August 27, 2012 - by Tom Federico
This is the second chapter of our Pick’em Strategy Playbook, a series of blog posts on football pick ’em contest strategy. In general, we are compiling this Playbook from past related posts on TeamRankings.com, as well as recent insights and studies we’ve done. We also post advice on NFL survivor pool strategy, as well as weekly contest analysis during football season.
Our first chapter of the Pick’em Strategy Playbook explored how skilled players can generate a substantial edge in pick’em style contests, and why pick’ems represent an attractive ROI opportunity. In this second chapter, we’ll review how we define success in pick’em contests, and illustrate a few of the more common traps that tend to snare a lot of misinformed pick’em players.
When it comes to measuring success in pick’em contests there are two metrics that make the most sense to evaluate. We’ll refer to them as primary and secondary metrics, since the first is more important:
Case Study 3: More Home Runs Is Better Than A Good Batting Average
For the sake of illustration, consider the following three pick’em players, who all have participated in their company’s last 10 NFL office pools. Each contest attracted around 100 players, and had a $10 entry fee. The top 5 finishers (top 5%) win money.
Which of these people would you rather be?
Obviously this is an extreme example, but the clear answer is Harry. (If you don’t agree, you might as well stop reading now.) You certainly don’t want to be Tom, who probably just sucks at NFL pick’ems. Tom’s case illustrates the fact that never coming close to winning is definitely a bad sign.
Dick, on the other hand, is a curious case. He’s got a great batting average from the standpoint of outperforming expectations, but he’s not hitting any home runs; he’s not winning. Bad luck may well be the reason. But the fact that Dick has never won, coupled with the fact that Harry has cashed not one but two times, suggests that something deeper may be going on here.
As it turns out, there are a lot of Dicks in your office pool. (I swear I did not plan that one, it just happened.) By not understanding optimal pick’em strategy, these people inadvertently maximize their odds not to do poorly, but by doing so, they sacrifice their best chances to actually win. The most typical pitfalls from a strategy point of view are:
All this brings us to Harry, who appears to be employing strategies that maximize his odds to win and/or maximize his expected return. He’s hit two dingers, defying the odds by cashing twice in a 100-person pool in just 10 years. Sure, he’s struck out three times along the way. But who cares? Whether he finishes at the 25th percentile or the 75th percentile, the result is the same: he loses his $10 entry fee.
You need to adopt Harry’s mentality to win big in pick’em contests in the long term. You also need the appropriate information and analysis skills to implement an informed, data-driven decision making process. It takes equal parts math and guts — math to figure out when an unpopular or counterintuitive pick makes sense, and guts to actually go through with it, and be comfortable with the consequences if it doesn’t work out.
We can help with the math part, but the guts need to come from you.
We’ll conclude this chapter with a case study illustrating how someone like Harry (or TeamRankings) would use data, intuition, and some quick math to identify a great picking decision — one that most of his opponents would either be too scared or too ignorant to make.
Case Study 4: The Most Likely Winner Trap
Here’s the situation: You are contending for first place in 200-person NFL game winner based pick’em contest. The buy-in was $5 and the first place finisher gets it all: $1,000 in cash. There is only one game left to pick in the season, and you’re tied for first with 10 other people. There are no tiebreakers in the contest. If multiple people tie for first, they split the $1,000 pot.
The Patriots are favored by three points over the Jets in this deciding game. After doing some research, you think that the Patriots have about a 60% chance to win. Also, you’d guess that probably 7 or 8 of your 10 opponents are going to go with New England. The Patriots are a popular team, they’re the safer pick, and there’s a lot of money on the line.
What’s your optimal strategy here?
In our experience, most people would say, “OK, don’t mess this up. I’m tied for first, there’s a lot of cash on the line, and I want to win some money. Why take an unnecessary risk? Take the Patriots and be happy with a share of the pot.”
Well, here’s the math behind your two options, assuming 8 of your 10 opponents pick the Patriots:
It’s not even close. Picking the Jets is by far the better option, offering twice the expected return, with overall odds of winning that are not terribly lower than the alternative. And what if only 7 of your competitors and not 8 take the Pats? According to the math, it’s still a better decision to pick the Jets, if your goal is to maximize your expected return.
So even in a contest built around picking winners, in a case like this one you can increase your expected return by picking the expected loser! The only way to figure it out is to run the numbers. And if the Patriots win, everyone will call you an idiot. It’s still the better decision.
Coming Up Next In Part 3
With our high-level framework for evaluating success pick’em contests defined, in the next chapter, we’ll dive into the nuts and bolts: the specific factors you should evaluate on a week to week basis to maximize your odds to succeed at pick’em contests, including both game predictions and non-football factors. Check back
tomorrow (Tuesday) soon. (Ed. Note: Sorry, still working on this…)
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