LEXINGTON, Massachusetts (May 16, 2015) - WinterGreen Research announces that it has published a new study Sports Analytics: Market Shares, Strategy, and Forecasts, Worldwide, 2015 to 2021. 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.
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.
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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SPORTS ANALYTICS EXECUTIVE SUMMARY
Sports Analytics Market Driving Forces
Sports Analytics Organizational Market Driving Forces
Play of the Game
Sports Analytics Market Shares
Sports Analytics Market Forecasts
1. SPORTS ANALYTICS MARKET DESCRIPTION AND MARKET DYNAMICS
1.1 All Teams Crunch Numbers
1.2 Sports Analytics That Appeal to the Fan Base
1.2.1 Hockey Analyses Take Into Account Situations (Even-Strength, Power Play, Shorthanded)
1.2.2 Analytics Change the Outcome of the Games
1.2.3 Seriously Flawed Sports Analytics
1.3 Team Sports Analytics
1.3.1 Red Sox Sports Analytics Information Services
1.3.2 Red Sox Win the World Series Three Times
1.3.3 Red Sox Value Patient Hitters
1.3.4 New York Yankees
1.3.5 Moneyball Is Alive And Well in Oakland
1.3.6 Oakland A's General Manager Billy Beane Moneyball
1.3.7 MLB Tampa Bay Rays
1.4 Hockey Analytics
1.5 Soccer Sports Analytics
1.5.1 Liverpool And The Director Of Football
1.5.2 Global Football Has Fundamental Shift Going On
1.6 NFL Stats Football Analytics
1.7 Media Sports Analytics
1.8 Auto Racing Stats and Analytics
1.9 Spurs of the National Basketball Association
1.9.1 NBA Corner Shot For Three Points
1.9.2 Resting Aging Stars For Deep Playoff Runs
1.9.3 NBA Rockets Team Investment in Analytics
1.9.4 Defensive Shifts In Baseball vs. Defensive Shifts in Hockey
1.10 MLB Tampa Bay Rays
1.11 Dallas Mavericks Basketball Team
1.12 NHL Hockey Los Angeles LA Kings
1.13 Professional Golfers
1.14 Road Cycling
1.15 Sports Data Visualization
1.15.1 Data Visualization
1.15.2 Sports Analytics for Fans
1.16 Sports Team Ownership
2. SPORTS ANALYTICS MARKET SHARES AND MARKET FORECASTS
2.1 Sports Analytics Market Driving Forces
2.1.1 Sports Analytics Organizational Market Driving Forces
2.1.2 Play of the Game
2.1.3 NHL Shift Charts
2.2 Sports Analytics Market Shares
2.2.1 Companies and Media Focused on Sports Analytics
2.2.2 Stats
2.2.3 Stats/Prozone Describes Performance
2.2.4 Perform/Opta
2.2.5 OptaPro Portal
2.2.6 TruMedia
2.2.7 Catapult Team
2.2.8 Catapult: National Hockey League NHL
2.2.9 Catapult Total Revenue
2.2.10 QSTC
2.2.11 Bodybuilding.com
2.2.12 Sportvision
2.2.13 Fox NFL Predictions
2.2.14 Synergy Basketball Designed for Coaches By Coaches
2.3 Sports Analytics Market Forecasts
2.3.1 Sports Analytics Market Segments
2.3.2 Personal Analytics
2.4 Sports Analytics Regional Market Analysis
2.4.1 US
3. SPORTS ANALYTICS PRODUCT DESCRIPTION
3.1 STATS
3.1.1 Stats’ SportVU Technology
3.1.2 Stats ICE - Basketball Operations Solutions
3.1.3 Stats Fantasy Sports
3.1.4 Stats Fantasy Games
3.1.5 Stats Pick/Predictor Fantasy
3.1.6 Stats Salary Cap Fantasy
3.1.7 Stats Leagure Stype Fantasy
3.1.8 Stats Commissioner Fantasy
3.1.9 Stats Bracket Fantasy
3.1.10 Stats' Sports Solutions Group
3.1.11 Stats Player Tracking
3.1.12 STATS MatchCast
3.1.13 Stats Prozone
3.1.14 Prozone World Cup 2014
3.1.15 Prozone Data, Information, Insights.
3.1.16 Prozone’s Football Heritage
3.1.17 Prozone Describes Performance
