Those subsets did not offer large enough samples but the results were seductive enough to warrant another research. Substantial profits with small samples are like erotic moments. They may lead to something good, or they may fizzle out.

Rules

(1) Horse must have been out of the money in its debut race.

(2) Must be coming back either

(a)  following a layoff, or

(b)  shipping from a different racing circuit

Rationale

These rules do not come from a vacuum. I’ve been researching this factor for quite some time and was rather encouraged by observations from James Quinn. I was also encouraged after having questioned a number of trainers on the subject. Yes, some trainers crank their horse up for a debut win, but many others confided that the first race for less than super-talented horses was for schooling and that they got serious as of the second race.

Most important, my previous research shows that horses finishing out of the money and at least four lengths behind in their debut race increase their Beyer fig by an average of 9.9 points in their second career race. You cannot argue with the facts: horses, human beings and all other species usually improve the second time they do something. Otherwise a first-time pilot would be allowed to fly a 747 packed full of passengers. 

Shipping to a different circuit incorporates a positive trainer intention. Within many types of research, the subset of shippers emerges with a return on investment that improves upon the original set. California racing is an exception, for the distance of a ship is prohibitive, with the exception of the Route 5 corridor between Northern and Southern California. The results of this research for California tracks constituted a negative subset, but I have purposely included those Cal races in the overall sample, so as to avoid subconscious fudging.

The Tally

There were 621 races with 89 winners for a 14 ½ percent hit rate (this and all numbers are rounded off).

Return:   1,326

Invest:    1,242

Profit:         84   (nearly 7 percent)

Critical Analysis

Methods that are derived from a high average mutuel and regular longshot winners are susceptible to breakdowns in longer samples, so 621 races cannot be considered a large sample.

There is some suspicion that the longshot win record surpassed the real expectation. Why?

Because, with 8-1 and above as an arbitrary definition of “longshot”,  normally there is a ratio between longshot winners and longshot place horses of 10:17. This is based on numerous research expeditions. It’s the approximate inverse of the proportion between winning favorites and faves finishing second.

In this sample there were 20 such longshot winners while there were 27 longshot place finishers. There should have been 34. It is possible that in a larger sample, some of the longshots that won would be finishing place.

But another possibility exists: that with second-time starters coming from poor first races, it’s all or nothing and the normal ratio between win and place longshots cannot be expected.

The good news is that this follow-up research partially validates the findings of our previous sample.

Where it begins to look good: How to handicap second-time starters

The good thing about artisan research is that the researcher can revisit the races of the sample, not with simplistic correlations as with a dbase, but in an analytical way.

Through this analysis, I’ve found some promising news. Recall that many mechanical methods cannot be tampered with. If you inject sensible handicapping to a contrarian method, you lose the contrarian advantage and thereby shave off your best payoffs.

In a contrarian method, the reason that horses pay so much is because their wins cannot be explained within any classical handicapping criteria.

In order to do an item analysis of the second-timer factor, I numbered each of the races as they were tallied. In that way, I could see the number and then immediately refer back to the racing form past performances that were used in the research, a process that purely technological research makes more difficult.

Let’s look at a sampling of 10 longshot winners. Patterns will emerge. (Lay-1 means first race after layoff. “WHY” introduces handicapping reasons that support the original mechanical choice. First L is first-time lasix and first-b is first-time blinkers.)

Wildcat Shoes                                               To the bottom

Paid 23.60, 29Oct03, CD. Beyers: Went from 22 debut race to a 92 second time out. Shipped from AP, Lay-1 (which means coming back after a vacation of at least 45 days).

WHY. (1) Though finish was eighth by 15 lengths, had early speed in debut race, leading from the start through and beyond the four-furlong point of the 6f sprint. (2) Trainer W. Fires had profitable trainer performance stats in dirt category and his best win percentage was for Lay-1.

Secondary factor. First L. 

