Statsational WTA Model US Open August 29
![John Alesia](https://cdn.sharp.app/user/8925479b-c103-4c68-9e7c-6a6d4c880045.jpg)
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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