SYSTEM AND METHOD FOR LIVE COUNTER-FACTUAL ANALYSIS IN TENNIS
A computing system identifies data related to a tennis match between a first player and a second player. The data includes a current match state and a current in-match performance. The computing system generates an input data set that includes the data related to the tennis match. The generating includes modifying the current match state to assume that the first player will win a next point in the tennis match. Based on the input data set, the computing system measures an importance of the next point to the first player winning the tennis match.
1 . A method comprising:
identifying, by one or more processors, tennis match data corresponding to a tennis match between a first player and a second player, wherein the tennis match data includes a current match state;
generating, by the one or more processors, an input data set including the tennis match data, the generating comprising modifying the current match state to assume that the first player will win a next point in the tennis match; and
predicting, by the one or more processors, a tennis match outcome based on the input data set and the modified current match state.
2 . The method of claim 1 , the method further comprising:
generating, by the one or more processors, an importance of the first player winning the next point.
3 . The method of claim 1 , the method further comprising:
identifying, by the one or more processors, a set of points in the tennis match between the first player and the second player;
determining, by the one or more processors, a gained leverage of the first player over the set of points; and
generating, by the one or more processors, a momentum of the first player based on the gained leverage.
4 . The method of claim 3 , the method further comprising:
determining, by the one or more processors, that the gained leverage for the next point exceeds a threshold; and
identifying, by the one or more processors, the next point as a clutch point.
5 . The method of claim 3 , wherein generating the momentum of the first player based on the gained leverage includes:
generating, by the one or more processors, an exponentially weighted moving average of the gained leverage of the first player.
6 . The method of claim 1 , the method further comprising:
predicting, by the one or more processors, a tennis match set outcome based on the input data set, the current match state, and the tennis match outcome.
7 . The method of claim 1 , the method further comprising:
outputting, by the one or more processors, one or more graphical representations corresponding to the tennis match outcome.
8 . A non-transitory computer-readable medium having one or more sequences of instructions stored thereon, which, when executed by a processor, causes a computing system to perform operations comprising:
identifying, by the computing system, tennis match data corresponding to a tennis match between a first player and a second player, wherein the tennis match data includes a current match state;
generating, by the computing system, an input data set including the tennis match data, the generating comprising modifying the current match state to assume that the first player will win a next point in the tennis match; and
predicting, by the computing system, a tennis match outcome based on the input data set and the modified current match state.
9 . The non-transitory computer-readable medium of claim 8 , the operations further comprising:
generating, by the computing system, an importance of the first player winning the next point.
10 . The non-transitory computer-readable medium of claim 8 , the operations further comprising:
identifying, by the computing system, a set of points in the tennis match between the first player and the second player;
determining, by the computing system, a gained leverage of the first player over the set of points; and
generating, by the computing system, a momentum of the first player based on the gained leverage.
11 . The non-transitory computer-readable medium of claim 10 , the operations further comprising:
determining, by the computing system, that the gained leverage for the next point exceeds a threshold; and
identifying, by the computing system, the next point as a clutch point.
12 . The non-transitory computer-readable medium of claim 10 , wherein generating the momentum of the first player based on the gained leverage includes:
generating, by the computing system, an exponentially weighted moving average of the gained leverage of the first player.
13 . The non-transitory computer-readable medium of claim 8 , the operations further comprising:
predicting, by the computing system, a tennis match set outcome based on the input data set, the current match state, and the tennis match outcome.
14 . The non-transitory computer-readable medium of claim 8 , the operations further comprising:
outputting, by the computing system, one or more graphical representations corresponding to the tennis match outcome.
15 . A computer system comprising:
a processor; and
a memory having programming instructions stored thereon, which, when executed by the processor, causes the system to perform operations comprising:
identifying tennis match data corresponding to a tennis match between a first player and a second player, wherein the tennis match data includes a current match state;
generating an input data set including the tennis match data, the generating comprising modifying the current match state to assume that the first player will win a next point in the tennis match; and
predicting a tennis match outcome based on the input data set and the modified current match state.
16 . The computer system of claim 15 , the operations further comprising:
generating an importance of the first player winning the next point.
17 . The computer system of claim 15 , the operations further comprising:
identifying a set of points in the tennis match between the first player and the second player;
determining a gained leverage of the first player over the set of points; and
generating a momentum of the first player based on the gained leverage.
18 . The computer system of claim 17 , the operations further comprising:
determining that the gained leverage for the next point exceeds a threshold; and
identifying the next point as a clutch point.
19 . The computer system of claim 17 , wherein generating the momentum of the first player based on the gained leverage includes:
generating an exponentially weighted moving average of the gained leverage of the first player.
20 . The computer system of claim 15 , the operations further comprising:
predicting a tennis match set outcome based on the input data set, the current match state, and the tennis match outcome.