As much as I love the standings gain point approach to valuing players, it does have an a couple of inherent weaknesses.
First, it’s dependent upon some form of league history to work. The whole ranking and valuation process is derived from previous standings data! Those starting new leagues, or joining an existing league, don’t have this information available.
Second, assuming you have prior standings to draw from, I’ve always been bothered by the small sample sizes of that data. And I don’t know about you, but something odd always seems to happen in my leagues. One year someone runs away with it, one year it’s a tight race between five teams, one year we add two teams, the next year we contract a team.
What are we to do?!?!
Thank You OnRoto and NFBC
Thankfully, some very generous league hosting sites have made their standings information publicly available or shared it with me! With their help, I think we can put to bed the concerns over lack of league history and small sample sizes. We have MANY leagues to look at now.
The fine folks at OnRoto.com have shared their NL- and AL-only standings data. If you’re not familiar with OnRoto, their goal is to cater to sophisticated fantasy leagues, many of which play by the “old-school” rules required by “long-term players”. They also are willing to fulfill just about any customization request (more on this later!).
I’ve also written several times about NFBC standings data for mixed leagues.
What follows is a close look at the 2016 12-team “only league” data from OnRoto. If you’re curious, you can see the 2015 AL information here and the 2015 NL information here.
Now, let’s take a look at the data!
AL-Only Standings by Category
Here are the average AL statistics within each rotisserie scoring category:
| RK | PTS | AVG | R | HR | RBI | SB | ERA | WHIP | W | K | SV |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 12 | 0.272 | 987 | 291 | 964 | 128 | 3.583 | 1.191 | 94 | 1,311 | 90 |
| 2 | 11 | 0.268 | 945 | 274 | 926 | 115 | 3.753 | 1.227 | 88 | 1,271 | 79 |
| 3 | 10 | 0.266 | 917 | 262 | 894 | 107 | 3.856 | 1.245 | 85 | 1,229 | 72 |
| 4 | 9 | 0.264 | 889 | 254 | 867 | 100 | 3.934 | 1.258 | 82 | 1,194 | 64 |
| 5 | 8 | 0.262 | 867 | 245 | 846 | 94 | 4.014 | 1.271 | 80 | 1,159 | 57 |
| 6 | 7 | 0.260 | 844 | 236 | 823 | 89 | 4.079 | 1.286 | 77 | 1,133 | 52 |
| 7 | 6 | 0.259 | 824 | 227 | 793 | 83 | 4.160 | 1.298 | 74 | 1,108 | 46 |
| 8 | 5 | 0.257 | 804 | 217 | 773 | 78 | 4.225 | 1.310 | 72 | 1,083 | 40 |
| 9 | 4 | 0.255 | 777 | 207 | 747 | 73 | 4.280 | 1.322 | 70 | 1,048 | 36 |
| 10 | 3 | 0.253 | 743 | 195 | 714 | 67 | 4.386 | 1.339 | 66 | 1,005 | 30 |
| 11 | 2 | 0.250 | 711 | 184 | 681 | 61 | 4.525 | 1.360 | 61 | 961 | 21 |
| 12 | 1 | 0.246 | 636 | 162 | 604 | 49 | 4.728 | 1.392 | 55 | 901 | 11 |
To better explain what you’re looking at, a team could have finished in 10th place in the standings but still finished 1st place in the home runs category. That team’s data appears on the “Rank 1” row, not on the “Rank 10” row.
NL-Only Standings by Category
And here are the NL stats:
| RK | PTS | AVG | R | HR | RBI | SB | ERA | WHIP | W | K | SV |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 12 | 0.276 | 950 | 257 | 915 | 164 | 3.411 | 1.183 | 93 | 1,354 | 88 |
| 2 | 11 | 0.272 | 917 | 244 | 879 | 143 | 3.596 | 1.217 | 86 | 1,284 | 76 |
| 3 | 10 | 0.269 | 883 | 231 | 845 | 133 | 3.710 | 1.232 | 82 | 1,234 | 68 |
| 4 | 9 | 0.267 | 863 | 222 | 816 | 122 | 3.810 | 1.253 | 79 | 1,192 | 61 |
| 5 | 8 | 0.264 | 840 | 214 | 798 | 112 | 3.902 | 1.270 | 75 | 1,155 | 54 |
| 6 | 7 | 0.263 | 813 | 206 | 775 | 106 | 3.994 | 1.284 | 73 | 1,125 | 49 |
| 7 | 6 | 0.261 | 787 | 198 | 743 | 99 | 4.080 | 1.297 | 70 | 1,093 | 44 |
| 8 | 5 | 0.259 | 763 | 191 | 718 | 92 | 4.173 | 1.313 | 66 | 1,062 | 37 |
| 9 | 4 | 0.258 | 740 | 184 | 692 | 85 | 4.241 | 1.329 | 63 | 1,026 | 33 |
| 10 | 3 | 0.255 | 703 | 174 | 660 | 78 | 4.351 | 1.347 | 60 | 991 | 27 |
| 11 | 2 | 0.252 | 673 | 160 | 630 | 70 | 4.445 | 1.372 | 55 | 945 | 20 |
| 12 | 1 | 0.249 | 618 | 143 | 570 | 56 | 4.631 | 1.406 | 48 | 826 | 11 |
Disclaimer Time
Recall how earlier I mentioned that OnRoto is willing to cater to just about any league customization request? While that’s great for all the league managers out there, it’s bad for anyone trying to analyze all that standings data.
