This dataset provides an archive of Fantasy Premier League (FPL) player performance data for eight seasons, spanning from 2016-2024.

The data was originally collected from https://github.com/vaastav/Fantasy-Premier-League, a public repository for FPL data.

The dataset has been meticulously cleaned and processed to ensure accuracy and consistency. This may include handling missing values, correcting inconsistencies, and standardizing formats.

The dataset includes a wide range of player statistics captured on a gameweek-by-gameweek basis. This allows you to analyze trends, identify patterns, and gain valuable insights into player performance.

This dataset can be a powerful tool for FPL enthusiasts and data scientists alike. Here are some potential applications: - Trend Analysis: Identify historical trends in player performance across different seasons and positions. - Predictive Modeling: Develop machine learning models to predict player points, performance, and transfers. - Informed Team Selection: Make data-driven decisions to optimize your FPL team for each gameweek. - Comparative Analysis: Compare player statistics across seasons and positions to uncover hidden gems and potential breakout stars.

Using this dataset, you can gain a deeper understanding of FPL player performance and enhance your decision-making for the upcoming season.

Snapshot img

Fantasy Sports Market Size 2025-2029

The fantasy sports market size is forecast to increase by USD 10.13 billion, at a CAGR of 7.1% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing popularity of dedicated apps and the utilization of these sports technology for brand promotion. The proliferation of user-friendly apps has made accessing and participating in fantasy sports more convenient than ever before, leading to a surge in demand. Brands recognize the potential of this trend, using fantasy sports as a marketing tool to engage consumers and build brand loyalty. However, the future of fantasy sports remains uncertain, with concerns surrounding the potential negative impacts on health and well-being. The addictive nature of fantasy sports gaming can lead to excessive time spent on digital platforms, negatively affecting productivity and overall well-being.
Companies must navigate these challenges by implementing responsible gaming practices and promoting a healthy balance between digital engagement and real-life activities. By addressing these concerns and continuing to innovate, fantasy sports providers can capitalize on the market's potential and maintain a strong competitive edge.

What will be the Size of the Fantasy Sports Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The market continues to evolve, with dynamic market activities unfolding across various sectors. Season-long fantasy sports platforms offer users customizable league settings, head-to-head matches, and real-time game data, enabling a more engaging user experience. Waiver wire transactions and player projections are integral components, requiring continuous analysis from fantasy sports analysts and machine learning algorithms. Fantasy sports communities foster interaction through player chat, news feeds, and podcasts, creating a vibrant ecosystem. Draft strategies and auction drafts vary, with salary cap leagues and private leagues offering unique challenges. Advertising revenue and affiliate marketing provide monetization opportunities, while privacy policies ensure user data security.

Daily fantasy sports (DFS) operators employ advanced statistical analysis and probability calculations to offer real-time contests, further fueling the market's growth. API integrations and data modeling enable seamless data access, while customer support and commissioner tools cater to league management needs. Freemium models, subscription models, and public leagues cater to diverse user preferences, with mobile applications and web applications ensuring accessibility. Risk assessment and lineup optimization strategies are essential for success, while injury reports and expert analysis inform user decision-making. Fantasy sports platforms continue to integrate social media, offering a more immersive experience. News feeds and custom leagues provide users with personalized content, further enhancing engagement.

How is this Fantasy Sports Industry segmented?

The fantasy sports industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Fantasy soccer
  Fantasy baseball
  Fantasy basketball
  Fantasy football
  Others


Application

  Individual Competition
  Team Competition


Demographic

  Under 25 Years
  Between 25 and 40 Years
  Above 40 Years


Dietary Preference

  Vegan
  Gluten-Free
  Keto


Target Audience

  Busy Professionals
  Health Enthusiasts


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  Middle East and Africa

    Egypt
    KSA
    Oman
    UAE


  APAC

    China
    India
    Japan


  South America

    Argentina
    Brazil


  Rest of World (ROW)

By Product Insights

The fantasy soccer segment is estimated to witness significant growth during the forecast period.

In the realm of fantasy sports, soccer holds a significant position, allowing participants to build teams comprised of real-life soccer players and earn points based on their on-field statistics or perceived value. Soccer fantasy leagues, such as Draft Fantasy Football, McDonald FIFA World Cup Fantasy, Fantasy Premier League, and UEFA Champions League Fantasy Football, attract a massive following due to the universal appeal of soccer. These platforms offer users flexibility to manage their rosters, making unlimited transfers before the season's commencement. Fantasy sports communities thrive on player chat, league settings, and head-to-head matches, fostering a competitive and engaging environment.

