ROTISSERIE: SGP Denominators for 2018

For those new to the concept, Standings Gain Points (SGPs) estimate the amount of a given statistic you would need to move up one point in the standings in a standard 5x5 roto league, based on the distribution within each category. For example, depending on the league and the season, 18 runs, on average, would move you up one place in the final standings. A player who scores 54 Runs above replacement level would then be worth a three SGPs in runs. SGPs have the advantage of measuring every category on the same scale, so you can simply add up a player's SGPs to gauge his value. (For further discussion of valuation methods, see the Forecaster's Toolbox.)

To determine SGPs you need to know the distribution (or "lumpiness") of the standings. The best source of SGP data is from your league's history, especially if you've had the same scoring system and number of teams for a while. You can take the standings for each category and use the SLOPE function in Excel (or LINEST function in Excel or OpenOffice) to calculate the best fit between the individual stats totals and the points for each rank (use points as the X value and the stat totals as the Y value; this may be counter-intuitive to those who speak math, but it works). Check your numbers against the tables below for reasonability.

If you don't have good data for your league, are in a new league, or just don't trust your math skills, you can use these denominators here. Just be aware that there's good and bad in using "generic" numbers like these. The bad part is that valuations can be very sensitive to the denominators (i.e., small changes in a denominator, especially in the "average" categories can cause large changes in valuations). However, that may dispel the illusion of precision that dollar values sometimes give us. You're much better off thinking of a player in terms of dollar ranges ($25-$30) rather than a specific number ($27). Better yet, think in terms of overall value ("second tier") rather than as a priceable quantity.

The Denominators

SGP denominators fluctuate from year to year and league to league. In order to mitigate the outliers, we take the average SGPs across many leagues and use a weighted average of the past three seasons. By averaging across a large sample, we hope to produce the most likely (note: not the "correct") distribution. Note that the dollar values you generate from SGP are not likely to match the projections on or in the Baseball ForecasterSince standings gain points are sensitive to the league context, they require historical data to estimate accurately., therefore, uses PVM (percentage value method) for its player values.

Below are the values for the three most common league types—12-team AL- and NL-only, and 15-team mixed—as well as values for 10-team leagues. The "formula" shows you how to calculate the SGP for each player. The ideal method would be to calculate performance above replacement level. This is usually found by running a preliminary valuation and taking the average of the first 5 or 10 players who fall below the draftable line.

Offense was up in 2017, which led to a wider distribution among players in the offensive categories, so most of those SGP values have risen. We also saw some shifts in pitcher usage, with fewer pitchers putting up 180+ innings. As a result, the counting categories in pitching, Wins and Ks, have seen declines in SGP values. At the same time, the SGP values for ERA have increased quite a bit, as the bottom-tier pitchers are more affected by the surge in offense than the top-tier pitchers.

Things you should know

These numbers are based on leagues with 14 hitters and 9 pitchers. While we allow for minor variations when calculating the denominators, the AB and IP totals are strictly based on leagues with a 14/9 configuration. All of the leagues were 5x5.

The AB and IP totals for AL-only and NL-only leagues may differ. This makes sense intuitively, as the AL has 15 more everyday hitters, and they tend to pinch hit less in the AL than in the NL.

15-Team Mixed

Category    SGP     Formula
========  =======  ==========
Runs        18.1    Runs/18.1
HR           7.9    HR/7.9
RBI         20.5    RBI/20.5
SB           7.2    SB/7.2
AVG       0.0015    (((1871 + Hits) / (7000 + AB)) - 0.267) / 0.0015

W            2.5    W/2.5
Sv           6.1    Sv/6.1
K           32.5    K/32.5
ERA       0.0752    (3.94 - ((569 + ER) / ((1300 + IP) / 9))) / 0.0752
WHIP      0.0129    (1.257 - ((1635 + H + BB) / (1300 + IP))) / 0.0129

12-Team NL Only

Category    SGP     Formula
========  =======  ==========
Runs        28.0    Runs/28.0
HR           9.5    HR/9.5
RBI         28.1    RBI/28.1
SB           8.5    SB/8.5
AVG       0.0021    (((1505 + Hits) / (5700 + AB)) - 0.264) / 0.0021