3.1.18 Prozone Opposition Scouting
3.1.19 Prozone Team Analysis
3.1.20 Prozone Physiological Monitoring
3.1.21 Prozone Player Recruitment
3.1.22 Stats Global Network
3.1.23 Stats Strategic Support
3.1.24 Stats Case Studies
3.1.25 Stats Football
3.1.26 Stats Rugby Union
3.1.27 Stats Rugby League
3.2 Perform/OptaPro
3.2.1 OptaPro VideoHub Elite
3.2.2 OptaPro VideoHub Elite Competitions Covered
3.2.3 OptaPro Portal
3.2.4 Opta
3.2.5 Opta Sports Data
3.2.6 Opta Sportsbook Predictive Analytics & Data Modelling
3.2.7 Opta Analytics In Action
3.3 TruMedia Sports Analytics
3.3.1 TruMedia's MLB Analytics Platform
3.3.2 TruMedia MiLB Minor League Analytics
3.3.3 TruMedia Soccer Analytics
3.3.4 TruMedia Crossing Pattern Football Analytics Platform/ESPN
3.4 Sportvision
3.4.1 Sportvision Motorsports Driving Innovation
3.4.2 ESPN Commits to Sportvision K-Zone Live on Every Pitch for MLB Coverage
3.4.3 SmartSports, Boston-Based Parent Company of SmartKage, and Sportvision
3.4.4 NHL, Sportvision Progress in Chip-Based Player Tracking
3.4.5 NHL Website Advanced Statistics
3.5 Sports Vision Technologies P3ProSwing Professional Golfers
3.6 Fox What If Embraces Technology as It Redefines Sports Competition
3.6.1 Fox What If Sports Simulations
3.6.2 Fox Sports Analytics
3.6.3 STATS LLC Global Sports Statistics
3.6.4 Stats Quarterbacks
3.4.5 Stats Running Backs
3.4.6 Stats Tackle
3.6.7 FoxSports.com
3.6.8 Foxsports.com/Whatifsports.com
3.6.9 FoxSports.com WhatIfSports.com: Positioned As Sports Simulation Destination
3.6.10 Foxsports NFL Prediction Widgets
3.6.11 Foxsports CFB Predictions
3.6.12 Foxsports SimMatchup
3.6.13 Foxsports MLB Power Rankings
3.7 ESPN Analytics
3.7.1 ESPN NFL National Football League
3.7.2 ESPN Major League Baseball Sports Analytics
3.7.3 National Basketball Association
3.7.4 ESPN Blackhawks Hockey Analytics Effectiveness
3.7.5 ESPN Stats & Information
3.7.6 ESPN Stats & Info
3.8 CBS Sports Analytics
3.8.1 St. Louis Blues Coach Ken Hitchcock Uses Analytics To Help Make Better Line Combinations
3.8.2 NHL Shot Location Data
3.9 Cognitive Computing Real Time Sports Analytics
3.10 Pro Football Focus
3.10.1 SportVU Football Solutions
3.11 IBM Watson Cognitive Computing
3.11.1 IBM Golf TryTracker
3.11.2 IBM Grand Slam Tennis
3.12 Sports Analytics Institute: Player Evaluation System
3.12.1 Sports Analytics Institute Growing an Organization's Sports Analytics Competency
3.12.2 Sports Analytics Institute: Hockey
3.13 Baseball Swing Analysis
3.13.1 MLB myHits 6 Key Hitting Stages
3.13.2 MLB League Tools and Services
3.14 82games
3.15 Catapult
3.15.1 Catapult Team Customer Base
3.15.2 Catapult Monitoring Elite Athletes
3.16 Real Sports Analytics
3.16.1 Real Sports Analytics Player Performance Scorecards
3.17 Sports Business Intelligence
3.18 SAS
3.18.1 SAS Sports Analytics
3.18.2 SAS Customer Intelligence Analytics
3.19 SAP
3.20 Hawk-eye
3.21 Nike+
3.21.1 Nike Personal Analytics
3.22 QSTC
3.23 Synergy Sports
3.24 CSA – Competitive Sports Analysis
3.25 Sports Analytics Institute
3.25.1 Sports Analytics Institute Player Evaluation System
3.26 Oracle
3.27 Google Analytics
3.27.1 Google Analytics Used In Loyalty Program
4. SPORTS ANALYTICS TECHNOLOGY
4.1 Legislation: UEFA’s Financial Fair Play (FFP), Premier League’s Elite Player Performance Plan (EPPP)
4.1.1 UEFA’s Financial Fair Play (FFP)
4.1.2 Elite Player Performance Plan (EPPP)