Zach’s Contender

22.20, 27Feb03, GP. Beyers: went from 41 to 66. Ship from WO, Lay-1.

WHY. The 2-year-old to 3-year-old layoff pattern in previous C&X research.

Secondary. First b.

Anita Xanax

51.80, 18Oct03, LaD. Beyers: -0 to 41. Lay-1.

WHY. A combination of various secondary factors.

Secondary. (1) Went from sloppy track in debut to fast track in second career race and was not bred for the slop. (2) Profitable trainer on dirt, but small sample. (3) In claimer for the first time, but shipping from small track to big track may nullify this factor. (4) First b.

The Call Stands

18.00, 27Feb04, OP. Beyers: 20 to 73. Lay-1.

WHY. (1)  Switch from mediocre trainer to 19% guy. (2) Hidden move in debut, proving he could run, going from tenth by 17 to fifth by 11 in the stretch.

Secondary. First L.

Mr. Willie Joe

19.60, 15Jun03, CrC. Beyers: 24 to 55. Lay-1.

WHY. (1) Dropped from Maiden Special Weight to maiden claimer.

Secondary. Trouble: bumped at start of debut race and steadied on the turn. First L.

Time Time

60.60, 29Nov03, Pen. Beyers: 21 to 37. Ship from AQ.

WHY. The ship from the Big A to Penn National is equivalent to a maiden dropping in class.

Secondary. None.

Krupa

92.90, 21Jan04, GP. Beyers: -0 to 67. Ship from Mth, Lay-1.

WHY. (1) The 2-year-old to 3-year-old layoff pattern. (2) Maiden dropper, though only one level within maiden claiming ranks.

Secondary. First L.

Clear and Cold

27.80, 11Sep03, CrC. Beyers: 31 to 60. Lay-1.

WHY. (1) Collazo, Henry, profitable trainer on dirt with plus 400-race sample. (2) Had speed in debut and was third while wide on the turn before fading.

Mr. Lion

47.40, 20Dec03, CrC. Beyers: 31 to 66. Lay-1.

WHY. There were no obvious signs here. This horse had an even debut race after getting off slowly.

Secondary. None.

Cattoy

21.20, 18Dec03, GG. Beyers: 65 to 71. Ship from SA, Lay-1.

WHY. (1) Was well-bet as debut horse at 7/2, and had even race while lugging out. (2) The SA to GG ship itself is equivalent to a maiden class drop, and the horse had an objective maiden class drop from 25,000 to 14,000.

Secondary. None.

Using the second-timer factor

Going through the whole research horse by horse, all 621 horses (I spent 2 weeks on this research alone), I can assure you that had a handicapper used the above handicapping factors as criteria (2-year-old-to 3-year-old pattern, maiden dropper, early speed in debut, well-bet in debut, profitable trainer specialty, hidden move in debut) in combination with secondary factors ... the return on investment would have skyrocketed. Many of the horses in this research would have been easy to eliminate. Of the above winners, only one had no signs whatsoever, from a handicapping standpoint.

If, as a filter we were to require at least one of the above-annotated primary factors, and in the absence of two of the above factors, at least one secondary factor, then we’d have a legitimate filter that would cut down on the number of bets, without cutting down significantly on the number of payoffs. The return on investment would rise.
But alas, I cannot publish a return on investment, since injecting partially judgmental  handicapping factors would add a subjective element to the research.

Most of the winning second-time starters had ended up finishing their debut race an embarrassing number of lengths behind, and thus, for their second race, there was a boost in the average odds.

There was no humanly possible way to research the dynamics of each of the 621 fields of horses. But there are certain dynamics that stand the test of time. A second-time starter with no supporting handicapping factors that faces a field that includes class droppers is an automatic elimination. The maiden class drop supersedes the second-time factor in order of preference.

But if the class dropper is 8/5 and the second-timer is 12-1, then the handicapper has reason to bet his second choice, that is, after having handicapped the race and made the usual judgments about the field.

