Why You Should Aim for Third Place

Finish third in each rotisserie category and you’ll win the league. We’ve all heard or read that at some point. Where does it originate from? Is it founded in fact?

I’ve spent a lot of time acquiring and analyzing standings data of late (AL-only, NL-only, mixed).  And looking at that information got me to thinking that I could easily determine if finishing third across-the-board is really what it’s cracked up to be.

Turns out that it is. Finishing third in all ten categories would have won 67 of the 76 AL-only leagues and 47 of the 51 NL-only leagues I looked at.

But in looking at things a little closer, I found an even better reason you should set your sights on finishing third. One that had never crossed my mind.

While trading e-mails with the folks at OnRoto about the AL- and NL-only standings data, they pointed this out to me…

“My experience is that the SGPs are actually bell shaped within each category… which has an impact on how you should set up your team.”

Relax

I just mentioned SGP. Not everyone uses standings gain points. I know this. But hold on! Even if you use z-scores, PVM, or the auction calculator to value your players, the concept of moving up and down the standings is really what we’re about to look at. Moving up the standings applies to everyone! This article is not about valuation or even ranking players.

Regardless of your preferred valuation methodology, when playing fake baseball games our goal is to move up the standings one spot at a time. We can all look at a given set of standings and see that it might take 15 runs or 0.06 ERA points, on average, to move up to that next spot.

The Data Used

I downloaded and cleaned up the 2015 NFBC Main Event standings data (30 leagues, 450 teams). Here are the average standings of those 30 leagues:

2015 NFBC Main Event Standings
RANK BA R HR RBI SB ERA WHIP W K SV
1 0.275 1,075 287 1,031 170 3.22 1.14 109 1,484 108
2 0.272 1,040 276 1,003 156 3.38 1.18 102 1,425 97
3 0.271 1,018 268 983 148 3.49 1.20 99 1,391 90
4 0.269 1,004 261 973 142 3.55 1.21 96 1,364 86
5 0.268 993 256 960 135 3.62 1.22 94 1,346 81
6 0.267 980 250 947 130 3.67 1.23 92 1,325 78
7 0.265 970 245 933 127 3.71 1.23 90 1,311 74
8 0.265 956 241 923 122 3.76 1.24 89 1,293 70
9 0.263 943 236 912 117 3.81 1.25 87 1,279 68
10 0.262 932 230 899 113 3.85 1.26 85 1,259 63
11 0.261 919 225 885 107 3.89 1.27 83 1,243 57
12 0.259 904 219 870 104 3.96 1.28 80 1,211 50
13 0.258 886 210 850 98 4.02 1.29 79 1,180 42
14 0.255 861 198 826 89 4.11 1.30 75 1,128 33
15 0.252 822 186 784 76 4.28 1.32 69 1,043 17

I then used that average standings data to determine the average stats needed to climb up one spot in the standings.

Stats Required to Reach Next Position in Standings
TO REACH BA DIFF R DIFF HR DIFF RBI DIFF SB DIFF ERA DIFF WHIP DIFF W DIFF K DIFF SV DIFF
1 0.0029 34.9 11.0 28.7 13.2 0.153 0.038 6.9 58.9 10.5
2 0.0017 22.9 7.8 19.8 8.7 0.117 0.014 3.0 33.6 7.3
3 0.0018 13.0 7.7 10.3 5.6 0.052 0.012 3.1 27.2 4.1
4 0.0012 11.2 4.4 12.7 6.9 0.070 0.008 2.0 18.0 4.8
5 0.0010 13.0 5.8 13.2 4.8 0.054 0.010 2.4 21.0 3.0
6 0.0012 10.2 5.0 13.7 3.5 0.036 0.007 1.5 13.8 3.9
7 0.0009 14.0 4.5 9.9 5.3 0.059 0.009 1.3 18.2 4.1
8 0.0012 12.8 4.8 11.5 4.9 0.044 0.011 2.1 13.9 2.5
9 0.0011 11.2 6.4 12.7 4.1 0.045 0.007 2.1 20.1 4.1
10 0.0014 13.4 4.3 13.8 5.6 0.041 0.008 2.0 16.2 6.3
11 0.0015 14.8 6.3 15.3 3.2 0.064 0.010 2.4 31.7 7.3
12 0.0017 17.3 8.8 19.2 6.2 0.065 0.013 1.9 31.5 7.9
13 0.0026 25.6 12.2 24.7 9.1 0.088 0.012 3.8 51.7 9.3
14 0.0029 38.4 12.2 41.9 13.0 0.170 0.021 5.7 84.8 15.5

For example, you can see that, on average, first place in the standings table was 287 HR and second place was 276 HR. That’s a difference of 11 HR to climb from second place to first, and you see that in the first row of the “HR DIFF” column above.

Looking at the data, you can see some bell shaped phenomenon playing out. The numbers in the middle of the standings are noticeably smaller than at the edge of the standings. It’s still a little hard to absorb, so I also graphed each category out.