Fortunately, OnRoto also provided some roster configuration information for each league. The information included the number of hitters and pitchers allowed on each roster.
This allowed me to exclude obvious outliers, like those that had less than 9 pitchers or 14 hitters. I did not immediately disqualify leagues that allowed for more than 9 pitchers or 14 hitters because it wasn’t clear that those players were starters (they may have been bench slots).
OnRoto also provided the number of IP and AB accrued for each team in all the leagues. This is how I attempted to weed out those leagues that had unusual starting lineups. If a league, as a whole, had significantly above or below average IP or AB, I removed that entire league from my calculations.
After going through this process, I was left with data from 59 AL-only and 43 NL-only leagues. It’s still possible that keeper leagues are mixed among this data, but this still represents a vast improvement over what I’ve been able to find elsewhere.
Overall Standings Results
I’ve written previously about how aiming to finish in third place within each rotisserie category should result in you winning the league. Let’s take a look at if that theory holds up in the only leagues.
| PLACE | AL-ONLY | NL-ONLY |
|---|---|---|
| 1st Place | 100.27 | 98.63 |
| 2nd Place | 92.75 | 90.65 |
| 3rd Place | 84.22 | 82.35 |
| 4th Place | 78.92 | 78.74 |
| 5th Place | 73.04 | 73.49 |
| 6th Place | 67.00 | 67.31 |
| 7th Place | 61.59 | 61.27 |
| 8th Place | 55.66 | 56.74 |
| 9th Place | 50.26 | 51.29 |
| 10th Place | 44.81 | 44.76 |
| 11th Place | 39.32 | 38.86 |
| 12th Place | 30.03 | 29.35 |
When you run the math on an across-the-board third place finish, you end up with 100 points (10 categories * 10 roto points).
The data above suggests that, on average, finishing with 100 points does win the league. But what about the ACTUAL results?
In the 59 AL-only leagues, finishing with exactly 100 points would have only won 49 times! Finishing with 105 points would have won 56 of the leagues. It would have required a total of 107 to win all leagues.
In the 43 NL-only leagues, a 100 point finish was more fruitful, winning 39 of them. Putting of 105 points would have won all 43 leagues.
AL-Only Standings Gain Points
Now that we’ve looked at the standings, we can calculate the raw and relative SGP for the two league types.
| SGP TYPE | AVG | R | HR | RBI | SB | ERA | WHIP | W | K | SV |
|---|---|---|---|---|---|---|---|---|---|---|
| 2016 RAW | 0.0021 | 27.8 | 10.6 | 29.0 | 6.4 | (0.0899) | (0.0158) | 3.1 | 34.5 | 6.6 |
| 2015 RAW | 0.0021 | 25.1 | 8.9 | 25.1 | 6.1 | (0.0770) | (0.0133) | 3.1 | 38.7 | 5.8 |
| 2016 RELATIVE | 0.00007 | 0.96 | 0.37 | 1.00 | 0.22 | (0.0026) | (0.0005) | 0.09 | 1.00 | 0.19 |
| 2015 RELATIVE | 0.00008 | 1.00 | 0.35 | 1.00 | 0.24 | (0.0020) | (0.0003) | 0.08 | 1.00 | 0.15 |
NL-Only Standings Gain Points
| SGP TYPE | AVG | R | HR | RBI | SB | ERA | WHIP | W | K | SV |
|---|---|---|---|---|---|---|---|---|---|---|
| 2016 RAW | 0.0023 | 27.9 | 9.4 | 28.7 | 8.7 | (0.1000) | (0.0181) | 3.7 | 40.1 | 6.5 |
| 2015 RAW | 0.0022 | 28.6 | 9.1 | 28.0 | 8.5 | (0.0919) | (0.0172) | 3.6 | 45.0 | 7.0 |
| 2016 RELATIVE | 0.00008 | 0.97 | 0.33 | 1.00 | 0.30 | (0.0024) | (0.0004) | 0.09 | 1.00 | 0.16 |
| 2015 RELATIVE | 0.00008 | 1.00 | 0.32 | 1.00 | 0.30 | (0.0020) | (0.0004) | 0.08 | 1.00 | 0.16 |
Want the Data to Analyze Yourself?
Have at it. Here’s the AL data and here’s the NL data.
If you like what you’ve read here and want to be informed of other things I’m working on, please follow me on Twitter by clicking below.
Good luck this year, only leaguers! Stay smart.