Season-long fantasy sports and daily fantasy

Download Free Sample
Fantasy Sports Analytics – Statistics and Analysis 2022-2026

The fantasy sports market analytics statistics provide and accurate prediction of the whole market. This data enables vendors to make informed decisions. The fantasy sports market share is expected to increase by USD 6.11 billion from 2021 to 2026, and the market's growth momentum will accelerate at a CAGR of 6.51%.

The fantasy sports market statistics also provide information on several market vendors, including Blitz Studios Inc., Dream Sports, Fantasy Power 11, Fantrax, Flutter Entertainment Plc, Fox Corp., GamesKraft Technologies Pvt. Ltd., Head Digital Works Pvt. Ltd., Josh Clemm, LivePools Pvt. Ltd., MyTeam11 Fantasy Sports Pvt. Ltd., Paramount, Playerzpot Media Pvt Ltd, Roto Sports Inc., RotoBash apps Pvt Ltd, Sachar Gaming Private Limited, The Football Association Premier League Ltd., The Walt Disney Co., and Yahoo Inc among others.

Only a specific statistics will certainly address your current needs but if you wish to get a glimpse about the full report, here is the sample for fantasy sports market analytics report 2022-2026, it will help you strengthen your plans and strategies for better growth.

This detailed analytics helps the new and established market players to access their current strategies and substitute them according to the data. this report extensively covers fantasy sports market segmentation by type (fantasy soccer, fantasy baseball, fantasy basketball, fantasy football, and others) and geography (North America, Europe, APAC, South America, and Middle East and Africa).

One of the key factors driving the global fantasy sports market growth is the launch of various apps for fantasy sports. The launch of various apps for fantasy sports is notably driving the fantasy sports market growth, although factors such as increasing traction of mobile video games and traditional e-sports may impede market growth.

This detailed analytics helps the new and established market players to access their current strategies and substitute them according to the data. You can get more information on the key market drivers, fantasy sports market trends, and challenges as well.

Fantasy sports service providers develop software and markets an online platform for multiplayer fantasy sports. Fantasy sports are games where participants act as general managers to build teams that compete with other fantasy owners based on the statistics generated by real individual players or professional teams. The most common variation converts statistical performance into points that are compiled and totaled according to a roster selected by a manager that makes up a fantasy team.

Download Free Sample
This fantasy sports market size report comprises information about the potential market growth during the forecast period. The market is expected to grow by USD 5.38 bn during 2021-2025, and the market’s growth momentum will accelerate at a CAGR of 6%.

This market report guides key and emerging vendors, in market expansion by taking into consideration various market drivers and the factors responsible for them. Click here to obtain the latest data on the size of fantasy sports market, competitive analysis, and other research information.

Fantasy Football Market Outlook

In 2023, the global fantasy football market size was valued at approximately USD 24.4 billion, and it is projected to reach USD 48.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.9%. This robust growth is driven by the increasing popularity of sports betting, the expansion of internet penetration, and the evolving digital landscape that has made fantasy sports more accessible to a global audience.

The burgeoning interest in fantasy football is significantly fueled by the thrill associated with virtual sports management and the competitive spirit it invokes among participants. The advent of high-speed internet and the proliferation of smartphones have considerably lowered entry barriers, enabling users from diverse demographics to engage with fantasy football platforms. Enhanced user interfaces and the strategic inclusion of real-time data and analytics have further enriched the user experience, making the game more immersive and engaging. Additionally, the growing partnerships between fantasy sports platforms and major sports leagues have enhanced the credibility and reach of the market.

Another crucial growth factor is the increasing monetization avenues within the fantasy football ecosystem. Platforms are leveraging ad revenues, subscription models, and in-app purchases to enhance their profitability. The introduction of innovative revenue streams like virtual goods, personalized content, and premium features provides substantial growth opportunities. Furthermore, the gamification of fantasy sports, including interactive features like social sharing and leaderboards, has significantly contributed to user retention and engagement.

Public perception and societal trends have also played a pivotal role in the market's growth. The cultural acceptance of fantasy sports as a mainstream activity has expanded its demographic reach beyond traditional sports enthusiasts. The integration of fantasy sports into mainstream media, including dedicated shows and podcasts, has increased visibility and user adoption. This cultural shift has also led to the formation of fantasy football communities, fostering a sense of camaraderie and collective enthusiasm.