Here’s a look at runs, home runs, and stolen bases:

R_GRAPH

HR_GRAPH

SB_GRAPH

For fear of causing Carpal Tunnel, I won’t make you scroll through all ten categories of graphs, but you can view them individually by clicking these links (R, HR, RBI, SB, AVG, W, K, SV, ERA, WHIP). Or you can take my word for it that all ten demonstrate the same phenomenon.

What Do You Notice?

Each category is slightly different, but for the most part it’s clear that the standings are bell shaped (I’ll get to Saves in a minute). The red line on each graph represents the standings gain points calculation (this is also represented in the parentheses in the title of each graph).

For example, according to my own calculations on this NFBC data (using Excel’s SLOPE calculation), it takes 15.19 runs to move up one spot in the standings. That 15.19 calculation does not take into account exactly where your team is in the standings. It’s more or less an “average” calculation with the effect of outliers being mitigated.

When you look at the graphs you see that the “on average” nature of the SGP calculation has some weaknesses. When you’re at the edge of the bell curves it takes much more to reach the next team in the standings (to reach 1st, 2nd, 12th, 13th, 14th, and sometimes 3rd). When you’re in the middle of the curve it’s almost always easier to move up the standings than the “on average” SGP calculation indicates.

Moneyballing

Despite a fear of being accused that I don’t really understand what Moneyball was about (that’s never happened in the FG comments), I’ll make the analogy anyways. It seems like we have an inefficiency to take advantage of here.

In an auction or in a draft, we have a limited amount of resources or draft picks to work with. So it becomes imperative to spend those resources wisely and in the most efficient way possible. Given the bell shaped curve we see in these graphs, it’s most efficient to spend or draft players that can position you to come in third place.

As you move up the curve in an effort to reach second or first place, it becomes more costly and a less efficient use of your resources. If you project yourself to be in third in HR and seventh in SB, you should first allocate resources to the SB gap. A given amount of resources will get you further in the SB category than in HR.

Saves Are Different

Check out the saves graph:
SV_GRAPH

The curve is skewed further left than the others. It’s difficult to climb that curve from the bottom of the standings (the steepness here is surely due to punting and teams that didn’t plan on punting but then threw in the towel when their closers flamed out). Once you get past that part of the curve the teams are very tightly packed, with the average distance between teams being less than four saves!

Practically Speaking

This is all well and good. But what does this really mean? I’m a skeptic by nature. So I can imagine some of you are thinking, “What do you think happens, Mr. Bell? Do you think I’ll shoot for third and everyone else will aim for fourth and fifth, and the plan works perfectly? It’s not like the other managers in my league aren’t trying to do the same thing.”

Another skeptical thought I have is that I usually walk out of my drafts with the highest projected totals in nearly all categories. This is not to toot my own horn. I’m sure you have similar experiences. This is due to the biased or self-fulfilling nature of using a set of projections and preferences that nobody else will be using (read Todd Zola here).

With that skepticism in mind, here are a few practical ways you can apply this information:

  • You should try to track team projected stats during your draft or have historical targets in mind about what it will take to finish around third. If you customize projections, don’t use those same projections to calculate the projected standings. Use an unbiased resource, like Steamer (without your tweaks and edits). Try to keep your team in the middle of the standings (or bell curves).
  • Avoid trying to “run away” with a category during the draft. It’s misguided. Not only are you wasting stats (you only need to beat second place by one), it can be extremely costly to do so.
  • Don’t sweat it if one or two other teams themselves try to “run away” with categories. Stick with but try to beat the rest of the pack.
  • The ideal strategy is to build a balanced team that is set up to be in the middle to top of the pack in each category. Don’t punt! Especially if punting means you’ll be sacrificing a category you could easily move up in for categories where you’re trying to climb the steep end of the bell curve. Once you feel confident that your team will be in the thick of the race in each category, then you can get aggressive and try to climb the extreme parts of the curve.
  • Perhaps the best thing you can do on a practical side is to continue performing the four bullet points above regularly as the season progresses. Use Steamer’s rest-of-season projections and monitor where you’re likely to fall.



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Tanner writes for Fangraphs as well as his own site, Smart Fantasy Baseball . He's written two e-books, Using SGP to Rank and Value Fantasy Baseball Players and How to Rank and Value Players for Points Leagues, and worked with Mike Podhorzer developing a spreadsheet to accompany Projecting X 2.0. Much of his writings focus on instructional "how to" topics, Excel, and strategy. Follow him on Twitter @smartfantasybb.

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Lenard
Member
Member
Lenard

This is why America is falling behind. Let’s not just aim for first place, let’s take it by the throat and make it ours. This is how we make America great again. /poutyface

ashtray
Guest
ashtray

This third place talk is for losers. I will be so good at winning all the categories I get tired of winning. Go big or go home.

HappyFunBall
Guest
HappyFunBall

Saves are Un-American. Let’s build a wall to keep out the closers. And we’re going to make Tony LaRussa pay for it!