4.1.3 Elite Player Performance Plan (EPPP) Focus on Youth Development
4.2 Major League Baseball MLB Analytics
4.3 US National Football League NFL
4.4 John Henry Owner of Boston Red Sox Uses Sports Analytics to Win World Series
4.5 Stats Technology
4.5.1 STATS Servers
4.5.2 STATS RESTful API
4.5.3 Stats Interactive
4.6 Sports Analytics Dynamic Architecture
4.6.1 Google Search Engine Dynamic Architecture
4.6.2 BigFiles
4.6.3 Repository
4.6.4 Microsoft .Net Defines Reusable Modules Dynamically
4.6.5 Microsoft Combines Managed Modules into Assemblies
4.6.6 Microsoft Architecture Dynamic Modular Processing
4.6.7 IBM SOA Architecture is Dynamic for the Transport Layer
4.7 IBM WebSphere MQ Dynamic Architecture is Base for SOA
4.8 IBM Software Enterprise Service Bus
4.8.1 IBM ESB and SOA
4.9 Electromagnetic 12 Sensor 6 DOF Golf System
4.8.2 Golf Electromagnetic Flexible Screen
4.8.3 Experts Can Note Needed Improvements, Create Database Of A Person’s Own Swings
5. SPORTS ANALYTICS COMPANY PROFILES
5.1 Advanced Sports Analytics
5.2 Analytics Educational
5.3 Associated Press
5.3.1 AP Positioning
5.3.2 Associated Press Not-For-Profit Cooperative
5.4 Bodybuilding.com
5.5 Catapult: NHL Technology Reduces Injuries
5.5.1 Catapult Focused on US College Sports System
5.5.2 Catapult Data Collection
5.5.3 Catapult Revenue
5.5.4 Catapult Regional Revenue
5.5.5 Catapult Total Revenue
5.5.6 Catapult US:
5.5.7 Catapult EU
5.5.8 Catapult ROW
5.5.9 Catapult Total Units Ordered
5.5.10 Catapult Player Tracking in Australian Rules Football
5.5.11 Catapult Hockey Player Tracking
5.5.12 Catapult Device
5.5.13 Catapult in the NFL
5.5.14 Catapult Can Help Trainers Understand How Much Stress Of The Game
5.5.15 Catapult Measuring Intense Play
5.5.16 Big Wave Surfers Use Catapult to Ready for Event
5.6 Competitive Sports Analysis
5.7 Major League Baseball (MLB) Teams
5.7.1 MLB.com Digital Academy Instructional Center
5.7.2 MLB Coaches Corner
5.7.3 Youth Baseball Leagues
5.7.4 MLB my Hits
5.7.5 MLB myPitch
5.8 Motor Sports Analytics
5.9 National Football League (NFL)
5.9.1 AFC-North
5.9.2 AFC-South
5.9.3 AFC-East
5.9.4 AFC-West
5.9.5 NFC-North
5.9.6 NFC-South
5.9.7 NFC-East
5.9.8 NFC-West
5.9.9 NFL Stats
5.10 Perform/Opta Pro
5.10.1 Opta
5.10.2 Opta Partner Clients
5.10.3 Opta Partners for Betting
5.10.4 Opta Partners for Broadcast
5.10.5 Opta Partners for Online and Mobil
5.10.6 Opta Partners for Print
5.10.7 Perform Revenue
5.10.8 Perform Acquires Opta
5.11 Ramp Holdings
5.11.1 RAMP Holdings ROI
5.11.2 RAMP Holdings Capital Investment and Revenue
5.11.3 RAMP Holdings Partners
5.12 SmartSports
5.12.1 SmartSports/Sportvision
5.12.2 Sportvision
5.12.3 MLS Teams Seek Edge With Player-Tracking Technology
5.13 Sports Vision Technologies
5.14 Statistical Sports Consulting
5.15 Synergy Sports
5.15.1 Synergy Basketball Designed for Coaches By Coaches
5.15.2 Synergy Changes The Game
5.16 TruMedia Networks
5.16.1 Tony Khan Acquires Sports Analytics Firm TruMedia Networks
5.16.2 TruMedia Networks/Detroit Tigers Long Term Licensing Agreement
5.16.3 TruMedia Partners with Harvard Sports Analysis Collective
5.16.4 Jacksonville Jaguars Executive Tony Khan makes Strategic Investment in TruMedia Networks
5.16.5 TruMedia Networks Baseball Analytics Site In Partnership With Journalist Peter Gammons
5.16.6 TruMedia Networks and ESPN Power NFL Crossing Pattern Analytics Product
