2022 Tennis Trading Thread
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Good morning. Backing Sakkari @ 3.05
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Sabalenka is a machine. Future women's number 1 for me. Very aggressive, never-say-die attitude, and pretty damn fit too, which is an added bonus!
Unfortunately the market has been onto her potential for a quite a while now, so the juicier prices are less abundant. Bah. 
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@simon said in Tennis Trading Thread 2018:
All ties at Chengdu tomorrow qualify for the lays, and none at Shenzhen. List below:
Fognini (500)
Querry (500)
Sousa (500)
Auger-Alliasime (500)My tactical moan obviously worked yesterday as 3 of the 4 won today! Good end to the week, and back in green too!
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Backing Sabalenka @ 2.78
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All ties at Chengdu tomorrow qualify for the lays, and none at Shenzhen. List below:
Fognini (500)
Querry (500)
Sousa (500)
Auger-Alliasime (500) -
@frode-lia said in Tennis Trading Thread 2018:
@simon @Ryan-Carruthers ... or "Fred Perris", as my wife calles him
I’ve listen to quiet a few of his pods before
Cheers bud, downloaded! -
@simon @Ryan-Carruthers ... or "Fred Perris", as my wife calles him
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@simon @Ryan-Carruthers Great pod on the subject from Tim Ferriss with Howard Marks here: https://tim.blog/podcast/
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@ryan-carruthers never actually read it, but I’m a big fan of road cycling so massively aware of it and it’s theories since Steve Peters was working with uk cycling at the time it was published.
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@caio-schumacher
A little background. I have the last couple of years used Dan Weston projected hold models to find value in players with good serve. My results got much better going from straight stats to the projected hold model. My tennis trading is very systematical in the sence I only use five different strategies. 3 for ATP and 2 for WTA. So I use the ratings different from strategy to strategy. But as a example the strat I use the most, and with my second highest ROI for the year.- I find WTA players with 3% pluss in their procjected hold. Ex: (dont remember exact numbers) Stephens had 63% PJH, and Azarenka had 59% PJH. Stephens was between 2.4-2.6 in pre game odds. In other words, hugh value on Ostapenko.
- I checked for injuries and so on.
- My strat is then to back Stephens every time she is one break under, or and she loses the first set.
- I would first let the players serve once each.
- On the third serve Stephens was down 3-0. I would then back Stephens for 1% (using the BTC staking calculator) on Azarenkas serve.
- Stephens broke 3-1 and I took my profit.
- Stephens lost 1 set 6-3 and lost here first serve. I went in again with 0.5% on odds over 8, and she broke once again.
- Stephens won the match 2-1.
Rules for the strat is as follow:
Let both players serve once each.
Go in on first break, but not after 4-4.
Take profit after backed player goes up.
Or, take stop loss after backed player goes down.
The last thing is the most important. It is in stoping the loses your profits lies.
I have used the BTC model for Miami, and it have worked very nice. The thing I like with the BTC engine is that its availeble when I do my research. Usually before my kids wake up. Instead of waiting for a email. And it have been very accurate (surpriceingly since Adam still call them experimental?!?) Looking forward to follow them closly this autum. -
@simon Sounds like somebody has read the chimp book?
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@ryan-carruthers @Frode-Lia 100% agree with you both. My head knows it, my inner chimp doesn't. Definitely one of my weakest points is putting too much pressure on the short term, when good or bad.
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@frode-lia @Simon I agree, variance is a bitch but one you have to get used to
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@simon said in Tennis Trading Thread 2018:
@frode-lia thanks bud, been losing the faith this week but know with systems like this losing runs are absolutely inevitable.
You would have lost a lot of money if you stoped investing in stocks in 2008 because of a rough year
As @Ryan-Carruthers often say, it is a marathon. -
@frode-lia thanks bud, been losing the faith this week but know with systems like this losing runs are absolutely inevitable.
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So it's been a poor week so far trading at Chengdu and Shenzen which has resulted in me doing some more number and data crunching. I have gone through all the games in the north American swing I wasn't able to trade, and attributed and average loss or win to these based on the point by point data on flashscore and here are the numbers. Sample size still small but some patterns look to be emerging.
ATP 250 Clay 10% ROI
ATP 250 Grass 20% ROI
ATP 250 Outdoor Hard 1% ROI
ATP 250 Indoor Hard 8% ROIATP 500 Clay 9% ROI
ATP 500 Grass 2% ROI
ATP 500 Outdoor Hard -9% ROIATP 1000 Outdoor Hard 11% ROI
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