Calling the Shots with
Machine Learning in Sports
Presented By:
Rahul Khanna
Knoldus
Our Agenda
About MachineX
MachineX
KSAI MACHINEX BLOGS KNOLX
 Calling the shots with Machine Learning in Sports
 Calling the shots with Machine Learning in Sports
ML in Predicitng Results
● One of the expanding areas necessitating good predictive
accuracy is sport prediction, due to the large monetary
amounts involved in betting.
● In addition, club managers and owners are striving for
classification models so that they can understand and
formulate strategies needed to win matches.
● These models are based on numerous factors involved in the
games, such as the results of historical matches, player
performance indicators, and opposition information.
 Calling the shots with Machine Learning in Sports
 Calling the shots with Machine Learning in Sports
Understanding the Team Better
● Understand the importance, in particular situations, of
individual points, shots, plays and players.
● Isolate behavior that contributed most to the team's win / loss
for each particular game on the field or court
● Measure the impact of different players including defensive
players and attacking players on a game's outcome
● Helps players and coaches to assess that attributes have the
greatest impact on player performance and whether
preparation can affect those attributes so that they can
concentrate their efforts on factors that really matter.
Help Make Better Decisions on Field
● Video refereeing with “Goal Line Technology(GLT)” can
accurately pickup errors and mistakes whether a ball has
crossed the goal line or not which human eye can’t due to
positioning and blockage.
● DRS (Decision Review System) a technology normally used in
cricket to assist the match officials with their decision making
process in a situation that may demand to challenge the
decision taken by an Umpire
● Similarly Snickometer is used to identify whether a ball has
really hit the bat or pad on realtime in a cricket match. Hot Spot
is also a similar advanced technique which leverages infrared
imaging system.
 Calling the shots with Machine Learning in Sports
DEMO
Thank You !

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Calling the shots with Machine Learning in Sports

  • 1. Calling the Shots with Machine Learning in Sports Presented By: Rahul Khanna Knoldus
  • 6. ML in Predicitng Results ● One of the expanding areas necessitating good predictive accuracy is sport prediction, due to the large monetary amounts involved in betting. ● In addition, club managers and owners are striving for classification models so that they can understand and formulate strategies needed to win matches. ● These models are based on numerous factors involved in the games, such as the results of historical matches, player performance indicators, and opposition information.
  • 9. Understanding the Team Better ● Understand the importance, in particular situations, of individual points, shots, plays and players. ● Isolate behavior that contributed most to the team's win / loss for each particular game on the field or court ● Measure the impact of different players including defensive players and attacking players on a game's outcome ● Helps players and coaches to assess that attributes have the greatest impact on player performance and whether preparation can affect those attributes so that they can concentrate their efforts on factors that really matter.
  • 10. Help Make Better Decisions on Field ● Video refereeing with “Goal Line Technology(GLT)” can accurately pickup errors and mistakes whether a ball has crossed the goal line or not which human eye can’t due to positioning and blockage. ● DRS (Decision Review System) a technology normally used in cricket to assist the match officials with their decision making process in a situation that may demand to challenge the decision taken by an Umpire ● Similarly Snickometer is used to identify whether a ball has really hit the bat or pad on realtime in a cricket match. Hot Spot is also a similar advanced technique which leverages infrared imaging system.
  • 12. DEMO