Vulnerable Morning Line Favorites – List to Share

[BETA]

This post is about finding wagering opportunities based on vulnerable ML favorites. Each day I run a database query to isolate these potential bad bets (underlays) to tab for further handicapping review….

Obviously, this info would be better suited for exchange wagering; however, I like to use it as a tool to “potentially” play against horses in both the horizontal and vertical wagering pools….

For those interested in the statistical performance, here’s some data for consideration….
Last 12 Months ending Jan 2017:
Plays = 3687
Win% = 17.01%
ROI = -34.53%
I. V. = 1.32
Average Off Odds = 3.59

Subset of same horses actually going off as Tote Favorite:
Plays = 1198 (32% of total sample)
Win% = 23.62%
ROI = -34.14%
I.V. = 1.84
Average Off Odds = 1.78

Last 3 Months ending Apr 2017:
Plays = 695
Win% = 17.99%
ROI = -32.91%
I. V. = 1.40
Average Off Odds = 3.50

Subset of same horses actually going off as Tote Favorite:
Plays = 243 (35% of total sample)
Win% = 25.10%
ROI = -33.37%
I.V. = 1.92
Average Off Odds = 1.81

As a reminder, this info is intended as a starting point only as each race needs to be properly vetted to warrant further action…. For those interested, this list can be found daily at the following website:
https://sites.google.com/site/horseracinganalytics/home

BOL!

[Winger]

Originally Posted by BETA

This post is about finding wagering opportunities based on vulnerable ML favorites. Each day I run a database query to isolate these potential bad bets (underlays) to tab for further handicapping review….

Obviously, this info would be better suited for exchange wagering; however, I like to use it as a tool to “potentially” play against horses in both the horizontal and vertical wagering pools….

For those interested in the statistical performance, here’s some data for consideration….
Last 12 Months ending Jan 2017:
Plays = 3687
Win% = 17.01%
ROI = -34.53%
I. V. = 1.32
Average Off Odds = 3.59

Subset of same horses actually going off as Tote Favorite:
Plays = 1198 (32% of total sample)
Win% = 23.62%
ROI = -34.14%
I.V. = 1.84
Average Off Odds = 1.78

Last 3 Months ending Apr 2017:
Plays = 695
Win% = 17.99%
ROI = -32.91%
I. V. = 1.40
Average Off Odds = 3.50

Subset of same horses actually going off as Tote Favorite:
Plays = 243 (35% of total sample)
Win% = 25.10%
ROI = -33.37%
I.V. = 1.92
Average Off Odds = 1.81

As a reminder, this info is intended as a starting point only as each race needs to be properly vetted to warrant further action…. For those interested, this list can be found daily at the following website:
https://sites.google.com/site/horseracinganalytics/home

BOL!

Are these numbers based on back-testing, or did you come up with the model before January 2016?

[cnollfan]

Thanks, Beta. I love this.

[VigorsTheGrey]

Hello...Nice of you to share your work here with us.....Do you plan on posting race card data for at least a few weeks here...?

That would be great...! What do the numbers under your models (far right) represent...? What does "bump" mean...? And "HOT"...?

Thank you...Vigors.

[BETA]

I’ve attached the list for of Vulnerable Morning Line Favorites for May 25th…. As general clarification, this list proves useful as my personal approach involves multiple tracks…. If you’re only playing one or two tracks, this info will not be especially useful as your normal handicapping routines will easily identify these poor ML Favs….

Winger, in Jan 2017 I altered my contender selection methodology…. The database detail I shared above is based on back testing this new approach…. The data shown for the last three months represents “live” results.

Cnollfan, thanks!

Vigors, the numbers shown for each model represent the “rank” (1 = best); the “bump” is a value based algorithm; and “hot” = hot trainer based on recent trends…. Please understand that this worksheet and corresponding contender grade is intended as an organizational starting point only (subject to a more in-depth handicapping appraisal based on the unique dynamics of each individual race).

BOL!

[VigorsTheGrey]

I love this..! Thanks...I read more on your site about the process and the models...very organized and clear...will put it into use soon...thanks again...Vigors.

