California Racing Has Always Been an Island

By now everyone's read the Drape story about Triple Crown winner Justify receiving an alleged (no one has disputed it yet, so maybe they'll drop the alleged part soon) positive test for the drug scopolamine.

This drug is not new to horse racing, as over the years positives have resulted in trace amounts (through contamination) where trainers are held accountable. But, as the data has come in, it has been studied, and jurisdictions around the world have set limits on the amount of the drug that can, according to the science, be attributed to the environment.

In Louisiana, it's 75 ng/ml, Europe 30 ng/ml.

The International Federation of Horse Racing Authorities has the contamination limit at 60 ng/ml.

In Australia, it's 25 ng/ml. 

Justify's test, according to Drape, showed 300 ng/ml.

California seems - at least some protagonists do - to think 300 mg/ml can still be a contaminant.

This leads to a broader discussion about uniform rules on drugs and suspensions. Let's face it, that should've been done an epoch ago; uniform rules are directly proportional to fewer regulatory clown shows. But, for whatever reason, California racing does not seem to take heed. It does what it does.

I've always felt it's why the general public doesn't much understand horse racing.

To your average Joe or Jane, this reads fairly simple. It's a case of a 0.08 blood alcohol limit for drunk driving because everyone agrees that's proper. But in California, a guy who blew a 0.12 was let drive home because someone arbitrarily decided he's a big dude and he said he drank some mouthwash. It just doesn't compute.

Have a nice Thursday everyone.





Can We Beat the Computer Horse Betting Models? At Times, Sure We Can.

On a previous post I mentioned a book I read a couple of weeks ago called "Digital Marketing in an AI World" and promised a couple of thoughts on AI or big data models for horse racing.

If you're interested I'll share a few of those thoughts below.

First, I'm a believer in modeling for sports betting and racing, because with proper discipline, some smarts, and a malleable model we can make hay when the sun shines. Numbers remove bias, and they take away what we thought we knew, but really never knew out of a wager. A good model, even in horse racing's high rake environment, can work, and work pretty well.

When we analyze data in horse racing a few characteristics generally occur.

i) We learn pretty quickly how difficult the game is to beat. The angles we thought were great, aren't great at all (unless you like losing 15 or 20 cents of every dollar you bet). When you run a model on a subset of (statistically significant) data, the chances of it showing +EV are slim. When you parse or layer too much, you're chasing your tail with bad information.

ii) The horses a model may signal as plays are pure overlays, and some of these horses - on paper - will look gawd awful. We'll see an 0 for 11 horse, a bad jockey switch, terrible form - what we may call 'qualitative anti-angles' - that make us not want to wager on the animal (which is precisely why these wagers can approach 1.00 ROI).

iii) the price of the horse (or the bet type) is everything.

The teams we read so much about are doing much of the above religiously. Can we beat them? In my view, Fred's book tells us one way how.

Self driving cars are in the news, sometimes for terrible reasons. When an accident occurs, it sheds light on the problems with AI, and in-turn, some of racing's computer modeling.

This AI works on a three-step process - perceive, plan and execute. In Tempe, Arizona last year, this was on display, and not in a good way.

A woman was walking her bicycle across a four lane highway after dark and was struck and killed by a self driving car. The car's LIDAR perceived a human with a bicycle, but in the planning stage it computed it could not be a human with a bicycle because it's a 4 lane highway at night. In the execution stage the AI asked "what should we do?" and the answer was, "keep going."

Fred writes: "Machine learning systems can make mistakes, and it's possible to outflank the competition by capitalizing on them."

In racing, in my view, we see this often.

Several years ago I remember playing the Woodbine polytrack for the first day of the meet. Like other computer modelers I knew the poly is fast, and horses who make the lead are great bets. At times, even with bad trainers or riders, you could make a score. But, at least one modeler was slow to the draw.

At Woodbine, the fifth race had a horse who my model said would make the lead, and horses who made the lead were 4 for 4* already. It was a green light. But one bot, run on a model, didn't agree. Whether it was working with late pace numbers, didn't have a built-in bias, or what I do not know, but it just kept fading the animal. It was 6-1 on the board 14-1 on the exchange, then 16-1, then 17-1. I kept putting up cash, wondering what in the hell price this model was working on. It took the offers up to 25-1. The horse won easily and paid $18.

