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Events in WTA Wuhan this week are the inspiration for this article, with the markets panicking in the extreme when a big underdog was causing a top ten player problems…
According to investopedia.com, the definition of ‘Panic Selling’ is ‘Wide-scale selling of an investment, causing a sharp decline in price. In most instances of panic selling, investors just want to get out of the investment, with little regard for the price at which they sell.’
We have seen this in several instances this week, in particular in the Timea Bacsinszky matches, against Maria Sharapova and Caroline Wozniacki.
Timea Bacsinszky’s superb performances in Wuhan caused market panic…
Investopedia also make the point that ‘The main problem with panic selling is that investors are selling in reaction to pure emotion and fear, rather than evaluating fundamentals.’
This is without a doubt the case in the Tennis trading markets, with a high proportion of activity driven on this basis, as opposed to having a solid plan – a trading script – to stick to.
We can relate the panic selling concept to the Tennis markets.
Yesterday, in the Bacsinszky vs Wozniacki match, we saw Wozniacki’s price escalate sharply when Bacsinszky successfully served out the first set at *5-4 up. It is my belief that many traders backed the Dane in-play when a break down in set one, with a view to building a position to trade out from, expecting the higher ranked player to break-back and level the set. This method already had one successful trade, with Bacsinszky breaking to lead *2-1 but Wozniacki getting the set back on level terms at 3-3. Personally I have no problem with these trades at all, and believe them to offer positive long-term expected value based on my break-back stats.
What I have more of a problem with, from an EV basis, is how traders panicked and dumped Wozniacki when she failed to break, and at the points early in the second set that she struggled. Bacsinszky got to 30-30 and deuce in several of Wozniacki’s early service games, and we could see that the market was losing belief in Wozniacki.
But why?
That brings us to the second point from Investopedia – ‘The main problem with panic selling is that investors are selling in reaction to pure emotion and fear, rather than evaluating fundamentals.’
This quote perfectly illustrates the situation. I can see it now. I didn’t have my Twitter timeline on but it’s 1.01 that generally the discussion, and thought process, amongst many people would have been along the lines of the following…
Set 1 – ‘OMG Wozniacki is losing to an unknown, let’s back her’. When she lost the set, these people face a problem that they are likely not to have evaluated in advance. Do they hold or do they dump? Holding involves keeping faith in the more illustrious player to turn the match around, whilst dumping involves taking a hedged loss on the market and exiting their position. The problem many traders face is they probably don’t actually know which approach is correct in any situation!
Traders faced a tough decision when Caroline Wozniacki lost the first set…
How many people in the market had an advance plan – a trading script – worked out so that they knew how to approach every match situation before it occurred? If you offered me even money on less than 50% of the market, I’d take that bet.
How many people in the market have profiled this situation in these type of matches in advance so that they know how often various scenarios develop? Now, if you offered me even money on less than 10% of the market, I’d snap your hand off. It’s probably less than 1%.
There in a nutshell is one way to trade tennis successfully.
If you know in advance how likely certain situations are to develop from others, then we can apply those numbers to the market and make long term, positive expectation, decisions, based on that information.
The problem is there that this isn’t easy, and requires hard work. But it is rewarding if you put the effort in.
Legendary trader and Twitter personality, @puntdotcom, once mentioned in an interview that to succeed, he advised to ‘keep every piece of data on anything you can keep data on.’
I couldn’t agree more. I have trading spreadsheets going back a very long time that I can analyse in conjunction with the historical point by point data, which allows me to build scenarios to analyse en masse.
This helped immensely in the Bacsinszky matches against Sharapova and Wozniacki this week.
I can go to my database and filter scenarios such as the following, for analysis:-
1) WTA 2014 season up to, and including 25th September, 2014.
2) Underdog starting price is 3.00 or higher.
3) Underdog wins first set.
4) Underdog has a ‘red’ projected hold on the daily spreadsheets (4.5% or below the surface mean).
5) Point by point data is available.