American Football has played a pivotal role in the evolution of fantasy sports, particularly in North America, where the National Football League (NFL) stands as the most popular league for fantasy football. The deep-rooted passion for American Football among fans has translated into a robust fantasy football culture, with millions of participants engaging in both daily and season-long leagues. The NFL's extensive media coverage and the availability of detailed player statistics have made it an ideal sport for fantasy leagues, offering fans an opportunity to test their managerial skills and engage with the sport on a deeper level. This engagement is further amplified by the NFL's active promotion of fantasy football, which has helped to sustain and grow its fan base over the years.

From a regional perspective, North America continues to dominate the fantasy football market, driven by the high penetration of internet services and the strong sports culture in the region. The United States alone accounts for a significant portion of the market owing to the popularity of the National Football League (NFL). Meanwhile, Europe and the Asia Pacific are emerging as significant growth regions. The increasing popularity of soccer and the rising number of internet users in countries like India and China are expected to contribute to the market's expansion in these regions.

Platform Analysis

The fantasy football market is segmented into mobile applications and websites based on the platform. Mobile applications have revolutionized the fantasy sports experience by offering users the convenience of managing their teams on the go. The advent of sophisticated mobile apps with user-friendly interfaces, real-time updates, and interactive features has significantly enhanced user engagement. The integration of advanced analytics and personalized recommendations in mobile applications has made it easier for users to make informed decisions, thereby increasing user satisfaction and retention.

On the other hand, websites continue to be a popular platform among a segment of users who prefer a more detailed and expansive interface. Websites offer a broader range of features and functionalities compared to mobile applicatio

The Market Research Report Covers Fantasy Sports Companies and is Segmented by Fantasy Sports Type (Traditional Fantasy Sports, Daily Fantasy Sports & Ancillaries), Sporting Type (Football, Baseball, Basketball, Others), and Country. The market size and forecasts are provided in terms of value (USD million) for all the above segments.

The global fantasy football market is experiencing robust growth, driven by increasing smartphone penetration, readily available internet access, and the ever-growing popularity of professional football leagues worldwide. The engagement fostered by fantasy football platforms, which blend competition with strategic decision-making, fuels user loyalty and continuous engagement, translating into significant revenue streams for operators. The market is segmented by application (individual vs. team competitions) and access method (mobile phone vs. computer), with mobile platforms witnessing faster adoption due to convenience and accessibility. Major players like FanDuel, DraftKings, and ESPN dominate the market, leveraging their established brand recognition and sophisticated platforms. However, smaller, niche platforms are also emerging, catering to specific user preferences or offering specialized features. The North American market currently holds the largest share, fueled by the immense popularity of American football, but significant growth is anticipated in other regions, particularly in Europe and Asia, as the sport’s global reach expands and digital infrastructure improves. The competitive landscape is dynamic, with ongoing innovation in platform features, scoring systems, and marketing strategies to attract and retain users. The forecast period from 2025 to 2033 projects substantial market expansion, driven by factors such as enhanced user experience, increased integration of data analytics, and the growing adoption of esports-like features within fantasy football platforms. This will likely lead to an increase in advertising revenue and potential partnerships with leagues and merchandise providers. However, regulatory hurdles surrounding gambling, data privacy concerns, and the potential for user fatigue represent potential restraints. Overcoming these challenges requires ongoing platform development focusing on security, transparency, and responsible gaming practices. The market's success hinges on continuing innovation and adapting to evolving user preferences while navigating the regulatory landscape to maintain sustainable growth. We estimate the CAGR (based on a reasonable assumption) to be in the range of 10-15% for the forecast period, leading to significant market expansion.

Our NFL Data product offers extensive access to historic and current National Football League statistics and results, available in multiple formats. Whether you're a sports analyst, data scientist, fantasy football enthusiast, or a developer building sports-related apps, this dataset provides everything you need to dive deep into NFL performance insights.

Key Benefits:

Comprehensive Coverage: Includes historic and real-time data on NFL stats, game results, team performance, player metrics, and more.

Multiple Formats: Datasets are available in various formats (CSV, JSON, XML) for easy integration into your tools and applications.

User-Friendly Access: Whether you are an advanced analyst or a beginner, you can easily access and manipulate data to suit your needs.

Free Trial: Explore the full range of data with our free trial before committing, ensuring the product meets your expectations.

