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Statsational WTA Model US Open August 29

John Alesia
John Alesia

We will add new sports and models as we continue to build the app and make it more robust. While our developers work on that, we want to give you as much information as possible via content and articles.

I will post my models for upcoming Tennis matchups as often as possible. Be on the lookout during the day because there may be multiple tournaments worldwide.

Reading the model is very simple. I have the line posted at one of the sportsbooks. I will post which book the lines were taken from each day. I will then show what my model thinks the line should be. The last column is the most important. That is the edge I see based on the difference in my line and the bettable line.

The natural reaction would be to be all lines with an edge. I tend to be slightly conservative and look for a 5% edge or greater to make a wager. With tennis (and soccer) I tend to be a bit leery of very large edges. 15-20% or more can mean there is something the model is not picking up, perhaps an injury or some pretty sharp bettors pushing the line to the side we are showing as a high negative edge. This could be a good fade opportunity. That is, betting against the player we show to have an edge.

You should all play around with these and track them yourselves. See if you are seeing those with a great edge losing often.

On matches where we see an edge, but the line is very high, I sometimes like to bet those on the spread line. Preferably sets, but you may also look at the game spread line. The reason for this is a high unlikelihood that the big dog wins the match, but there may be value in betting on the spread. You can split the bet up and do both as well.

Today's lines are taken from Draftkings.

August 29

Players

Actual Line

Sharp App Line

EDGE

Arantxa Rus

425

501

-2%

Madison Keys

-600

-501

-2%


Players

Actual Line

Sharp App Line

EDGE

Na Lae Han

1100

2591

-5%

Marketa Vondrousova

-2500

-2591

0%


Players

Actual Line

Sharp App Line

EDGE

Elsa Jacquemot

240

883

-19%

Lesia Tsurenko

-310

-883

14%


Players

Actual Line

Sharp App Line

EDGE

Martina Trevisan

115

101

3%

Yulia Putintseva

-140

-101

-8%

Players

Actual Line

Sharp App Line

EDGE

Tatjana Maria

135

158

-4%

Petra Martic

-165

-158

-1%

Players

Actual Line

Sharp App Line

EDGE

Camila Giorgi

380

324

3%

Jessica Pegula

-525

-324

-8%

Players

Actual Line

Sharp App Line

EDGE

Elina Svitolina

-650

-332

-10%

Anna Lena Friedsam

450

332

5%

Players

Actual Line

Sharp App Line

EDGE

Daria Kasatkina

-750

-286

-14%

Alycia Parks

500

286

9%

Players

Actual Line

Sharp App Line

EDGE

Karolina Pliskova

-215

-367

10%

Elena Gabriela Ruse

175

367

-15%

Players

Actual Line

Sharp App Line

EDGE

Peyton Stearns

-205

-104

-16%

Viktoriya Tomova

170

104

12%

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