[fight]

I cant find hot or bump where is it ty

[Winger]

Originally Posted by BETA

I’ve attached the list for of Vulnerable Morning Line Favorites for May 25th…. As general clarification, this list proves useful as my personal approach involves multiple tracks…. If you’re only playing one or two tracks, this info will not be especially useful as your normal handicapping routines will easily identify these poor ML Favs….

Winger, in Jan 2017 I altered my contender selection methodology…. The database detail I shared above is based on back testing this new approach…. The data shown for the last three months represents “live” results.

Cnollfan, thanks!

Vigors, the numbers shown for each model represent the “rank” (1 = best); the “bump” is a value based algorithm; and “hot” = hot trainer based on recent trends…. Please understand that this worksheet and corresponding contender grade is intended as an organizational starting point only (subject to a more in-depth handicapping appraisal based on the unique dynamics of each individual race).

BOL!

That's pretty promising that your 3 month trend is staying in line with your back-testing. I can see a lot of value in what you are doing.

[Dave Schwartz]

Those are excellent numbers!

IMHO, the real key to winning is in picking good low-odds non-contenders.

[biggestal99]

We shall see how it does on the x. Played the last 3 races on the vf list,today
20 bucks to lose at the sp.

I'll do it when ever I play the x.

Allan

[BETA]

See attachment.

Also, a couple of quick notes…. For “off” tracks and “off” the turf races it’s best to disregard both the vulnerable ML Favorite List as well as the Contender Grades shown on the Past Performance worksheet (located on website).

It’s very important to also not fall in love with the “A+” Contender Grades while skipping your normal handicapping routines…. My own approach is centered on a “regression-to-the-mean” general philosophy and in turn, I am quick to manually downgrade (or upgrade) contenders as necessary….

BOL!

[BETA]

Biggestal99’s post got me thinking…. I’m not an Exchange player and thus not totally familiar with the format; however, I’ve reworked the data based on what I assume is a typical scenario…. This corrected data is based on offering the Vulnerable Morning Line Fav at Morning Line Odds (sell price)…. In turn, assuming all orders are filled when the tote price <= ML Odds…. The following new data reflects all winners paid per ML Odds instead of Tote (off) Odds:

Last 12 Months ending Jan 2017:
Plays = 1416
Win% = 21.75%
ROI = -18.76
I.V. = 1.68
Average Off Odds = 1.94

Last 3 Months ending Apr 2017:
Plays = 278
Win% = 23.02%
ROI = -18.88
I.V. = 1.80
Average Off Odds = 1.94

Very sorry for not properly presenting this scenario/data in my initial post!

[BETA]

Just wanted to let you know your product “Organize Your Handicapping” was the inspiration behind my recently revised contender selection methodology…. In fact, I’m a fan of most of your work (products); your on-going innovative, original “thinking”; and your willingness to share new approaches/processes at modest pricing!

I would encourage anyone who isn’t familiar with Dave to check out his website and his product “offerings”!

[VigorsTheGrey]

Hi BETA, was wondering if you were going to post your daily files for this coming Sat and Monday...?

[biggestal99]

Originally Posted by BETA

Biggestal99’s post got me thinking…. I’m not an Exchange player and thus not totally familiar with the format; however, I’ve reworked the data based on what I assume is a typical scenario…. This corrected data is based on offering the Vulnerable Morning Line Fav at Morning Line Odds (sell price)…. In turn, assuming all orders are filled when the tote price <= ML Odds…. The following new data reflects all winners paid per ML Odds instead of Tote (off) Odds:

Last 12 Months ending Jan 2017:
Plays = 1416
Win% = 21.75%
ROI = -18.76
I.V. = 1.68
Average Off Odds = 1.94

Last 3 Months ending Apr 2017:
Plays = 278
Win% = 23.02%
ROI = -18.88
I.V. = 1.80
Average Off Odds = 1.94

Very sorry for not properly presenting this scenario/data in my initial post!

Hmm interesting the roi goes up when using that method.

The 7th just went off at woodbine. Savana city the play against is sitting at 7-2 he then dips with 2 minutes to post to 5-2.

I literally was drooling at that price.

I could not hit the keyboard fast enough (in x betting you snooze you lose) to place the bet.

Horse runs rallies for second as chalkie wins.

Keep em coming, when I have enough of a sample I will post the results.


Allan