The above is not as isolated occurrence.

What other mistakes do we see?

In my view - lame horses. If you're an old school horse watcher, you can take these models to school, using the model itself - perceive, plan, execute. Did the horse look like this last time? No, then execute, because that model betting $1,400 on its nose likely has no clue.

I have seen horses head to the gate lame who were gate scratched that the models were on. They're losing money, so we have to be the one to beat them.

Overall, I am certainly no expert, but I love modeling and models, for horse racing or otherwise. They work. But, it doesn't mean they can't be exploited. Those are a couple of areas I think they can be had.

Have a really nice Friday everyone.

* My top pace figure (with a slight speed track modification) went 10 for 10 that day. It was a rare Let It Ride type day that keeps a lot of us coming back. 

The Tantalizing Touts

@bvalvsracing tweeted out a nice article last week about the touts. It talks a great deal about entertainment content versus hard-edged +EV predictions. Namely, it pays to tout for entertainment purposes, because it's sexier. That's why we see a lot of content presented like this -

“The wrong team is favored and I love this team as a home underdog. They are coming off extra rest and the defense has been impenetrable so far this season. I will be taking them on the money line and expect them to win the game.”

You and I know the obvious - that information is already considered in the line, so it's kind of useless. But if that team performs well, then this tout is off to the races.

Meanwhile, for the +EV dude or gal, they're off in the tout wilderness with their analysis.

“Due to many factors and variables within the model, we have the home team priced at -9.75 with a current edge over the market price of x%, being our biggest edge even after regression back to the market price. Also, I see variations in price/spread from -6.5 -120 to -7 +105 and a few other prices across the screen so it will also depend on how much you value 7 in today’s NFL and what outs you have among other considerations.”

Zzzzzzz.

Horse racing represents this phenomenon a lot.

"Chad Brown wins with shippers from overseas in routes."

Thanks, that's why the horse is 6-5.

However, unlike in sports betting - where you do see the second kind of content - in horse racing there is very little. The HANA Horseplayer Magazine had some, you'll find a little on twitter now and again. But it's pretty much a dearth.

I think there are a couple of reasons for it - i) most profitable players keep their oddslines and angles a secret, and ii) there is almost no market for this analysis in horse racing; math players aren't trying to beat 20% juice in horse racing in some six horse field scattered almost minute by minute on any given day.

Another point that struck me while reading the article. The tantalizing touts, with angles, and all the rest can make hay in sports, because if they are not horrible people will win enough over a season to keep firing. You only have to beat 4.8% (or lower if you line shop) takeout. I think that's why we see so many of them. It's difficult to break even over a season (no offense to them, they are just doing their jobs) playing TVG host pick 4 tickets.

Have a nice Wednesday everyone.

Gambling - Skill Game Success Must Be Achievable

I was reading the Atlantic's Derek Thompson's book Hitmakers this week. Thompson explores a lot when it comes to marketing, business and human psychology and I found it kind of interesting.

One section of the book is devoted to why some games catch on and some don't, where he introduced a concept called "MAYA".

To illustrate his point, he talked about Tetris, the best selling video game of all time, created in the 1980's by a Russian programmer, and Minecraft, the second biggest seller ever. Both games, the author contends, are pure puzzles not unlike lego or other childhood games and they have a few common themes.

"The level of play must be simple enough to execute, and the point of these games is neither to make players tear out their hair nor give  away the secret too easily," he writes. "... these [most successful] games are designed with what neurologist Judy Willis called an achievable challenge. People will take up a challenge if they think they can solve it - Most Advanced Yet Achievable : MAYA."

In terms of gambling games, this is pretty obvious isn't it?

Poker is a tough game to learn, but it's not overly daunting. And, with low juice you have a chance to win - MAYA.

Black Jack rose to prominence in the 1960's with the classic book, Beat the Dealer. You can beat blackjack, if you try, and someone is showing you how - MAYA.