My database showed the following results:-
| Matches | Pre Match | Pre Match | Pre Match | Overall | |||
| Favourite | Favourite | Favourite | Success | ||||
| Wins Set | Breaks First | Goes Set & Break Down first |
Rate % | ||||
| Recovers It | |||||||
| Set 2 | Set 2 | Set 2 | |||||
| Yes | No | Yes | No | Yes | No | ||
| 52.78 | 46.53 | 62.34 | 79.86 | ||||
| 144 | 76 | 68 | 67 | 77 | 48 | 29 | |
So, from 144 matches, in 79.86% of scenarios the underdog did not train to 1.01.
Actually this figure should be slightly higher, as there were also some examples were the pre-match underdog staved off multiple break points, from scores like 0-40 or 15-40 either when the set was on serve, or from a set and break up, and this would have fairly large positive price movement for the pre-match favourite.
One example of this was the Angieszka Radwanska vs Dominika Cibulkova semi-final at the Australian Open on January 23rd, 2014. Cibulkova took the first set 6-1, and led 4-0 in set 2. At this point traders that stuck with Radwanska would be staring a loss in the face, but the Pole broke for *1-4 and held for 2-4*. In this next game, Cibulkova held despite going 0-30 and it is highly likely that traders who had held their position, and averaged down their position a set and break down would have been able to scratch at least, if not exit for slight profit at 0-30.
However, these weren’t quantified and for purposes of analysis I’ll use the 79.86% figure for ‘non trains’ although I actually expect this percentage to be slightly higher, probably around the 82-83% mark. There was also one match, between Na Li and Barbora Zahlavova-Strycova, where there were no breaks in set 2 and it went to a tie-break.
What may surprise some readers is the low percentage that the pre-match favourite actually won the second set when they lost the first set – just 52.78%. However, when backing the pre-match favourite when a set down, you don’t necessarily need them to win the set – merely to have decent price movement in the direction you require according to your script is enough.
Also, the pre-match favourite didn’t even manage to take the first break in the set half the time, with the pre-match underdog going a set and break up on 77/144 occasions (53.47%).
Having said this, the pre-match favourite’s performance from a set and break down was incredible. They recovered this deficit to get the set back on serve 48/77 times (62.34%) and this percentage is stellar – 18.37% above the 43.97% WTA average and this 62.34% percentage is also higher than ANY individual WTA player’s break-back percentage over the last 12 months.
So, how does this allow us to formulate a trading plan?
Let’s assume the following (the worst case scenario):-
1) We laid Bacsinszky when a break up at *2-1 and hedged for profit when Wozniacki broke for 3-3.
2) We then laid again when she led by a break again at *5-4 and lost when she served the set out.
This probably gave us a small losing position if we were to equal hedge, but instead of this we can add to our lay of Bacsinszky by doing so again at the start of set two. We now know that in almost 80% of matches we get a chance to hedge for profit at some point, and are able to scratch trade a few percent more as well.
In this spot, Wozniacki broke first after the previously mentioned scary moments where the market was clearly getting nervy, and we can, at that point, either equally hedge for profit, or at least clear liability on the Dane and look for the big market flip. The markets generally love the set two winner prior to a deciding set so this isn’t a bad strategy whatsoever.
In the Sharapova vs Bacsinszky match, Bacsinszky actually took a tiebreak to win the first set and didn’t lead by a break, so a back of Sharapova when a set down would have yielded immediate dividends when she broke for *1-0 in the first game of set two.
In either of these matches, should Bacsinszky actually have broken first in set two, we can average down our lay price by laying her when a set and break up, knowing that the pre-match favourite’s record for recovering break deficits is magnificent from this situation.
Holding positions and averaging down lay prices requires a high degree of courage and mental strength, but with detailed knowledge of the numbers involved in previous similar scenarios, this allows us to keep a level head, knowing that in around 80% of matches we will be able to trade out for significant profit.
Finally, on the subject of ‘averaging down’, I notice that many financial websites do not advise this style of trading.
However, with the financial markets, it’s highly unlikely that investors do not know when the optimal times are to re-enter the market again, and may re-enter incorrectly. Furthermore, it’s also much more difficult, if not impossible, to equate the likelihood of a position rising again.
In the sports trading markets, it’s different. Analysing historical scenarios allows us to apply the percentage of outcomes (the likelihood of a swing back in the market) to the various key situations of a tennis match and these can tell us when to enter, and average down, to good effect.
