When Horse Racing meets Chaos Theory

When Horse Racing meets Chaos Theory

We’ve all been there. We’ve carried out a full analysis of a horse race, a Maximser type of approach, and you feel completely confident of what the outcome will be. But low and behold, the result is a complete random. This is when horse racing meets chaos theory.


Scene 1: The Analysis

Let’s say that you’ve considered:

  • The chance of every runner
  • Those proven on the ground/going
  • The horses competent and proven over the distance
  • Fitness and those on a winnable mark
  • Recent speed figures
  • Those suited by the course
  • The characteristics of the racecourse (e.g. this course doesn’t favour front runners)
  • How the race will be run and noted which horses it will suit
  • Which horse will make the running, which will track the leaders, race prominently, race midfield, be held up, or race in rear
  • Prices, which demonstrate value and/or appropriately priced
  • Jockey booking for shortlisted horse is positive – or jockey has won on the horse before
  • Trainer/stable, which is in form and horses are at the top of their game
  • Any other factors that point to one horse winning the race quite comfortably.

And let’s also assume for this example that:

  1. There are no horses taking a distinct drop or step up in class
  2. All horses are relatively exposed
  3. This is not a maiden or 2 year old conditions or nursery race where they’re all lightly raced

As a result of this analysis, let’s now suggest that you have a prediction of the horse that is most likely to win and listed the horses likely to finish second and third.

  1. Winner: Horse A
  2. 2nd: Horse B
  3. 3rd: Horse C


Scene 2: The Race

  1. The race starts just like you expect and you were right with who sets the pace
  2. Everyone travels well for the first half of the race
  3. The race starts to pan out as you expected during the closing stages
  4. The field make their move just outside the final furlong


Scene 3: The Sting

Horse D, a 33-1 shot, makes all and wins by over a length. Let’s consider that:

  1. It’s fully exposed and hasn’t won for about a year
  2. It’s not been placed in its last five starts
  3. Has inferior speed ratings
  4. Has no recent form
  5. The trainer and stable are out of form
  6. The jockey had never ridden the horse before
  7. It had never won over the distance, going and course before.

The questions that will be asked:

  1. Why did that horse win?
  2. How did that horse overcome the course’s characteristic to win from the front?
  3. What was missed in the analysis?
  4. Who rode the horse and what did he/she do differently that previous jockeys didn’t?
  5. Why was the price so high if it really did have a chance of winning?
  6. Where did the improvement come from? Did the horse’s last performances suggest that a drop or step up in trip would bring this about? Did the course bring out the improvement?
  7. Was the going absolutely perfect for this horse?
  8. Were previous runs completely underestimated in the speed figures?
  9. Were there track biases that explain the poor recent performances where it never stood a chance?
  10. Was it wearing first time headgear that brought about a significant change?
  11. Did the rest of the field leave themselves too much to do?
  12. Was the rest of the field overestimated?


Epilogue: Meet Chaos Theory

On Investopedia, Chaos Theory is defined as “a mathematical concept that explains that it is possible to get a random result from a normal equation.”  What we get here is 2 + 2 = 5.

Chaos Theory is considered very complex and controversial, however, our race above shows where horse racing meets chaos theory.

The ‘normal equation’, i.e. the full race analysis, suggests we have a pretty good idea of who is likely to win. But when that horse loses to a competitor that doesn’t meet any criteria of the normal equation, it has us asking all sorts of questions as to why and how.

Unfortunately, that’s horse racing and chaos theory. Like as in the last article on maximizers and satisficers we refer to the late, great Sid James in Carry On At Your Convenience; “I work it out scientifically, can I help it if they don’t run scientifically.”

The conclusion is simply “the race cannot be reasoned”.

This race will be confined to the record books. We can’t win them all, but often we’ll find that our normal equation works more often than when a touch of chaos theory hits us in the face with a completely random answer.

Unpredictable is another word that could explain this occurrence and perhaps luck, but more often than not a bit of satisficer mentality will lead to creating a pool of contenders who are likely to be involved at the sharp end.


Categories General