Latest Break-Back Stats

Su Wei Hsieh is very poor at keeping a break lead...

COMBINED OVERALL BREAK-BACK STATS SINCE MARCH 2014:-
WTA - 440 trades, 259 winners (58.86%) - 9.30% above WTA top 100 average
ATP - 297 trades, 131 winners (44.11%) - 10.79% above ATP top 100 average

18-24 MAY BREAK-BACK STATS (after 24th May):-
WTA - 41 trades, 22 winners (53.66%) - 4.10% above WTA top 100 average
ATP - 21 trades, 6 winners (28.57%) - 4.85% below ATP top 100 average

ROME MASTERS BREAK-BACK STATS (after 18th May):-
WTA - 47 trades, 26 winners (55.32%) - 5.76% above WTA top 100 average
ATP - 20 trades, 9 winners (45.00%) - 11.58% above ATP top 100 average

MADRID MASTERS BREAK-BACK STATS (after 11th May):-
WTA - 27 trades, 13 winners (48.15%) - 1.41% below WTA top 100 average
ATP - 26 trades, 12 winners (46.15%) - 12.73% above ATP top 100 average

COMBINED MUNICH/OEIRAS BREAK-BACK STATS (after 4th May):-
WTA - 16 trades, 7 winners (43.75%) - 5.21% below WTA top 100 average
ATP - 39 trades, 16 winners (40.00%) - 6.58% above ATP top 100 average

COMBINED 21-27th APRIL BREAK-BACK STATS (after 27th April):-
WTA - 36 trades, 26 winners (72.22%) - 22.66% above WTA top 100 average 
ATP - 29 trades, 10 winners (34.48%) - 1.06% above ATP top 100 average

MONTE CARLO MASTERS/WTA KUALA LUMPUR BREAK-BACK STATS (after 20th April):-
WTA - 6 trades, 5 winners (83.33%) - 38.77% above WTA top 100 average
ATP - 33 trades, 21 winners (63.64%) - 30.22% above ATP top 100 average

COMBINED 7th-14th APRIL BREAK-BACK STATS (after 13th April):-
WTA - 47 trades, 22 winners (46.81%) - 2.75% below WTA top 100 average
ATP - 33 trades, 17 winners (51.52%) - 18.10% above ATP top 100 average

COMBINED CHARLESTON/MONTERREY BREAK-BACK STATS (at end of tournament):-
WTA - 82 trades, 50 winners (60.98%) - 11.42% above WTA top 100 average

MIAMI BREAK-BACK STATS (at end of tournament):-
WTA - 65 trades, 47 winners (72.31%) - 22.75% above WTA top 100 average
ATP - 49 trades, 19 winners (38.78%) - 5.36% above ATP top 100 average

INDIAN WELLS BREAK-BACK STATS (at end of tournament):-
WTA - 71 trades, 39 winners (54.93%) - 5.37% above WTA top 100 average
ATP - 47 trades, 21 winners (44.68%) - 11.26% above ATP top 100 average


The above stats clearly illustrate the edge that the break-back stats in the TennisRatings Tier Two Daily Spreadsheets have.

Since I started keeping records of the break-back percentages in events in March, we can see that the players recommended by the spreadsheets to lay when a break up have generated at least 5% more winning trades than either the relevant ATP/WTA top 100 break-back mean, with WTA Miami in particular proving spectacularly successful.

Knowing which players to lay with a positive expectation when a break up is a crucial asset for swing traders and this information is unique to TennisRatings.  

If you would like the spreadsheet with full break-back information simply sign-up for TennisRatings updates.
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