Sports Betting has been around forever at about 5% juice. It's a tough game to beat, but it feels achievable to millions of people because the house edge is not usurious. MAYA.

When the misanthropes on twitter talk about grinding out in horse racing, jackpot bets kill the game, there are no low takeout bets to allow people to churn, and all the rest of those mean, nasty things, they aren't being misanthropic. They're just telling you that betting horse racing is not MAYA; succeeding at it is not achievable to the masses like those other games. And if the business would do more to make solving the puzzles (at potential profit) more achievable, the sport would be better off.

Have a great long weekend folks. And best wishes for a safe weekend to our friends in Florida and area.

Data Can Market Itself into Something Really Big

I finished a decent book recently - Digital Marketing in an AI World - about artificial intelligence in marketing, and big data.

Author Fred Vallaeys was one of the earliest google employees and he was involved in a lot of the big data (and systems) google has created over the years to enhance their marketing platform (which still makes up almost all of the company's revenue).

In the book Fred made a couple of interesting points that relates in some way to horse racing.

One of them - software, big teams, big data and wagering - I will cover later when I have some time. The one I'd like to share some thoughts relates to "the data"; a topic not unfamiliar to those in this sport.

Fred noted that back in 2005, google looked into the purchase of Urchin. Urchin was a system that collected data from various sources and allowed a business to see where pretty much every metric they could imagine was coming from. I used the system in my work, and it was a leg up. There was a lot of money being spent on developing these analytic packages at the time, but it truly was nascent.

Google being in the space scared a whole lot of folks:

"Many people were afraid that this was going to kill the analytics industry. Chills went up the spines of businesses and vendors who were installing tracking systems," Fred wrote.

When google announced this package - one they could charge a high price for; this is called Google Analytics today - was going to be free, it was even more concerning. It could be the end of many businesses, in a new space.

The result was the exact opposite:

"Because google made analytics plentiful and cheap, all of a sudden everyone was paying attention, and able to afford analytics. This turned out to be a huge boon for the industry. Businesses began to say "this is something we should do more with."

This freeing up of the data caused massive ripple effects, and it sure didn't kill an industry.

Back at a conference in about 2004 I hung around with these folks from Utah, all smiling and wearing green shirts. They had an awesome tracking and analytics company, but they were quite small. As demand for analytics grew, though, so did they. Four years later the small team were rich - Adobe acquired them for $1.8 billion.

Google freeing up data and making it all very mainstream no doubt helped them - and others; there were dozens of these companies, and many are still in business today - succeed. It created a massive ecosystem where each and every new entity - third party ads, internal ad spend (like Amazon) - and just about everyone else can enhance their sales process and grow their business.

Unlike web analytics which is still growing today, horse racing at the very best is stalled. Perhaps using institutional roadblocks and heavy regulation to keep others out is ROI positive in the long-term for the sport when it comes to data. However, when we look at where the growth is coming from in other industries, it makes one wonder. If Equibase invited participation and intra-sport growth through transactional-type economics, would the sport be better off? Perhaps it would.

Have a nice Tuesday everyone.

Fixed Odds Betting Solutions Seem Simple, Because They Probably Are

You might've heard a lot about fixed odds betting over the last few months.

In horse racing, some quarters believe that fixed odds wagering would be welcomed, primarily due to the failings of the pari-mutuel system - namely, money dumps at 1 minute or closer to post, making the odds board look like barely a suggestion. I'm one of those people, in theory.

The gripes about fixed odds wagering frequently revolve around the immutable truth that, at times (especially if you have a clue what you're doing), your wager size will be limited, or the book will not even accept your bets - the "no sharps allowed" phenomenon.

This is not difficult to understand, of course. If someone is making 1% or 2% returns with lots of volume, your book can get killed in a hurry at $5,000 or $10,000 per bet. In a sport like horse racing, with billions wagered, the inside money, the sharps; it could be pretty hellish for those taking the bets.

What I find curious about this whole system is that the problems are completely obvious, but we've seen a solution that's already been vetted and works - a betting exchange.