Given the relatively low percentage of winners and only moderate size sample, this research cannot qualify as an automatic bet. But it can serve as a very useful handicapping tool. A recent winner at Saratoga by these criteria (including the layoff) was Stock Tip in Race 5 on August 1. He paid $110 to win.  To the top
 

SOCIAL DARWINISM AT THE TRACK: THE SHORT FORM METHOD
with thanks to the IRS for the concept of "long form" and "short form"

Have you noticed? Several times, we've received research from C&X readers, and the added factor to whatever the original rules were is: trainer percentage must be above X%.

No matter what the researched factors, the inclusion of low-percentage trainers ruins the bottom line.     

It is remarkable that some of these no-win stables actually attract owners. A low training fee can hardly make up for a low return from racing. A friend of mine once began a horse-owning syndicate but he chose a low-win trainer because that trainer was a nice guy. It didn't work out.                     

One might think that these low% guys would make up for it by high average mutuels. But it ain't so. Like the gullible owners that find these trainers, there are also gullible players who bet them.
Most of these no-win trainers are nice guys. I don't even want to mention their names here. When living on the backstretch, it hurt me to walk past the barn of a slumping stable full of nice guys. 
You readers have trainer win percentages in the pps, so no need to make hay over the names of losing trainers.

Looking at Southern Cal, it looks as if these no-win trainers are being eaten alive by guys like Jeff Mullins, Robert Frankel, Mike Mitchell, Bill Spawr, Brian Lynch, Jenine Sahadi (not a guy). Nothing we can do about this except to go with the flow. You look at the pps of horses of these trainers, and you finally come across a win, only to discover that it occurred beneath the line "previously trained by...".

With very few exceptions, these low-win trainers have a very low return on investment as well. The average mutuel of their wins should be higher than normal because the betting public should be underbetting these trainers. But the public continues to handicap horses of these trainers by speed and pace figures and other factors that are rendered unrealistic by the low hit-rate and r.o.i. of the stable.

In the long run and most of the time in the short run as well, the handicapper can abbreviate the pps by simple exing out any horse whose trainer wins 7 percent or less.

Another ex-out is a combination of rider/trainer in which both halves of the combo have 9 percent or less.

Another darwinesque elimination Proven losers at today's class level provide us with another automatic toss. A horse that has lost three unexcused races or more at today's class level or below should not be in the race. No matter what their speed figs or finish positions tell us. The "proven loser" elimination works especially well in the maiden claiming ranks and at allowance nw1. A field comprised entirely of proven losers can lead to substantial payoffs, while occasionally, the proven-loser elimination will leave only a horse or two without the blemish, and those horses are often not be the favorites.

Though a good many of the above trainer, trainer-rider, and proven-loser eliminations are longshots,  lower-odds horses often qualify to be exed out.

In separate longshot research, none of the above eliminations interferes with the r.o.i. of regular longshot betting.  
 

The Short Form   

Who would not love to do his taxes with the short form rather than the long form. In handicapping, we have the long form (all the pps) and the short form (the pps minus the above eliminations). Maybe you partied the night before and didn't have time to do reasonable handicapping. Well, you can use the short form. Handicap only those races in which at least half the field can be eliminated by the above criteria.

Suddenly a 10-horse field becomes a 4-horse field. A 7-horse field could become a 3-horse field. With multi-card simulcasting, you've got five or six or more tracks to deal with, and short-form handicapping allows you to cherry pick only short-form races. (For tris and superfectas, short-form eliminations are not entirely excluded from finishing third or fourth.)

Consider that in a field in which most trainers are of the high-win variety, any of them can defeat any of the others. The supertrainers chalk up their high hit rates thanks to the poorer barns, but against each other they are no longer so super.
Much less real handicapping is required with the Short Form. Eliminating low-win trainers and proven losers at the level allows the handicapper time for intense analysis where it really counts. It's also a way of quickly deciding, when faced with an over-extended menu, of  which races to dig into.  To the top