couple outputs from 2006 stats

R/HR/RBI/SB/AVG/TOT

C

-----

Joe Mauer /.0840 /-.0182 /.0496 /.1024 /.3471 /.5649

Brian McCann /.0051 /.0994 /.0747 /-.0193 /.2037 /.3636

Víctor Martínez /.0714 /.0139 /.0747 /-.0598 /.1432 /.2433

Iván Rodríguez /.0461 /-.0182 /.0077 /.1024 /.0138 /.1518

Paul Lo Duca /.0650 /-.1037 /-.0482 /.0010 /.1394 /.0536

Jorge Posada /.0177 /.0887 /.0747 /.0010 /-.1368 /.0453

Kenji Johjima /.0051 /.0353 /.0272 /.0010 /-.0540 /.0146

Russell Martin /.0177 /-.0502 /-.0035 /.1430 /-.1017 /.0052

Jason Kendall /.0524 /-.1464 /-.0454 /.1633 /-.0194 /.0045

Josh Willingham /.0082 /.1208 /.0216 /-.0193 /-.1469 /-.0155

1B

-----

Albert Pujols /.0714 /.1523 /.0807 /.0811 /.2769 /.6624

Ryan Howard /.0240 /.2485 /.1142 /-.0609 /.1585 /.4844

Lance Berkman /-.0044 /.1096 /.0779 /.0000 /.1626 /.3457

David Ortiz /.0587 /.2058 /.0807 /-.0406 /-.0497 /.2549

Justin Morneau /.0019 /-.0080 /.0611 /.0000 /.2231 /.2781

Travis Hafner /.0114 /.0775 /.0248 /-.0609 /.0958 /.1487

Paul Konerko /.0019 /.0027 /.0137 /-.0406 /.1508 /.1285

Jim Thome /.0366 /.0775 /.0025 /-.0609 /-.0378 /.0179

Lyle Overbay /-.0455 /-.1363 /-.0449 /.0406 /.1449 /-.0412

Nick Johnson /.0114 /-.1256 /-.0868 /.1420 /-.0229 /-.0819