The use of athlete wearable and tracking technology is growing, and a significant amount of data can now be produced for athlete performance. The next step is to leverage this data into predictive analytics that can be used by coaches for game planning and recruiting.
Here are some of the ways that CSA can leverage data produced from tracking systems into predictive analytics:
- Optimizing the starting line-up
- Predicting Readiness – An analysis of the athlete’s performance and biometric data can determine the “readiness” of a player for game day. Predictive analytics can incorporate this data into an analysis of the “optimum starting lineup”
- Injuries – Performance data can be used to calculate the impact of an injury to the starting lineup and provide analysis on why a particular player is the best starter. Equally important is using this data to prevent injuries in the future or to prevent re-injury
- Game planning
- Coaches can use the data as part of the self-scouting process. The athlete performance data is an input into the analysis that predicts the strengths and weaknesses of the players against an opponent. This helps identify where team weaknesses need to be managed and opponent weaknesses can be exploited
- Finding the “best fit” recruit or draft pick
- Data points on the performance of the existing athletes on the team can be used to identify the weaknesses of a team and can be used in defining and targeting the “best fit” recruit that meets the needs of the teams
Interested in learning more about how coaches find the “best fit” players for their teams? Make sure to check out our coaching tool, scoutSMART, and follow us on Twitter for all the latest recruiting updates and news.
-Diane Bloodworth, CEO of Competitive Sports Analysis