If you wanted to bet $20k on a soccer game in the UK, it wasn't overly difficult with an exchange. Ditto if you wanted to get $1,000 down on a horse, or even an NFL game. There was usually someone there to match your price - there's sharp money on both sides after all - and if there wasn't, you'd hang your bid (or offer, if you prefer) at a more attractive price and would probably get matched.

The advantages of this system were pretty clear. There was little risk to the bookie and the consumer could place a bet of virtually any size, seamlessly, at takeout rates which encouraged volume and sticky LTV's. In addition, those who were "stuck" in a position, either personally or owning a book, could lay off action, or balance. It could be used as a clearing house.



Earlier this decade, though, the largest exchange - Betfair - went public, and then was swallowed up, as we often see in the current M&A century we live in. Perhaps the new owners needed more margin per customer and the book itself was better for that, or maybe there was another reason (or fifty); but for whatever reason, the exchanges were not marketed.

Despite this technology and its numerous advantages, it's not being used like it even was a decade ago. It's the cousin you forgot you had.

Meanwhile, markets have long taught us that when there's demand, there's going to be supply. In the Far East, unregulated betting exchanges and similar services have popped up. One exchange alone is rumored to be doing over $50B in matched markets - a good deal of it in horse racing. This excahnge was rumored to be bringing in close to 20% of Hong Kong racing's turnover, although that's probably high. There are several others, some in my view pretty scary, which are linked to money laundering and organized crime. 



As well, new unregulated full service betting companies are doing what we describe above - using the exchange as a clearing house. I won't link the site, but I noticed one betting service scours the web for your price, and if your price is not available, it will automatically place your bid for you on the exchanges. With some regulation it would be pretty much the perfect betting ecosystem. It's exactly how this is all supposed to work.

What if racing - with its near monopoly, regulatory capture and $500M or more in subsidy - created a system like this for the sport a dozen years ago? Perhaps in 2019, Draft Kings and other books, now happily taking sports bets, would be a forgotten cousin to the racing exchange.

Fixed odds betting is fantastic for horse racing. Placing a bet at 5-2 when you like the horse at 5-2 and getting 5-2 is the way things should work. However, it's simply not the way it is, or it appears it's ever going to be. For that we should not blame fixed odds, we should blame the system the power brokers have created.

Have a nice Wednesday everyone.



The Change Train Needs More Than a Conductor

I caught a quick story in the Financial Post today about what companies do when things aren't going well, and they need a paradigm shift. The author focused on how one company - Best Buy - turned things around.

I found two planks kind of interesting. One plank,  is about a reorg -

"Putting a plan into action also requires the right people in the right places. Who gets brought in depends on whether the culture of the organization needs to be completely gutted or if a few tweaks will suffice. For example, in a situation of a complete reorganization, it may be better to change out entire teams under divisional leaders, especially if there is complacency and little buy-in. "

This strikes me, as I read this tweet this morning about Del Mar.
As most know, we've seen a couple things happen at Del Mar the last decade. They (along with others in California) raised juice, making payouts to customers worse; they replaced polytrack surfaces with dirt, which raised favorite win percentage, and resulted in (both in theory and practice) more breakdowns.

Now, let's say, like Best Buy, the culture was changed at the top.

Instead of switching surfaces, this new management said, we want fewer breakdowns, bigger fields, less chalk, and a better betting menu, and we'll reverse all those decisions.

I wish them luck. The existing stakeholders would want nothing of it.

Which brings me to the second plank, according to the author.

"A restructuring gives the company the opportunity to replace those shareholders who are not willing to support the company’s refocus. It is an important process to go through as capital partners need to be aligned with management and the plan about to be implemented."

The people who are giving you money need to buy-in as well. It's a house of cards without them.

In racing I find we often ask for change at the top; that management is bad; that they don't know what they're doing. Leaving aside if that's accurate or not, I'd contend it doesn't matter much. If someone was put in charge that demanded change, I highly suspect he or she would be run out of Dodge in two shakes of a lamb's tail.

Have a nice Tuesday everyone.

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