5.17 Vista Equity Partners
5.18.1 STATS
5.17.2 Stats Was Part of News Corporation (the parent of FOXSports.com) and the Associated Press
5.17.3 Stats Customers
5.17.4 STATS/Prozone
5.17.5 Prozone Software Tracks In-Game Player Performance
5.17.6 Stats Revenue
5.17.7 Stats Locations Worldwide
5.17.8 STATS Sports Public Relations
5.17.9 STATS Data And Content Company
5.17.10 Stats Data Centers
5.17.11 Stats Acquisitions
5.17.12 STATS/Sportz Interactive
5.17.13 STATS Projections for Daily Fantasy Sports
5.17.14 Vista Equity Partners And STATS Acquire Automated Insights
5.17.15 STATS Acquires The Sports Network
5.17.16 STATS Acquires TVTI
5.17.17 STATS Acquires Bloomberg Sports
5.17.18 STATS/Automated Insights
5.18 Sports Analytics Companies
5.18.1 Sports Analytics Vendors
5.18.2 PRINT MEDIA
5.18.3 DIGITAL MEDIA
5.18.4 Television/Video
LIST OF TABLES AND FIGURES
Table ES-1 Types of Organizations Using Sports Analytics
Table ES-2 Sports Analytics Market Driving Forces
Table ES-3 Sports Analytics Market Driving Factors for Player’s Agents
Table ES-4 Sports Analytics Market Aspects
Table ES-5 Sports Analytics Market Forces
Table ES-6 Sports Video Analytics Market Driving Forces
Table ES-7 Sports Analytics Fantasy Game Market Driving Forces
Table ES-8 Sports Analytics Uses
Figure ES-9 Sidney Crosby ?87 Of The Pittsburgh Penguins Celebrates A Second Period Goal With Teammate
Figure ES-10 Sports Analytics Market Shares, Dollars, Worldwide, 2014
Figure ES-11 Sports Analytics Market Forecasts Dollars, Worldwide, 2015-2021
Figure 1-1 Hockey Goal Scoring
Table 1-2 Owner John Henry and the Red Sox Leverage Sports Analytics
Table 1-3 Red Sox Sports Analytics Positioning
Figure 1-4 Red Sox Value Patient Hitters
Table 1-5 Sports Analytics in the Context of Physicality
Figure 1-6 Major League Baseball Average Roster Cost Per Win
Table 1-7 Web Sites Dedicated To Hockey Analytics
Figure 1-8 Rockets Lowest Percentage Of Midrange Shots
Figure 1-9 Major League Baseball Average Roster Cost Per Win
Figure 1-10 NHL Hockey Los Angeles LA Kings
Table 1-11 Cycling Computer Output
Table 1-12 Factors that Impact Ownership Use of Analytics for Sports Management
Table 2-1 Types of Organizations Using Sports Analytics
Table 2-2 Sports Analytics Market Driving Forces
Table 2-3 Sports Analytics Market Driving Factors for Player’s Agents
Table 2-4 Sports Analytics Market Aspects
Table 2-5 Sports Analytics Market Forces
Table 2-6 Sports Video Analytics Market Driving Forces
Table 2-7 Sports Analytics Fantasy Game Market Driving Forces
Table 2-8 Sports Analytics Uses
Figure 2-9 Sidney Crosby ?87 Of The Pittsburgh Penguins Celebrates A Second Period Goal With Teammate
Figure 2-10 NHL Shift Chart Player Statistics
Figure 2-11 NHL Shift Chart Goals Scored Line Statistics
Figure 2-12 NHL Entire Game Shift Chart
Figure 2-13 Sports Analytics Market Shares, Dollars, Worldwide, 2014
Table 2-14 Sports Analytics Market Shares, Dollars, Worldwide, 2014
Figure 2-15 MIT Sloan Sports Analytics Conference Attendees
Table 2-16 MIT Sloan Sports Analytics Conference Attendees
Table 2-17 Media Using Sports Analytics
Table 2-18 Digital Media Using Sports Analytics
Table 2-19 Television/Video Media Using Sports Analytics
Figure 2-20 Sports Analytics Market Forecasts Dollars, Worldwide, 2015-2021
Table 2-21 Sports Analytics Market Forecasts Dollars, Worldwide, 2015-2021
