Fantasy Rankings Prep (Part 1 of 3)

About four times a season, Eno unleashes the shocky monkeys and a few of us slow-footed writers are forced to enjoy ranking all the players. For the next few days, I am going to go over how I prepared my rankings.

Note: I am trying to keep the amount of math to a minimum. If somewhere you get lost in the procedure let me know and I can explain the procedure in more detail.

The first item to remember is all leagues are not even close to being the same. In my three keeper leagues, two are points based and the other is an AL only league with one pitcher category being Wins+Saves+Holds. Additionally, some leagues have keepers. How the keeper’s “salary” is set determines a their value. Other league options have innings pitched limits (good rates stats needed) or as in the case of my league with W+S+H, an IP minimum is set to keep owners from only using relief pitchers. Catcher rankings can vary quite a bit from a one catcher to  two catcher leagues or even two catcher slots with a 162 game limit as in Ottoneu. For my rankings, I did them off a basic 5×5 12-team league with 23 positions (14 position players, 9 pitchers).

If possible, I like to use the standing points gained method (a couple of explanations on the methodology). Some other methods may or may not be better, but I like it because it shows the league’s biases and gives me good baselines for final league positioning. I will not go into every gory math detail of the ranking method, so you may want to go back read the two articles previously reference or read Art McGee’s book, How to Value Players for Rotisserie Baseball or Larry Schechter’s new book, Winning Fantasy Baseball.

To get my values, I calculated the average final 2013 values from the last 20 teams to draft at NFBC last year. Here are the final totals and averages for each place in the standings along with the value (slope method) it takes to jump up one position in the standings.


1st 0.280 1109 293 1075 191
2nd 0.276 1078 272 1039 176
3rd 0.273 1048 266 1016 167
4th 0.271 1035 260 996 159
5th 0.269 1020 252 977 153
6th 0.268 1007 247 965 145
7th 0.267 987 241 949 139
8th 0.265 975 237 931 130
9th 0.263 960 229 917 120
10th 0.261 926 220 897 113
11th 0.259 899 208 854 107
12th 0.256 840 191 796 93
Average 0.267 990 243 951 141
Change to move up 0.00195 20.8 7.8 21.4 8.2


Rank ERA Wins WHIP Strikeouts Saves
1st 3.11 109 1.13 1496 122
2nd 3.27 102 1.16 1446 110
3rd 3.34 100 1.18 1404 102
4th 3.40 97 1.19 1370 95
5th 3.48 94 1.21 1347 90
6th 3.55 92 1.22 1323 84
7th 3.62 90 1.23 1303 80
8th 3.68 88 1.25 1281 75
9th 3.76 85 1.26 1256 69
10th 3.85 82 1.27 1221 61
11th 3.95 76 1.29 1149 52
12th 4.10 70 1.32 1063 35
Average 3.59 90 1.23 1305 81
Change to move up 0.081 3.0 0.015 33.3 6.8

These tables can be used for two purposes.

Number 1:  Knowing where your teams stands during drafts and auctions.

I keep track of a couple of items (in the points leagues, just one, total points) during the draft to make sure I am not getting too unbalanced, SB and HR (possibly AVG). Once a player is picked, just total their projected stats. You can then know how close you are at getting to a value which will put you too high in the rankings and over killing a stat.

One item to notice is how the top and bottom one or two teams are further away from the pack. These teams won by too much and wasted the stats they accumulated. When you are building a team, don’t aim for the previous top value, aim for just more than second place.

Number 2:  Value Players.

Well, I am going to go stop here and go over this step in detail in my article tomorrow. Please let me know if you have any questions so far.

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Jeff writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won three FSWA Awards including on for his MASH series. In his first two seasons in Tout Wars, he's won the H2H league and mixed auction league. Follow him on Twitter @jeffwzimmerman.

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I am in the process of ranking my pool of fantasy players, using the standings gain points (SGP) method. My problem is that my league went from 11 to 12 teams this year. We have been at 11 teams for the last 7 years so I have a ton of SGP data for our 11 team league. Is there a way to correlate that data to a 12 person league, as our league only has 13 hitters and 8 pitchers per team (we only use 1 catcher, and have 5 util slots instead of CI/MI/Util) and all of the generic SGP data I can find is based on 14 hitters / 9 pitcher leagues (generally with 2 catchers). This matters because I really don’t have to adjust for positional scarcity with only 12 catchers being drafted, and don’t necessaryily have to draft an additional MI. If anyone can help, it would be much appreciated.