Customizable: Filter and download only the data you need, tailored to specific seasons, teams, or players.

API Access: Developers can integrate real-time NFL data into their apps with API support, allowing seamless updates and user engagement.

Use Cases:

Fantasy Football Players: Use the data to analyze player performance, helping to draft winning teams and make better game-day decisions.

Sports Analysts: Dive deep into historical and current NFL stats for research, articles, and game predictions.

Developers: Build custom sports apps and dashboards by integrating NFL data directly through API access.

Betting & Prediction Models: Use data to create accurate predictions for NFL games, helping sportsbooks and bettors alike.

Media Outlets: Enhance game previews, post-game analysis, and highlight reels with accurate, detailed NFL stats.

Our NFL Data product ensures you have the most reliable, up-to-date information to drive your projects, whether it's enhancing user experiences, creating predictive models, or simply enjoying in-depth football analysis.

[232+ Pages Report] The global fantasy sports market size is expected to grow from USD 24.39 billion in 2022 to USD 44.87 billion by 2030, at a CAGR of 14.84% from 2023-2030

Analysis of ‘Winter Olympics Prediction - Fantasy Draft Picks’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ericsbrown/winter-olympics-prediction-fantasy-draft-picks on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Olympic Draft Predictive Model

Our family runs an Olympic Draft - similar to fantasy football or baseball - for each Olympic cycle. The purpose of this case study is to identify trends in medal count / point value to create a predictive analysis of which teams should be selected in which order.

There are a few assumptions that will impact the final analysis: Point Value - Each medal is worth the following: Gold - 6 points Silver - 4 points Bronze - 3 points For analysis reviewing the last 10 Olympic cycles. Winter Olympics only.

All GDP numbers are in USD

My initial hypothesis is that larger GDP per capita and size of contingency are correlated with better points values for the Olympic draft.

All Data pulled from the following Datasets:

Winter Olympics Medal Count - https://www.kaggle.com/ramontanoeiro/winter-olympic-medals-1924-2018 Worldwide GDP History - https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?end=2020&start=1984&view=chart

GDP data was a wide format when downloaded from the World Bank. Opened file in Excel, removed irrelevant years, and saved as .csv.

Process

In RStudio utilized the following code to convert wide data to long:

install.packages("tidyverse") library(tidyverse) library(tidyr)

Converting to long data from wide

long <- newgdpdata %>% gather(year, value, -c("Country Name","Country Code"))

Completed these same steps for GDP per capita.

Primary Key Creation

Differing types of data between these two databases and there is not a good primary key to utilize. Used CONCAT to create a new key column in both combining the year and country code to create a unique identifier that matches between the datasets.

SELECT *, CONCAT(year,country_code) AS "Primary" FROM medal_count

Saved as new table "medals_w_primary"

Utilized Excel to concatenate the primary key for GDP and GDP per capita utilizing:

=CONCAT()

Saved as new csv files.

Uploaded all to SSMS.

Contingent Size

Next need to add contingent size.

No existing database had this information. Pulled data from Wikipedia.

2018 - No problem, pulled existing table. 2014 - Table was not created. Pulled information into excel, needed to convert the country NAMES into the country CODES.

Created excel document with all ISO Country Codes. Items were broken down between both formats, either 2 or 3 letters. Example:

AF/AFG

Used =RIGHT(C1,3) to extract only the country codes.

For the country participants list in 2014, copied source data from Wikipedia and pasted as plain text (not HTML).

Items then showed as: Albania (2)

Broke cells using "(" as the delimiter to separate country names and numbers, then find and replace to remove all parenthesis from this data.

We were left with: Albania 2

Used VLOOKUP to create correct country code: =VLOOKUP(A1,'Country Codes'!A:D,4,FALSE)

This worked for almost all items with a few exceptions that didn't match. Based on nature and size of items, manually checked on which items were incorrect.

Chinese Taipei 3 #N/A Great Britain 56 #N/A Virgin Islands 1 #N/A

This was relatively easy to fix by adding corresponding line items to the Country Codes sheet to account for future variability in the country code names.

Copied over to main sheet.

Repeated this process for additional years.

Once complete created sheet with all 10 cycles of data. In total there are 731 items.

Data Cleaning

Filtered by Country Code since this was an issue early on.