Table 2-22 Sports Analytics Market Segments, Worldwide, Dollars, 2015-2021
Figure 2-23 Sports Analytics Market Segments, Worldwide, Percent, 2015-2021
Table 2-24 Sports Analytics Technology Target Markets
Figure 2-25 Sports Analytics Regional Market Segments, Dollars, 2014
Table 2-26 Sports Analytics Regional Market Segments, 2014
Figure 3-1 Stats’ SportVU Technology
Table 3-2 STATS’ SportVU Technology Target Markets
Table 3-3 Stats Turn-Key Fantasy Solution Functions
Figure 3-5 Stats Fan Experience
Table 3-6 Stats Leveraging The Timeline
Figure 3-7 Opta Sport Analytics Advanced Layer, Next Level Of Data Provision
Figure 3-8 Opta VideoHub Elite Data-Led Video Analysis
Table 3-9 Opta VideoHub’s Key Strengths
Figure 3-10 OptaPro VideoHub Elite Competitions Covered
Figure 3-11 OptaPro Portal
Figure 3-12 Opta Cricket Wagon Wheel Graphic, Created Using Data For BBC Sport
Figure 3-13 Opta Analytics Charting Success, Unsuccessful, and Assists
Figure 3-14 Investec Leveraging Opta Data Analytics
Figure 3-15 TruMedia's MLB Analytics Platform
Figure 3-16 TruMedia Networks Albert Pujols Batting Pattern
Table 3-17 TruMedia Analytics Platform Positioning
Figure 3-18 TruMedia Heat Zone Analytics
Figure 3-19 TruMedia Soccer
Table 3-20 TruMedia's Soccer Analytics Platform League Coverage
Figure 3-21 ESPN uses TruMedia's Soccer Analytics Platform
Table 3-22 TruMedia/ESPN Crossing Pattern NCAA Conferences Covered
Figure 3-23 Sportvision Sports Tracked
Figure 3-24 Sportvision NHL Puck Tracking System
Figure 3-25 Sportvision NHL Game Tracking System
Figure 3-26 Sports Vision Technologies P3ProSwing In-depth Golf Swing Analysis
Table 3-29 Golf Courses Available on P3ProSwing Golf Analytics Simulator
Table 3-30 Fox Sports Analytics Types of Simulations
Figure 3-31 Foxsports Dream Team SimMatchup
Table 3-32 Foxsports Whatifsports.com
Table 3-33 ESPN NFL Top 10 Analytics Use Ranking
Table 3-34 ESPN Major League Baseball MLB Analytics Use Ranking
Table 3-35 ESPN National Basketball Association NBA Analytics Use Ranking
Table 3-36 ESPN NHL National Hockey League Analytics Use Ranking
Table 3-37 ESPN Insider Knowledge Blog Posts
Figure 3-38 Hockey Analytics To Help Make Better Line Combinations
Table 3-39 Analytics Use as a Coaching Tool
Table 3-40 NHL Team Activities That Depend On Analytics
Table 3-41 Cognitive Computing Real Time Sports Analytics
Table 3-42 Cognitive Computing Sports Analytics Functions
Figure 3-43 IBM Augusta National Golf Try Tracker
Figure 3-44 IBM Predictive Analytics Technology Used In Rugby
Figure 3-45 IBM Sports Analytics Tennis Slam Tracker
Figure 3-46 IBM Sports Analytics Player Tracker
Figure 3-47 IBM Sports Analytics Tennis Stats COmparisons
Figure 3-48 IBM Sports Analytics Tennis Set Comparisons
Figure 3-49 IBM Sports Analytics Tennis Keys to the Match Tracker
Figure 3-50 Sports Analytics Institute Player Lifetime Value Evaluation System Components
Table 3-51 Sports Analytics Institute Player Evaluation System Stages
Figure 3-52 Major League Baseball MLB Baseball Swing Analysis
Figure 3-53 6 Key Hitting Stages
Table 3-54 Baseball Key Hitting Stages
Figure 3-55 Teaching Young Players Analytics
Figure 3-56 MLB Hitting Analytics for Young Players, Comparison to Big League Hitting Stars
Table 3-57 MLB.com Digital Academy Youth League Management Tools And Instructional Resources
Table 3-58 82games Types of Basketball Numbers