W            3.4    W/3.4
Sv           6.4    Sv/6.4
K           41.2    K/41.2
ERA       0.0897    (4.21 - ((561 + ER) / ((1200 + IP) / 9))) / 0.0897
WHIP      0.0165    (1.323 - ((1587 + H + BB) / (1200 + IP))) / 0.0165

12-Team AL Only

Category    SGP     Formula
========  =======  ==========
Runs        25.9    Runs/25.9
HR           9.8    HR/9.8
RBI         26.8    RBI/26.8
SB           6.5    SB/6.5
AVG       0.0021    (((1600 + Hits) / (6200 + AB)) - 0.258) / 0.0021

W            3.2    W/3.2
Sv           6.0    Sv/6.0
K           36.9    K/36.9
ERA       0.0885    (4.23 - ((564 + ER) / ((1200 + IP) / 9))) / 0.0885
WHIP      0.0153    (1.302 - ((1562 + H + BB) / (1200 + IP))) / 0.0153

10-Team Mixed

Category    SGP     Formula
========  =======  ==========
Runs        19.7    Runs/19.7
HR           8.4    HR/8.4
RBI         20.0    RBI/20.0
SB           8.2    SB/8.2
AVG       0.0019    (((2015 + Hits) / (7500 + AB)) - 0.269) / 0.0019

W            3.2    W/3.2
Sv           7.6    Sv/7.6
K           40.2    K/40.2
ERA       0.0894    (3.95 - ((658 + ER) / ((1500 + IP) / 9))) / 0.0894
WHIP      0.0161    (1.261 - ((1891 + H + BB) / (1500 + IP))) / 0.0161

10-Team NL Only

Category    SGP     Formula
========  =======  ==========
Runs        29.4    Runs/29.4
HR          10.5    HR/10.5
RBI         29.6    RBI/29.6
SB          10.4    SB/10.4
AVG       0.0024    (((1646 + Hits) / (6200 + AB)) - 0.266) / 0.0024

W            3.9    W/3.9
Sv           8.8    Sv/8.8
K           44.7    K/44.7
ERA       0.1017    (4.19 - ((558 + ER) / ((1200 + IP) / 9))) / 0.1017
WHIP      0.0188    (1.316 - ((1579 + H + BB) / (1200 + IP))) / 0.0188

10-Team AL Only

Category    SGP     Formula
========  =======  ==========
Runs        25.7    Runs/25.7
HR          10.9    HR/10.9
RBI         27.0    RBI/27.0
SB           7.6    SB/7.6
AVG       0.0023    (((1714 + Hits) / (6600 + AB)) - 0.260) / 0.0023

W            3.7    W/3.7
Sv           7.9    Sv/7.9
K           41.4    K/41.4
ERA       0.0957    (4.18 - ((603 + ER) / ((1300 + IP) / 9))) / 0.0957
WHIP      0.0168    (1.292 - ((1680 + H + BB) / (1300 + IP))) / 0.0168

4x4 Leagues and other mythical creatures

The denominators shouldn't change in standard 4x4 leagues; they would be the same within each category. But if your league doesn't exactly match the parameters of one of the above choices, you can make some adjustments. In general, you should adjust upward for each statistic in smaller leagues. The smaller the league, the greater the adjustment. And the adjustments should be bigger in the lumpier categories (SB, W, Sv). If you're unsure, you can experiment with different settings until a handful of test players look "right" to you.

If you use categories other than the canonical 5x5, Ed DeCaria has some suggestions:

For those that use categories beyond the typical 5x5, the best solution is to use your own league's historical data (to the degree possible), or match up your non-standard category to the 5x5 category that it most closely resembles in terms of statistical distribution (e.g., OBP should behave similarly to batting average, triples should behave similarly to stolen bases, holds might fall somewhere between wins and saves).

Here's one last tip: don't be bound by the numbers. Make adjustments until they look reasonable to you overall (don't worry if a few players seem out of line). And remember that the dollar values are just a guideline. Other factors, including potential for changes in playing time, injury risk, and regression should play large roles in your buying decisions. And most of all, have fun.

A thousand thanks to the folks at OnRoto for providing the league data that made this analysis possible.

Click here to subscribe

  For more information about the terms used in this article, see our Glossary Primer.