Showing posts with label fair odds. Show all posts
Showing posts with label fair odds. Show all posts

  • Beating an Efficient Market

    POSTED Aug 21, 2014 By Derek Simon
    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.

  • The Difference Between Probability & Profitability

    POSTED Jul 19, 2014 By Derek Simon
    If there is one mistake that I see both new and veteran handicappers make time and time again it is confusing probability with profitability — often in very inconsistent and haphazard ways.

    For instance, most bettors know that the post-time favorite wins approximately 1/3 of the time, making it a highly predictive factor. In fact, we can measure just how predictive by employing “impact values,” which were explained by Dr. William Quirin in his masterful work “Winning at the Races.”

    Impact values, or IVs, are calculated by “dividing the percentage of winners with a given characteristic by the percentage of starters with that characteristic,” Dr. Quirin explained.

    “An IV of 1.00 means that horses with a specific characteristic have won no more and no less than their fair share of races,” the good doctor concluded. Similarly, an IV greater than 1.00 denotes that a particular factor is producing more than its fair share of winners, while an IV below 1.00 means that it is producing less than its fair share.

    With that in mind, take a peek at the digits I obtained in an examination of 14,505 races featuring a sole betting favorite (no entries):

    Winners: 5,409
    Winners: 2,017
    Win Rate: 37.3%
    IV: 2.76

    What this means is that the post-time favorite can be expected to win 2.76 times more often than random chance would dictate — which is great.

    However, before we break out the top-shelf pork rinds and don our party hats, let me introduce another metric — one that I came up with several years ago called the odds-based impact value, or OBIV.

    The OBIV is based, not on field size, but on the average odds of the horses meeting the criteria of the study. The advantage of such an approach is that it more accurately assesses the factor being tested (provided the factor is not odds) by using an established and highly predictive methodology instead of random chance to determine the expected win rate.


    Note: The reason the “normal” range is 0.80-0.85 is to account for the various straight takeout rates and breakage points.

    So, harkening back to our study above, we find that post-time favorites produce an OBIV of 0.81 — which helps to explain why, despite a high IV, the ROI on such steeds is negative to the tune of about 16 cents on the dollar.

    The OBIV also explains why merely seeking high-IV, i.e. obvious, factors never makes money in the real world — although many handicapping gurus have advocated just that.

    Tim Maas, author of “Overlay Handicapping,” took it one step further: He used a variety of IV values to produce a fair odds line. Now, before I illustrate the folly of this, I want to credit Maas for at least attempting to use disconnected, or independent, variables in his method (this is another area that gets horse players into trouble — evaluating dependent variables as though they are independent, e.g. speed and form).

    Among the factors that Maas obtained IV value for were Quirin speed points and average earnings per start. To keep this demonstration simple, I will provide my own IVs for specific subsets of these factors — mainly, I will look at horses with at least eight Quirin speed points and horses with the highest average earnings per start in the field:

    * At least 8 Quirin speed points

    Number: 5,068
    Winners: 878
    Win Rate: 17.3%
    IV: 1.31
    OBIV: 0.83

    * Highest earnings per start in the field
    * (If the horse had fewer than five starts this year, the last two racing years were used)

    Number: 13,069
    Winners: 3,331
    Win Rate: 25.5%
    IV: 1.91
    OBIV: 0.83

    By combining these two factors in a makeshift system, we would expect an IV of approximately 2.50 (using Maas’ technique of multiplying the individual Ivs):

    * At least 8 Quirin speed points
    * Highest earnings per start in the field
    * (If the horse had fewer than five starts this year, the last two racing years were used)

    Number: 841
    Winners: 248
    Win Rate: 29.5%
    IV: 2.12
    OBIV: 0.87

    On the positive side, the numbers are vastly improved from those for each individual factor — even the OBIV is nominally better. However, they’re still not good enough to show a profit. In fact, the $2 net return of $1.67 (-16.5% ROI) is less than the $2 net return for post-time favorites ($1.68).

    Ouch. Two highly predictive factors and they produce more red ink than simply watching the tote board and playing the post-time favorite.

    And the situation doesn’t get any better when one asks for minimum odds (as Maas did by insisting on a “fair” price) — in fact it gets worse:

    * At least 8 Quirin speed points
    * Highest earnings per start in the field
    * (If the horse had fewer than five starts this year, the last two racing years were used)
    * Odds of 3-1 or greater.

    Number: 372
    Winners: 56
    Win Rate: 15.1%
    IV: 1.15
    OBIV: 0.87

    Of course, what all this tells us is that, in order to make money as opposed to just cashing tickets at the racetrack, one must look for unique factors and/or use known factors in unique ways.
    There is a difference between what is predictable and what is profitable.

  • The Pros & Cons of Exacta Wagering

    POSTED Dec 20, 2013 By Derek Simon
    As most of my podcast listeners and Facebook followers know, I’m not overly enamored with the tendency of today’s horse players to focus solely on exotic wagers — exactas, trifectas, pick-3’s, etc. I’ve argued that, while these types of wagers certainly provide players a better chance at a “big score,” they don’t always offer the value that most bettors think they do.

    Among the stranger reasons for playing exotics that I ever heard, though, came in an e-mail I received several years ago. Here’s what the e-mailer wrote in regard to win betting:

    “It doesn't work — period,” he noted. “I tried every way, every method. Betting to win will not work … a losing streak will wipe anyone out … the returns are not high enough.

    “Exotics [are] the only way to profit,” he went on, pointing out that his “new goal” was to minimize his bets and maximize his profits.

