Beating the Season Over-Under Follow-Up

Before the 2007 season began, I proposed a system that appeared to be able to systematically beat Las Vegas over-under lines on team wins. For the 2007 season, the results are in. The system's record would have been 8 correct, 3 incorrect, with 1 push (73% correct).

The system itself consists of two rules:

1. For teams predicted to win 9.5 games or more, bet on the under.
2. For teams predicted to win 6.5 games or less, bet on the over.

In other words, bet on mediocrity.

Historically, the system would have been 70% correct over the previous two years, and slightly over 58% correct over a 10 year period between 1996 and 2005. By betting 'over' on teams predicted to win 6 or less, instead of 6.5 or less, the overall rate would have improved to 61%.

Here is how the system fared this year. Over-under lines were taken from bodog.com on 6/30/07.




















UndersLineActualResult
SD1111-
BAL9.55

W
CHI10.57

W
IND1112L
NE11.516L
DEN9.57

W
PHI9.58

W
CIN9.57

W
OversLineActualResult
DET67W
CLE610

W
HOU6.58

W
BUF 6.57W
OAK54L


One thing I learned watching the results develop over the season is that the system is more successful the earlier in the year that the over-under lines are taken. Early in the year, long before training camps open, there is the least amount of information and the more likely it is that over-under lines are set based on the previous season's results. This is when uncertainty would be greatest, and perhaps when overconfidence is accordingly great. When looking for records of the over-under lines, I noticed that the earlier the line, the more confident it was--i.e. the further from 8 wins teams were predicted to win.

As player movements, retirements, injuries, team schedules, and pre-season games come into focus, over-under lines move to reflect the new information. Uncertainty is reduced, and the overconfidence would be mitigated. It might therefore better to place bets earlier rather than later in the pre-season, capitalizing on maximum uncertainty.

Why the System Works

The system is based on three principles:

1. The NFL season is extremely difficult to predict.
2. Regression to the mean is very strong in the NFL.
3. People are overconfident in their ability to predict team wins.

Humans, including NFL fans and gamblers, are susceptible to cognitive biases, and I believe these biases affect prediction markets. Cognitive (or heuristic) biases are systematic errors in judgment made in certain situations. These biases exist probably because they benefited early humans in their efforts to adapt and survive. For example, the "overconfidence effect" may bias people toward action rather than passivity in the face of a challenge.

But in a prediction situation, overconfidence is counterproductive. People who believe their prediction abilities are better than they truly are would take excessive risks. In one survey 80% of respondents claimed they were in the top 30% in driving skills. Similarly, it's likely that most gamblers also believe that they have some special ability or intuition to predict outcomes--otherwise they wouldn't be gambling.

Hindsight bias, also known as the "I knew it all along" effect, may also be a factor in fooling people into forgetting how poor their predictions really are. Ask yourself how well you thought New England would do this year. Be honest. According to the betting lines, half of all people thought they'd win 11 games or fewer. Remember how Randy Moss was supposed to be a "cancer?" How about the Bears? Half of bettors believed Chicago would win at least 11 games this year. But as the Bears floundered this year, many people forgot just how good they were expected to be--just on their defense alone. Most fans, including tv commentators, forget how uncertain things were before the first snap of the season. They say "it was obvious the Patriots would be unbeatable. They have Randy Moss!" or "obviously the Bears fell flat, Rex Grossman is terrible." I know that's my first instinct.

People also tend to remember correct predictions and forget incorrect ones--both by themselves and others. Today I noticed the cover page of an obscure football "prospectus" book I bought in August. It trumpeted, "Last year, we correctly predicted player X would have a breakout year! We said team Y would return to the playoffs!" That a book of over 300 pages of NFL predictions made four or five correct guesses is not an accomplishment. But it's the correct ones that are remembered.

Many people are also unable to grasp the concepts of randomness or luck. They discount regression to the mean because they expect extreme performances to continue. In the NFL, a team that finishes with a 14-2 record was probably a "fundamentally" 12-4 team that got lucky in a couple games. Fans and bettors may expect much of that 14-2 performance to carry over into the next season, thinking that 11 or 12 wins is a safe bet. But in reality, the team was a "12-win" team the previous season, so the chance of repeating such a successful year would be lower than expected. This effect is compounded when the same phenomenon affects a team's opponents. For example, part of the reason the Ravens and Bengals did not reach their over-under expectations is because division rival Cleveland improved from extremely poor performance.

This field of heuristics and decision-making fascinates me. I'm sure there is a lot of money to be made in not just betting markets, but equity markets. The one thing about sports though, is that it's relatively easy to analyze statistically. And no. I'm sorry to report I did not put my money where my mouth is.

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4 Responses to “Beating the Season Over-Under Follow-Up”

  1. Anonymous says:

    Remember Bill James' plexiglass principle, that teams who improve a lot one year tend to drop back the next? I used that to take the under on New Orleans (9.5), and it worked. Barely.

    My "under" bet on New England, though ... well, that didn't work out as well.

  2. Brian Burke says:

    The reverse would be true too, I suppose. Teams that collapse probably bounce back more than expected. Many observers may not account for injuries, luck, or other temporary circumstances.

  3. Doug Walters says:

    Hence why I predicted Washington and Tampa Bay to be "bounce back" teams. Regression to the mean works both ways.

  4. Anonymous says:

    Have you taken into account the juice?

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