Table 3-59 82games Stats Collected on Each Player in a Game
Table 3-60 Catapult Team Customer Base
Table 3-61 Catapult for Coaches Providing Scientifically-Validated Metrics on Athlete Performance
Figure 3-62 Real Sports Analytics Player Performance Scorecard
Figure 3-63 Real Sports Analytics Player Detail View
Figure 3-64 Real Sports Analytics Player Weekly Performance Scorecard
Table 3-65 Real Sports Analytics Game Metric Player Measure
Figure 3-66 Real Sports Analytics Player Color Coded Performance Scorecard
Table 3-67 SAS Sports Analytics Functions
Table 3-68 Hawk-eye Sports Analytics Features
Table 3-69 Sports Analytics Institute Player Evaluation System Features
Table 3-70 Google Analytics Used In Loyalty Program
Table 4-1 UEFA’s Financial Fair Play (FFP)
Table 4-2 Elite Player Performance Plan (EPPP) Fundamental Principles
Table 4-3 Elite Player Performance Plan (EPPP) Focus Areas
Table 4-4 Elite Player Performance Plan (EPPP) Grading Factors
Table 4-5 Key Areas of EPPP Focus
Table 4-6 Major League Baseball MLB Streaming Media Analytics Functions
Figure 4-7 Stats Data Center Technology
Table 4-8 STATS Data Delivery Protocols:
Table 4-9 STATS Servers Modules
Figure 4-10 Stats Content Delivery
Figure 4-11 Oracle Powers Stats Databases
Figure 4-12 Stats Secure Connection
Table 4-13 Stats Information Provided
Table 4-14 Stats Sports Covered
Table 4-15 Stats Sports Leagues Covered
Table 4-16 Stats Interactive Functionality
Table 4-17 Google Dynamic Architecture
Figure 4-18 Microsoft .Net Dynamic Definition of Reusable Modules
Figure 4-19 Microsoft .NET Compiling Source Code into Managed Assemblies
Figure 4-20 Microsoft Architecture Dynamic Modular Processing
Table 4-21 Process Of SOA Implementation Depends On N-Dimensional Interaction Of Layers That Can Be Modeled by Business Analyst
Table 4-22 IBM SOA Business I Services Layers
Figure 4-23 IBM Smart SOA Continuum
Table 4-24 SOA Foundation Reference Architecture
Figure 4-25 IBM WebSphere MQ WMQ Providing a Universal Messaging Backbone
Figure 4-26 Golf Swing Analyzer
Table 4-27 Golf Biomechanics Report Features:
Table 5-1 Motion Measurement Analysis Functions
Figure 5-2 AP Global Reach Statistics
Figure 5-3 AP Image Statistics
Figure 5-4 AP Revenue By Customer and Format
Figure 5-5 AP Download Statistics
Figure 5-6 AP Growth in Sales
Figure 5-7 AP Newsroom Profile
Table 5-8 Catapult System Device Description and Components
Table 5-9 Catapult System Device Positioning
Table 5-10 Catapult System Device Functions
Figure 5-11 Catapult Trending on The Daily Cut
Figure 5-12 Catapult Trending on The MLB Stress
Table 5-13 Motor Sports Analytics Features
Figure 5-14 Opta Partners for Betting
Figure 5-15 Opta Partners for Broadcast
Figure 5-16 Opta Partners for Online and Mobil
Figure 5-17 Opta Partners for Clubs and Governing Bodies
Figure 5-18 Opta Partners for Print
Figure 5-19 Opta Sponsors and Brands
Figure 5-20 Opta Partners
Figure 5-21 RAMP Holdings Investors
Figure 5-22 RAMP Holdings Integration Partners
Figure 5-23 RAMP Holdings Technology Partners
Table 5-24 Sportvision Credentials: Sports Broadcasting Technology
Table 5-25 TruMedia Networks Platform Components
Table 5-26 TruMedia Networks Analytics Solutions Target Markets
Figure 5-27 Stats Companies
Table 5-28 STATS Sports Technology Target Markets
Figure 5-29 Stats Customers
Figure 5-30 Prozone Cameras
Table 5-31 Prozone Optical Player Tracking
