運動分析的全球市場 (2023～2030年):各展開、類型、解決方案、技術、終端用戶、運動、零件的規模、佔有率、成長分析、預測

Global Sports Analytics Market Size, Share, Growth Analysis, By Deployment, By Type, By Solution, By Technology, By End-Use, By Sport, By Component - Industry Forecast 2023-2030

出版日期: 2023年04月23日 | 出版商:

SkyQuest | 英文 165 Pages | 商品交期: 3-5個工作天內

價格

簡介目錄

運動分析的市場規模，2021年為17億9,000萬美元，2022年為22億2,000萬美元，從2023年到2030年的預測期間中預計以28.1％的年複合成長率發展，2030年成長到126億美元的規模。

由於隊伍效能的分析，選手的追蹤，傷口的監測，選手個人的調節計劃的最佳化等開現場資料的利用增加，預計推動運動分析市場需求。

本報告提供全球運動分析的市場調查，市場概要，市場的各種影響因素的分析，技術、革新趨勢，市場規模的變化、預測，各種區分、各地區的明細，競爭情形，主要企業簡介等彙整資訊。

市場概要
市場規模
市場動態
促進因素
機會
阻礙因素
課題
主要的市場洞察
技術分析
價格分析
供應鏈分析
價值鏈分析
市場生態系統
IP分析
貿易分析
Start-Ups分析
原料分析
革新矩陣
開發中產品的分析
宏觀經濟指標
主要投資分析
主要成功因素
競爭的程度
市場動態及預測
市場動態
促進因素
機會
阻礙因素
課題
法規情形
波特分析
未來阻礙相關Skyquest的特別洞察
全球運動分析市場:各部署
市場概要
雲端
內部部署

全球運動分析市場:各類型

市場概要
開現場
關斷現場
全球運動分析市場:各解決方案
市場概要
影音分析
生物分析
智慧穿戴式
全球運動分析市場:各技術
市場概要
AI
巨量資料
其他
全球運動分析市場:各終端用戶
市場概要
個人
隊伍
電子競技
全球運動分析市場:各運動
市場概要
足球
板球
籃球
棒球
其他
全球運動分析市場:各零件
市場概要
軟體
服務
全球運動分析市場:各地區
市場概要
北美
美國
加拿大
歐洲
德國
西班牙
法國
英國
其他的歐洲
亞太地區
中國
印度
日本
韓國
其他的亞太地區
南美
巴西
其他的南美
中東、非洲
GCC各國
南非
其他的中東、非洲
競爭情形
主要5家公司的比較
主要企業的地位
主要企業的採用策略
主要成功策略
市場上最近的活動
主要企業的市場佔有率
主要企業簡介
IBM Corporation
SAP SE
Stats Perform
Opta Sports
TruMedia Networks
Catapult Sports Pty Ltd
SportsSource Analytics
Synergy Sports Technology
Zebra Technologies Corporation
ChyronHego Corporation
Kinexon GmbH
SAS Institute Inc.
Tableau Software, LLC
Gracenote Sports
Nielson Sports
Sports Mechanics
Sportsvision
Advanced Sports Analytics, Inc.
Experfy, Inc.
Global Sports Analytics, Inc.

簡介目錄

Product Code: SQSG45C2019

Sports Analytics Market size was valued at USD 1.79 billion in 2021 and is poised to grow from USD 2.22 billion in 2022 to USD 12.6 billion by 2030, growing at a CAGR of 28.1% in the forecast period (2023-2030).

Demand for the sports analytics market is anticipated to be driven by the rising use of on-field data for team performance analysis, player tracking, injury monitoring, and optimising individual player strength and conditioning programmes. The team management, particularly when compared to off-field and on-field details about each player's planned strategy, the player recruitment process, and the starting lineup for the game. Further market expansion is anticipated as a result of managers placing a greater emphasis on real-time data while setting up workouts and developing alternative game strategies.

As technology has developed, analytics has gained importance. Managers create game strategies based on data analytics and statistics in order to win games. Because they offer managers, decision-makers, coaching staff, and players a solution that generates significant information on many factors of the entire team and individual players, these sophisticated analysis tools are crucial for the development of in-game strategy. The solutions let managers gather information on players, as well as weather and playing surface conditions, to better develop a strategy.

In the past, a game's outcome was entirely dependent on the performers and their abilities. However, big data, artificial intelligence (AI), and machine learning (ML) technology advancements have led to a change in pattern in sports analytics. The algorithms of this software examine variables including opponents, game circumstances, and performance in both domestic and international contexts to suggest the top players for particular requirements. On the other hand, machine learning and deep neural networks help managers and coaches choose winning probability combinations and values.