Found a number of N/A Country Codes:

Serbia and Montenegro FR Yugoslavia FR Yugoslavia Czechoslovakia Unified Team Yugoslavia Czechoslovakia East Germany West Germany Soviet Union Yugoslavia Czechoslovakia East Germany West Germany Soviet Union Yugoslavia

Appears to be issues with older codes, Soviet Union block countries especially. Referred to historical data and filled in these country codes manually. Codes found on iso.org.

Filled all in, one issue that was more difficult is the Unified Team of 1992 and Soviet Union. For simplicity used code for Russia - GDP data does not recognize the Soviet Union, breaks the union down to constituent countries. Using Russia is a reasonable figure for approximations and analysis to attempt to find trends.

From here created a filter and scanned through the country names to ensure there were no obvious outliers. Found the following:

Olympic Athletes from Russia[b] -- This is a one-off due to the recent PED controversy for Russia. Amended the Country Code to RUS to more accurately reflect the trends.

Korea[a] and South Korea -- both were listed in 2018. This is due to the unified Korean team that competed. This is an outlier and does not warrant standing on its own as the 2022 Olympics will not have this team (as of this writing on 01/14/2022). Removed the COR country code item.

Confirmed Primary Key was created for all entries.

Ran minimum and maximum years, no unexpected values. Ran minimum and maximum Athlete numbers, no unexpected values. Confirmed length of columns for Country Code and Primary Key.

No NULL values in any columns. Ready to import to SSMS.

SQL work

We now have 4 tables, joined together to create the master table:

SELECT [OlympicDraft].[dbo].[medals_w_primary].[year], host_country, host_city, [OlympicDraft].[dbo].[medals_w_primary].[country_name], [OlympicDraft].[dbo].[medals_w_primary].[country_code], Gold, Silver, Bronze, [OlympicDraft].[dbo].[gdp_w_primary].[value] AS GDP, [OlympicDraft].[dbo].[convertedgdpdatapercapita].[gdp_per_capita], Atheletes FROM medals_w_primary INNER JOIN gdp_w_primary ON [OlympicDraft].[dbo].[medals_w_primary].[primary] = [OlympicDraft].[dbo].[gdp_w_primary].[year_country] INNER JOIN contingency_cleaned ON [OlympicDraft].[dbo].[medals_w_primary].[primary] = [OlympicDraft].[dbo].[contingency_cleaned].[Year_Country] INNER JOIN convertedgdpdatapercapita ON [OlympicDraft].[dbo].[medals_w_primary].[primary] = [OlympicDraft].[dbo].[convertedgdpdatapercapita].[Year_Country] ORDER BY year DESC

This left us with the following table:

https://i.imgur.com/tpNhiNs.png" alt="Imgur">

Performed some basic cleaning tasks to ensure no outliers:

Checked GDP numbers: 1992 North Korea shows as null. Updated this row with information from countryeconomy.com - $12,458,000,000

Checked GDP per capita:

1992 North Korea again missing. Updated this to $595, utilized same source.

UPDATE [OlympicDraft].[dbo].[gdp_w_primary] SET [OlympicDraft].[dbo].[gdp_w_primary].[value] = 12458000000 WHERE [OlympicDraft].[dbo].[gdp_w_primary].[year_country] = '1992PRK'

UPDATE [OlympicDraft].[dbo].[convertedgdpdatapercapita] SET [OlympicDraft].[dbo].[convertedgdpdatapercapita].[gdp_per_capita] = 595 WHERE [OlympicDraft].[dbo].[convertedgdpdatapercapita].[year_country] = '1992PRK'

Liechtenstein showed as an outlier with GDP per capita at 180,366 in 2018. Confirmed this number is correct per the World Bank, appears Liechtenstein does not often have atheletes in the winter olympics. Performing a quick SQL search to verify this shows that they fielded 3 atheletes in 2018, with a Bronze medal being won. Initially this appears to be a good ratio for win/loss.

Finally, need to create a column that shows the total point value for each of these rows based on the above formula (6 points for Gold, 4 points for Silver, 3 points for Bronze).

