I'm working on my pre-rankings, and I've always had difficulty factoring in the "rate" stats into my rankings.

I'm coming up with point values for each category in a pretty standard statistical way ((projected value - league average)/std dev)) which works fine for all counting stat categories, but doesn't work as well for rate stats because it doesn't factor in the number of AB or number of innings pitched. So I'm just basically ignoring AB (which isn't a big deal since most guys on fantasy lineups will have about 400-600 AB), and also ignoring IP. That sucks because my model is overranking relievers who pitch 1/3 the innings, and underrating pitchers who throw 230 innings. I could just add a 6th category and factor in innings pitched (doing the same STD Dev calculation), but then it would overrate pitches compared to to hitters (since they'd have 6 categories instead of 5)

First figure out your leagues average player. For AVG you take the number of players on your starting lineup minus one and multiply the AB's and H's by that. What this gives you is a league average team in AB/H minus a single player (you are about to add a player).

Now add your players AB's and H's to that number and calculate the AVG your team would have after that new player is added. Then subtract the league average from that and do your STD deviation calculations according to that.

Does that make sense?

So if your average player had 550 AB, 154 H's and a .280 AVG and you had a 14 man lineup.

Your average team would have 550x14 AB, 154x14 H's. However you want to subtract one player because you are seeing how much a single player helps the team. So you would take 550x13 AB's, 154x13 H's which is 7150 AB's and 2002 H's for a .280 AVG.

Now if for example you take a player with 600 AB's, 200 H's and a .333 AVG. He makes your totals 7750 AB's and 2202 H's for a .2841 AVG or an increase of .0041.

If you take a player with 300 AB's, 100 H's and a .333 AVG makes the totals 7450 AB's, 2102 H's for a .2821 AVG or an increase of .0021.

If you takea player with 550 AB's and 175 H's and a .318 AVG he makes your totals 7700 AB's and 2177 H's for a .2827 team AVG or an increase of .0027 AVG.

So adding a player to your team with 300 AB's and 100 H's would be slightly less valuable than adding one with 550 AB's and 175 H's even though the 300 AB guy has a higher AVG.

Last edited by Ender on Sat Feb 09, 2008 1:45 pm, edited 1 time in total.

Don't make this too hard. You need to convert ERA and OPS to some sort of a counting number.... one where the larger the number, the better... just like every other stat.

Look at your League's average OPS and average ERA from last year. Not MLB's averages, but your league's averages. They will be better, as you probably don't play too many scrubs.

Now assign a plus minus to each player. These numbers will be less than one for OPS, an nearly everyone will be less than one (in absolute value) for ERA. A handful of pitchers will be either a run better or a run worse than the league average.

Now multiply those numbers by either plate appearances for batters or innings for pitchers.

There you have it. You now have counting numbers. And they are even more "telling" than the other stats, such as wins or run scored, because you can see negative numbers, which literally drag down your team stats. Catchers will be less of a negative than you think in OPS because they will play less than someone who has a terrible year and plays every stinkin' day ( say, someone like Punto last year).

I take my projections, seperate by position. Then I add up all the stats to whatever categories your league has. For example, I add up all the first basemen's Runs, HRs, RBIs, ABs, Hits, SBs. (You can figure out SLG pct, OB pct, OPS etc).

Then I take the totals from each column and divide them by the number of first baseman, or eligible for first base. Sofor example the average 1B might hit .278, score 80 Runs, hit 23 HRs, drive in 86 RBIs and steal 4 bases.Then in a new set of columns I subtract those totals from my calculation. The first baseman I am comparing to hit .290, scores 95 Runs, hit 30HRs, drive 100 RBIs, and steal 0 bases.

I then do something like column 1 95 runs (projected player) minus 80 runs (average player) for a total of 15. Average works something like this (.290-.278)*the ABs the projected will get, say 500ABs. That's my total. Add up all the different scoring categories you have and you know what the projected player is worth versus other first basemen.

If you do this for each position then you take into account position scarcity.

Look in the Fantasy Baseball questions section and Elijah had a good post on this. I based my system at the start off of that, and evolved it to what I do now. (It still evolves)

using the suggestions here, I've put the formulas togther based on aggregated projected stats from Dierkes, Chone, Sportsline, and Marcel.

Based on my formulas against the projected stats, here's the top 25 that came out. (this league counts OPS instead of BA, so guys like Crawford, Reyes, and Hanley get a bump down)

How close do you think this is to a good ranking? Again, this is all calculation drive, and I haven't adjusted anything based on my preferences.

1 ... 11.46 .... Rodriguez, Alex 2 ... 9.84 ..... Howard, Ryan 3 ... 9.63 ..... Pujols, Albert 4 ... 9.54 ..... Ortiz, David 5 ... 8.30 ..... Holliday, Matt 6 ... 8.21 ..... wright, david 7 ... 8.03 ..... Cabrera, Miguel 8 ... 7.89 ..... Fielder, Prince 9 ... 7.15 ..... Ramirez, Hanley 10 .. 6.44 ..... utley, chase 11 .. 6.24 ..... Dunn, Adam 12 .. 6.13 ..... teixeira, mark 13.. 6.11 ..... Rollins, Jimmy 14.. 6.00 ..... Reyes, Jose 15.. 6.00 ..... Guerrero, Vladimir 16.. 5.96 ..... sizemore, grady 17.. 5.92 ..... Berkman, Lance 18.. 5.83..... Braun, Ryan 19.. 5.64..... soriano, alfonso 20.. 5.29 ..... Beltran, Carlos 21.. 5.06 ..... Lee, Carlos 22.. 4.86 ..... Hafner, Travis 23.. 4.34 ..... Jones, Chipper 24.. 3.84 ..... Ramirez, Manny 25.. 3.84 ..... Pena, Carlos

If you are happy with the system, it's all that matters. I always tinker with my formulas trying to see if the new results are better, or worse in my opinion.