    Sure, buy low, sell high. No problem.

    Still, does it really make sense to eschew betting on one horse or one race to bet on multiple horses and/or multiple races, especially when one is concerned about losing streaks? 

    Obviously, the short answer is no, although, like most “truths” in the Sport of Kings, there are exceptions. To illustrate both the pros and cons of one particular type of exotic wagering — the exacta (or “exactor” for my Canadian friends) — I looked at an average race at an average American racetrack — the nightcap at Hawthorne on Friday, Dec. 20.


    (Click on image to enlarge)
    Let’s start with the basics — the takeout rates, which dictate the amounts subtracted from the various pools to fund purses, pay Uncle Sam and otherwise keep the track in business:

    HAWTHORNE
    Win, place, and show: 17%
    Exacta and Daily Double: 20.5%
    Trifecta, Pick-3, Pick-4, and Superfecta wagering: 25%

    As even the studio audience of the “Jerry Springer Show” can see — after much arguing and swearing, of course — the numbers don’t look great for those betting exactas and daily doubles, and they look even worse for those wagering on tri’s, super’s, pick-3’s and pick-4’s.

    Nonetheless, successful speculation is all about finding value. In horseracing, this means insisting on odds greater than one’s actual chance of winning. Luckily, given that horses generally win in accordance with their final odds, we can use the win pool totals to approximate fair exacta payoffs with a reasonable degree of accuracy:

    (W)IN HORSE
    WIN POOL $ ÷ TOTAL WIN POOL $

    (P)LACE HORSE
    WIN POOL $ ÷ (TOTAL WIN POOL $ – WINNER’S WIN POOL $)

    $1 EXACTA PAYOFF
    1 ÷ (W × P ÷ 0.83) – 1

    With this in mind, let’s take a gander at Friday’s ninth race from Hawthorne (HAW). Listed below are the win pool totals:


    (Click on image to enlarge)
    Now, let’s assume that we caught a tiger by the toe and came up with 12-Miles and Miles as the most likely winner and 10-Ideal Alluvial as the probable second-place finisher. What is the fair exacta payoff for that combination, based on the final odds?

    Fair Exacta Payoff: 1 ÷ [4,265 ÷ 61,443 × 21,436 ÷ (61,443 – 4,265) ÷ 0.83] – 1 = $31

    It’s approximately $31 (see above), which means that the actual $39.90 return was a true overlay, even with the higher exacta pool takeout.

    Well, hooray, we’ve just proven that exacta bets can offer (significantly) better value than straight win bets!  

    Hold on Sloopy, not so fast. Remember that in this particular scenario we assumed a single bet on a single combination. The minute one starts “spreading,” i.e. wagering on more than one combination, the return on investment (ROI) plummets. For example, let’s say that instead of betting a $1 exacta on the 12-10 combo, we had spread our wagers a bit and plunked down a sawbuck on each combination offering a better-than-fair price.

    Below are the fair $1 exacta payoffs (based on the final win odds), with the actual will-pays listed in parenthesis. I’ve highlighted the overlays in green and the underlays in red:

    12 with…

    1 – Scr.
    2 – $881 ($461)
    3 – $135 ($113)
    4 – $159 ($109)
    5 – Scr.
    6 – Scr.
    7 – $621 ($282)
    8 – $62 ($69)
    9 – Scr.
    10 – $31 ($39)
    11 – $104 ($70)
    13 – $93 ($68)

    What leaps off the page — at least to me — is all the red ink. Six of the eight possible exacta combinations are underlays, which casts doubt on the notion that the exacta is a haven for value. What’s more, if we play the two overlays — 12-8 and 12-10 — the expected payoff is effectively cut in half. And, no, this does not change if the dollar amounts are raised (provided the distribution of money bet remains unchanged).

    As you might imagine, spreading is even more pronounced in multi-race sequences. According to an old Facebook poll I conducted, horseplayers (at least the ones that took part in my survey) generally use about 12 unique contenders in a typical Pick-3 bet.

    Ironically, the one thing that exotic betting has going for it is a lower hit rate. Let me explain: Although most gamblers don’t think about it, sports betting in almost all its forms is the ultimate exercise in socialism, whereby the haves pay for the have-nots. This is because the “tax,” i.e. the takeout (or vigorish), is paid solely by the winners.

    A horseplayer that loses a $10 bet does not fork out an additional 15-20 percent to cover the takeout; instead, the designated percentage, including breakage (in horseracing), is deducted from the winning payouts. Hence, less winning equals less takeout paid. I realize this is a pyrrhic victory if there ever was one, but it does illustrate why grinding it out can be so difficult for the average player to do.

    So what does all this prove? Only that it pays — quite literally — to treat every wager with care. Understand that higher returns don’t necessarily imply greater value and that the more money you churn, the more it costs you in the form of takeout and breakage.

    If you want to become a better bettor, keep records, assess your strengths and weaknesses and, for heaven’s sake, make the necessary changes. If you can’t cash an exacta to save your life, quit trying — at least with real money — until your skills improve. If every time you play the Pick-3, two of your top choices win and you collect zip, stop playing the Pick-3! Try betting your primary contenders to win or to place; do something, anything, other than what you’ve already proven doesn’t work for you.

    Above all, pay heed to the words of Thomas Tusser, who said: “A fool and his money are soon parted.” Try to remember that the next time you’re at the racetrack… or when buying a Rolex from a guy in a trench coat. Life is short. According to my new watch, there are 10 hours in every day — spend them wisely.