A clustering technique also targets particular groups through season ticket holder management data to support growing the fan base. Big data analytics improves team performance while increasing money from sales of products, sponsorships, broadcast rights, and tickets. Fantasy gaming solutions frequently integrate analytical data to display player information and specific players when selecting a player to win financial benefits. The industry is anticipated to benefit from the increased use of sports analytics solutions in fictional video games.

Top-down and bottom-up approaches were used to estimate and validate the size of the Global Sports Analytics Market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined by using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.

Segments covered in this report:

The Global Sports Analytics market is segmented based on Deployment, Type, Solution, Game, End-Use, Game, and Region. Based on Deployment, the market is segmented into Cloud and On-premise. Based on Type, the market is segmented into On Field and Off Field. Based on the Solution, the market is segmented into Video Analytics, BioAnalytics, and Smart Wearable. Based on End-Use, the market is segmented into individuals, Teams, and e-Sports. Based on Game, the market is segmented into Football, Cricket, Basketball, Baseball, and Others. Based on Component, the market is segmented into Software and Service. Based on region the global Sports Analytics market is segmented into North America, Europe, Asia-Pacific, South America, and MEA.

Driver

The Use of Big Data and Related Technologies is Growing

Modern technologies like the cloud, IoT, big data analytics, agility, and social media have been adopted, resulting in innovation and change that has boosted the economy in the business ecosystem. Modern business models have replaced the outdated ones thanks to digital technologies. The adoption of big data and related technologies has accelerated due to the rise in demand for in-depth knowledge. The globalisation of businesses, which is causing an increase in data volumes and sources, is to blame for the exponential rise in data volume. Every organization's machine learning professionals now have faster evaluation skills because to the concentration of massive volumes of data in one place. By utilising the difficulties and possibilities presented by big data sports analytics, businesses can improve important business activities, processes, and goals.

Internet expansion and rising use of connected and integrated technologies

The development of the internet and the availability of several methods for accessing it have led to a significant rise in the amount of data generated. As a result, high-speed internet service providers would benefit from expansion and advancement. Additionally significant variables pushing higher data output globally include economic development and global expansion. Every consumer touchpoint has developed into a key data point that may be produced to disclose user behaviour as a result of the growth in touchpoints and the requirement for data collecting to understand consumer behaviour. Sports analytics organisations will now engage data scientists and analysts to process gathered data due to the exponential growth in personal and organisational data. Sports analytics' potential to generate operating money is another element influencing adoption. This encourages businesses to spend money on sports analytics. Vendors of big data analytical market solutions now have the chance to benefit from the expansion and exceptional growth of the internet thanks to the proliferation of connected and consolidated technologies.

Restraint

Lack of Knowledge Regarding Benefits of Sports Analytics Solutions

The adoption of new technologies has typically lagged significantly behind in the sports business, but this has changed over time. Sports organisations are employing cutting-edge technical solutions to surpass competitors and create greater results. The cost of accessing infrastructure and facilities has increased as competition in sports, whether team or individual, has increased. Although it is still a small discipline, sports analytics will gain importance over the next few years. Despite increased interest in such innovations to boost performance in North and Europe, businesses in the areas lag in the use of analytics and other technologies due to poor technology penetration and stringent political restraints.

Sports organisations all around the region still rely on conventional analytic techniques, such as hiring former athletes or athletes themselves as coaches to instruct their teams and physiotherapists to evaluate the health of their players. The market for sports analytics is only slowly expanding due to each of these factors.

Market Trends

The unpredictability of the market and the quick uptake of new technologies are growing the use of these solutions globally, according to market trends in sports analytics. Businesses' focus on lowering software upgrades and maintenance needs is driving rising demand for software delivered via the cloud. This is due to the benefits that cloud-based solutions offer, including quick cloud computing, inexpensive costs, simple accessibility, and unlimited service. Superclubs are well-known due to their historic history of success, which has boosted their fan base and brand value, attracted great sportsmen from all over the world, and consequently raised sponsorships and investments. The future of football, according to these elite teams, is analytics.

Analytics' adoption has grown dramatically as a result of the world being more competitive, the requirement to establish decision-making to get an advantage over rivals, and the influence of social media. A key trend is the affiliation of teams and clubs with analytics organisations. For instance, Opta, a provider of football sports data, has teamed with a number of football clubs and leagues. Regardless of who is in possession of the ball, Opta's analytics can pinpoint every action a player does in a specific spot on the pitch. Analytics adoption is anticipated to be influenced by the increasingly competitive environment, the need for better decision-making to obtain an advantage over rivals, the execution of strategies for on-field competitions, and the effects of social media off the field. As a result, due to shifting sports dynamics and rising technology use in sports, the market share for sports analytics is projected to increase during the forecast period.