Beating an Efficient Market

Despite what various racetrack touts and system peddlers say, one of the things that makes consistently beating the races so tough is that, for the most part, pari-mutuel betting markets are efficient. This means that all the relevant and available information affecting the outcome of a horse race is generally known and accounted for. Hence, the final odds are an accurate reflection of a horse’s chances of winning — minus the track take and breakage, of course.

Sure, there are pockets of inefficiency and irrationalism. Scholars have long documented the existence of a “favorite-longshot bias,” whereby shorter-priced horses are slightly underbet and longer-priced horses slightly overbet. However, such inefficiencies are but ripples on the pari-mutuel ocean.

Still, the fact that inefficiencies can and do exist provides hope that the races can be beaten — just like grainy, out-of-focus video footage provides hope to some that bigfoot lives among us (often disguised as a broken tree branch).

In this article, I will attempt to show readers how they can spot and capitalize on inefficient markets — as well as efficient markets — to make more moolah at the racetrack.

Follow the Money 

Not to go all “Deep Throat” on everybody, but the simplest way to spot an efficient or inefficient market is to follow the money. Consider the following scenario:

John Doe is given $2 to bet to win on any horse running at Saratoga on Saturday.

* How does he choose what race to bet?

* How does he choose which horse to bet?

Well, assuming Mr. Doe is logical, one would expect him to play the race and horse that (he believes) give him the best chance of winning. However, even if Doe possessed the superior handicapping acumen of a dart-throwing monkey or one of those omnipotent racetrack touts mentioned earlier, it is clear that any market comprised solely of his wager would have to be inefficient. For, even if we ignored the fact that Doe’s horse would be 1-9, we are stuck with the unfortunate detail that all the other horses in the field — those that didn’t receive any of Doe’s dough — would be lumped together at 99-1.

Obviously, this is not an accurate assessment of each horse’s chances.

Thus, even though this was an extreme example, it should be self-evident that less money and fewer wagers equal a less efficient market. Might the opposite also be true? Does more money and more wagers lead to a more efficient market?

I decided to find out.

To provide a baseline, I first looked at all sole betting favorites (no favored entries) from a variety of races run across the fruited plain from September to December of 2013:

Number – 7,996

Winners – 2,904

Win Rate – 36.3%

$2 Net – $1.67

IV – 2.80

OBIV – 0.84

Next, I analyzed favorites in races with the lowest straight (win, place and show) handle on the card (provided the total pool was less than $10,000). As expected, the numbers took a nosedive, giving credence to my hypothesis that less betting/money results in a less efficient market:

Number – 185

Winners – 61

Win Rate – 33.0%

$2 Net – $1.50

IV – 2.11

OBIV – 0.75

Lastly, I looked at races with the greatest straight handle on the card (provided the total pool exceeded $10,000). Not surprisingly (at least to me), the figures were fantastic:

Number – 830

Winners – 320

Win Rate – 38.6%

$2 Net – $1.73

IV – 3.35

OBIV – 0.89

In races featuring above-average betting action, favorites won 38.6 percent of the time, lost just 13 cents per dollar wagered (compared to 16 cents for favorites overall) and had an impact value (IV) of 3.35 (versus 2.80 for favorites on the whole).

The Efficient Data Hypothesis

Now, I know what some of you are thinking: big deal, Derek, your “fantastic figures” still produced a loss of 13 percent. What good does it do to identify efficient and/or inefficient pari-mutuel markets if one still loses one’s shirt?

Keep your chin up, Daniel-san. It’s not so much what the stats tell us about these specific instances, it’s what they imply about handicapping in general. Let’s go back to the definition of market efficiency: all the relevant and available information affecting the outcome of a horse race is generally known and accounted for.

To me, this suggests that “all the relevant and available information affecting the outcome of a horse race” may be overvalued or undervalued in races attracting more or less wagering dollars, respectively. In other words, rather than patterning one’s handicapping around specific race conditions — placing extra value on workouts in two-year-old races, stressing class in turf races, etc. — a player might be better served by using the straight wagering pools to emphasize or de-emphasize traditional factors.

Take speed figures, for example. Using the database of races above, I compiled the following stats on horses possessing the best last-race Brisnet speed figure over today’s general track surface (AW/dirt or turf):

Number – 6,353

Winners – 1,835

Win Rate – 28.9%

$2 Net – $1.74

Nothing to get the pulse racing, right? Well, if you’re standing up, grab a chair (you’ll want to be sitting) and look at what happens when the digits above are parsed based on the size of the win, place and show pools:

STRAIGHT MUTUEL POOLS GREATER THAN OR EQUAL TO $25K

Number – 4,299

Winners – 1,209

Win Rate – 28.1%

$2 Net – $1.70

STRAIGHT MUTUEL POOLS LESS THAN $25K

Number – 2,054

Winners – 626

Win Rate – 30.5%

$2 Net – $1.83

In races with less than $25,000 in the win, place and show pools, the horse(s) with the top last-race speed figure produced a loss of just eight cents on the dollar — nearly half the loss produced in races with higher pool totals.

Get the point? By gauging the relative efficiency of the market one is betting into — be it the first race at Arapahoe Park or the feature race at Del Mar — my research suggests that well-known predictive factors like speed and class can be upgraded or downgraded accordingly.

And that, my friends, is what good handicapping is all about.