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市場調查報告書

運動分析的全球市場:佔有率、策略、預測(2015∼2021年)

Sports Analytics Market Shares, Strategies, and Forecasts, Worldwide, 2015-2021

出版商 WinterGreen Research, Inc. 商品編碼 330952
出版日期 內容資訊 英文 472 Pages
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運動分析的全球市場:佔有率、策略、預測(2015∼2021年) Sports Analytics Market Shares, Strategies, and Forecasts, Worldwide, 2015-2021
出版日期: 2015年05月25日 內容資訊: 英文 472 Pages
簡介

被預測運動分析市場規模2014年達到1億2500萬美金,至2021年達到47億美元。大幅度的成長由雲端運算的市場滲透、智慧型手機及社群媒體促進。

本報告提供運動分析市場相關分析、市場基本結構和推動因素、今後的市場規模、佔有率預測、主要產品的概要、主要企業簡介等資訊彙整、為您概述為以下內容。

摘要整理

第1章 運動分析市場概論、市場動態

  • 所有隊計算資料
  • 運動分析吸引了粉絲群
  • 隊伍運動分析
  • 曲棍球分析
  • 足球分析
  • NFL的足球分析
  • 媒體的運動分析
  • 摩托車賽統計、分析
  • NBA
  • MLB:Tampa Bay Rays
  • 籃球隊:Dallas Mavericks
  • NHL:Los Angeles LA Kings
  • 專業高爾夫
  • 公路自行車
  • 運動資料的視覺化
  • 運動隊的所有者

第2章 運動分析市場佔有率、預測

  • 運動分析市場促進要素
  • 運動分析市場佔有率
  • 運動分析市場預測
  • 運動分析的地區市場分析

第3章 運動分析產品概論

  • STATS
  • Perform / OptaPro
  • TruMedia Sports Analytics
  • Sportvision
  • Sports Vision Technologies P3ProSwing Professional Golfers
  • Fox What If Embraces Technology as It Redefines Sports Competition
  • ESPN Analytics
  • CBS Sports Analytics
  • Cognitive Computing Real Time Sports Analytics
  • Pro Football Focus
  • IBM Watson Cognitive Computing
  • Sports Analytics Institute: Player Evaluation System
  • Baseball Swing Analysis
  • 82games
  • Catapult
  • Real Sports Analytics
  • Sports Business Intelligence
  • SAS
  • SAP
  • Hawk-eye
  • Nike+
  • QSTC
  • Synergy Sports
  • CSA - Competitive Sports Analysis
  • Sports Analytics Institute
  • Oracle
  • Google Analytics

第4章 運動分析技術

  • 法律:UEFA的Financial Fair Play (FFP),Premier League's Elite Player Performance Plan (EPPP)
  • Major League Baseball MLB Analytics
  • 美國NFL
  • 波士頓紅襪隊的所有者John Henry使用運動分析贏得世界棒球錦標賽勝利
  • 統計技術
  • 運動分析的動態架構
  • IBM WebSphere MQ Dynamic Architecture 為SOA基礎
  • IBM Software Enterprise Service Bus
  • Electromagnetic 12 Sensor 6 DOF Golf System

第5章 運動分析:企業簡介

圖表一覽

目錄
Product Code: SH26381963

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.

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.

Table of Contents

                        Source: Sportvision.

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 Dynmics

  • 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 80

  • 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 173
    • 3.4.3. SmartSports, Boston-Based Parent Company of SmartKage, and Sportvision 174
    • 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 190
    • 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 332
  • 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 387
    • 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 436
    • 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 223
  • 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 241
  • 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
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