Sports Analytics: Market Shares, Strategy, and Forecasts, Worldwide, 2015 to 2021 Size and Share Published in 2015-05-26 Available for US$ 4000 at Researchmoz.us
The 2015 study has 472 pages, 177 tables and figures. Worldwide markets are poised to achieve significant growth as the cloud computing for utility infrastructure and the tablets and smart phone communications systems make training information more cogent and more available, remaking all sporting everywhere.
Information services will leverage automated process to leverage cloud computing: services The value of sports analytics is the predictive capabilities provided. The best sports teams are the ones using the power of real-time information to their advantage. What to measure? What real time information is the best? Can the players game the analytics systems?
Lets start with the story of Babe Ruth. The “Babe” used to come to every at bat with the desire to win the game. So early in the game, aware that at the end of the game it would fall on him to win the game, the “Babe” would deliberately strike out on pitches that he really could hit. Later in the game, the pitcher would remember the pitches that had gotten the “Babe” out and “Babe Ruth” could hit with ease, winning the game defying the statisticians.
So, Babe Ruth used sports analytics in the 1930’s in reverse, hoping to entice the pitcher to throw that very pitch he could hit in a tight situation later in the game. His very success illustrates that in sports analytics sophistication is needed. For sports analytics to track Babe Ruth, it would have been necessary to look at the pitches he could hit at the end of the game, not just everything that came at him. How sophisticated is that? You have to know your players to do good sports analytics.
Babe Ruth is at the center of one of the sad stories of sporting in Boston. The Boston Red Sox baseball team, in 2003, had not won a world series since Babe Ruth was sold to New York, the so called “Curse of the Bambino.” John Henry, a financial analytics wizard came along and purchased the Boston Red Sox along with other partners and he took the team to three world series using sports analytics as the dominant force for running the team and building fan enthusiasm. Sports become the model for predictive business decision making. Business has been reorganized among teams, inspired by sports. Analytics, developed by businesses are finding innovative use in sports, leading to models for
business to organize and manage teams.
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Sports analytics market driving forces relate to the ability to improve winning percentages and decrease the cost of paying players. By implementing metrics functions that describe how to put together a winning team without a very high payroll, sports analytics provide a winning edge to team management. Analytics are used to figure out how a team can improve fan appeal.
Sports analytics are used for creating fantasy leagues, giving sports fantasy players access to statistics that enhances their play of the game. It is used to improve scouting, to detect new player unusual talent and evaluate players competitive capability. Using the system, the agent gains competitive advantage with teams when they present analysis about the players they represent.
Shift charts represent an image of changing data. In the chart above, the numbers along the top represent the shifts played during the game.. The black lines represent goals scored and show what line was on the ice offensively and defensively for each goal scored in each period, period one, period two, and period three. Sport analytics are about patterns, detecting patterns and attaching value to them by being able to predict better what players will succeed and what players will do well in a certain system. The patterns apply to teams, to players and to fans.
The data about the sport is relevant in a lot of different ways, some teams are more able than others to harness the patterns to their benefit. Does it make a difference? Do the teams with better analytics win? Apparently so. The MIT sports analytics conference is a testament to the value of technology in sports. In hockey, analytics has been adopted big time, the trend this summer of 2015 has been for NHL clubs to hire bloggers and website operators so their content is proprietary.
Play of the Game is what makes sports entertainment, and the players entertainers. Hockey is a particularly appealing sport because it has so much player contact. It is a contact sport. Some of the better plyers play with finesse. Ovechkin for example, who had 27 even-strength goals this season (fifth in the league) and who scored a league-leading 24 power play goals is fun to watch. He is a premier player because of style and this makes him a fan favorite.
According to Susan Eustis, principal author of the market research study, “Sports teams have discovered that with intelligent use of sports analytics they can dominate a league. As the early adopters prove that analytics makes the difference between winning and losing, all teams, mangers, and fantasy sports players need to adopt use of the solutions creating market growth opportunities.
Sports analytics market size at $125 million in 2014 is anticipated to reach $4.7 billion by 2021. Significant growth is driven by the smart phone and social media in addition to cloud computing market penetration. With smart phones and tablets beginning to get significant uptake all over the world sports analytics play into that market expansion. Growth is a result of sports league and team department efforts.
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Stats / Prozone
Perform / Opta
Advanced Sports Analytics
Catapult: NHL Technology
Competitive Sports Analysis
Major League Baseball (MLB)
Motor Sports Analytics
National Football League (NFL)
Perform / Opta Pro
SmartSports / Sportvision
Sports Vision Technologies
Statistical Sports Consulting
Vista Equity Partners / STATS
Smart Analytics Products
Sports Analysis Software
Sports Health Consultant
Sports Medicine Clinic
Sports Video Analysis
Video Analysis Software
Baseball Swing Analysis
Golf Swing Analysis Software
Motion Analysis Software
Football Analysis Software
Soccer Analysis Software
Sports Cloud Architecture
Sports Analysis Mobile
Sports Player Selection
Sports Fantasy Games
Sports Analysis Forecasts
Sports Analysis Market
Sports Analysis Web
SOA Advances In
Application Service Levels
Sports Analytics Flexible
Response To Changing
Innovation For Leagues
Innovation For Team
Sports Software Localization
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