Statsational ATP Model Australian Open January 14, 2024
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 significant edge losing often. I sometimes like to bet those on the spread line on matches where we see an edge, but the line is very high. Preferably sets, but you may also look at the game spread line. This is because there is a high likelihood that the big dog will win 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.
January 14
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Matteo Arnaldi | -500 | -976 | 7% |
Adam Walton | 360 | 976 | -12% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Alexander Shevchenko | -300 | -492 | 8% |
Jaume Munar | 240 | 492 | -13% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Jannik Sinner | -1400 | -2248 | 2% |
Botic Van De Zandschulp | 750 | 2248 | -8% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Pavel Kotov | -130 | -164 | 6% |
Arthur Rinderknech | 110 | 164 | -10% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Fabian Marozsan | -130 | -122 | -2% |
Marin Cilic | 110 | 122 | -3% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Dane Sweeny | 215 | 2267 | -28% |
Francisco Cerundolo | -275 | -2267 | 22% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Thiago Seyboth Wild | 1600 | 4758 | -4% |
Andrey Rublev | -8000 | -4758 | -1% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
J J Wolf | -170 | -118 | -9% |
Sebastian Baez | 140 | 118 | 4% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Tomas Machac | -350 | -1223 | 15% |
Shintaro Mochizuki | 270 | 1223 | -19% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Christopher Oconnell | -245 | 116 | -25% |
Cristian Garin | 195 | -116 | 20% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Jesper De Jong | -250 | -165 | -9% |
Pedro Cachin | 200 | 165 | 4% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Taylor Fritz | -3000 | -6668 | 2% |
Facundo Diaz Acosta | 1200 | 6668 | -6% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Quentin Halys | 200 | 104 | 16% |
Lloyd Harris | -250 | -104 | -20% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Daniel Elahi Galan | 160 | 208 | -6% |
Jason Kubler | -200 | -208 | 1% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Novak Djokovic | -4000 | 4509 | 5% |
Dino Prizmic | 1800 | -4509 | -8% |
Players | Actual Line | Sharp App Line | EDGE |
---|---|---|---|
Frances Tiafoe | -190 | -101 | -15% |
Borna Coric | 155 | 101 | 10% |
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