Updated query as follows:

SELECT [OlympicDraft].[dbo].[medals_w_primary].[year], host_country, host_city, [OlympicDraft].[dbo].[medals_w_primary].[country_name], [OlympicDraft].[dbo].[medals_w_primary].[country_code], Gold, Silver, Bronze, [OlympicDraft].[dbo].[gdp_w_primary].[value] AS GDP, [OlympicDraft].[dbo].[convertedgdpdatapercapita].[gdp_per_capita], Atheletes, (Gold*6) + (Silver*4) + (Bronze*3) AS 'Total_Points' FROM [OlympicDraft].[dbo].[medals_w_primary] INNER JOIN gdp_w_primary ON [OlympicDraft].[dbo].[medals_w_primary].[primary] = [OlympicDraft].[dbo].[gdp_w_primary].[year_country] INNER JOIN contingency_cleaned ON [OlympicDraft].[dbo].[medals_w_primary].[primary] = [OlympicDraft].[dbo].[contingency_cleaned].[Year_Country] INNER JOIN convertedgdpdatapercapita ON [OlympicDraft].[dbo].[medals_w_primary].[primary] = [OlympicDraft].[dbo].[convertedgdpdatapercapita].[Year_Country] ORDER BY [OlympicDraft].[dbo].[convertedgdpdatapercapita].[year]

Spot checked, calculating correctly.

Saved result as winter_olympics_study.csv.

We can now see that all relevant information is in this table:

https://i.imgur.com/ceZvqCA.png" alt="Imgur">

RStudio Work

To continue our analysis, opened this CSV in RStudio.

install.packages("tidyverse") library(tidyverse) library(ggplot2) install.packages("forecast") library(forecast) install.packages("GGally") library(GGally) install.packages("modelr") library(modelr)

View(winter_olympic_study)

Finding correlation between gdp_per_capita and Total_Points

ggplot(data = winter_olympic_study) + geom_point(aes(x=gdp_per_capita,y=Total_Points,color=country_name)) + facet_wrap(~country_name)

cor(winter_olympic_study$gdp_per_capita, winter_olympic_study$Total_Points, method = c("pearson"))

Result is .347, showing a moderate correlation between these two figures.

Looked next at GDP vs. Total_Points ggplot(data = winter_olympic_study) + geom_point(aes(x=GDP,y=Total_Points,color=country_name))+ facet_wrap(~country_name)

cor(winter_olympic_study$GDP, winter_olympic_study$Total_Points, method = c("pearson")) This resulted in 0.35, statistically insignificant difference between this and GDP Per Capita

Next looked at contingent size vs. total points ggplot(data = winter_olympic_study) + geom_point(aes(x=Atheletes,y=Total_Points,color=country_name)) +

The Fantasy Football market has evolved into a thriving multi-billion-dollar industry, captivating millions of fans worldwide. As of 2023, the market size is estimated to be valued at over $8 billion, reflecting a consistent growth trajectory fueled by the increasing popularity of American football and the advanceme

The dataset is aimed to gear up for a new season of fantasy epl football. Fantasy EPL is one the most widely played fantasy sports league in the world.

The size of the Fantasy Sports market was valued at USD XXX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 13.83% during the forecast period.Fantasy sports is a game where participants put together virtual teams consisting of real players of a professional sport. Such teams compete based on the statistical performance of those players in real games. The performance translates into points, which are compiled and added up based on the roster selected by each fantasy team's manager.The fantasy sport market has seen significant growth over the last few years due to various factors: rising internet penetration, growth of mobile gaming, as well as popularity of sports leagues all around the world. Fantasy sports platforms offer the best opportunity for fans who would like to engage and be more interested in a sport while testing their skills in competing with other fans.The market is dominated by a few major players, but increasing numbers of startups are getting into the game, introducing innovative features and targeting niche sports and demographics. In this context, the fantasy sports platforms are including artificial intelligence and machine learning to ensure personalized recommendations, predictive analytics, and more enhanced user experiences as technology advances further. Recent developments include: March 2023: DraftKings Inc. announced plans to open its renowned online sportsbook, subject to licensing and regulatory approval in Massachusetts. Massachusetts will be the 21st state in the union to provide an online sportsbook by Boston-based DraftKings. In addition to giving Massachusetts residents access to several bet types, such as same-game parlays, player props, unique odds, boost choices, and more, DraftKings will also offer clients in the state attractive and exclusive bonuses., January 2023: The fantasy gaming company Fantasy Akhada announced intentions to sell a significant stake to GMR Sports, a GMR Group affiliate, for an estimated USD 160-175 million (INR 1,300-1,400 Crore). The transaction is anticipated to happen in stages, with GMR completing off in the following rounds and displacing some early investors., May 2022: Swedish website Fotbollskanalen received FSport'sflagship fantasy sports product from the gaming and media company with its headquarters in Helsingborg. Through a partnership with TV4, a television network, FSportwill provides the Football Channel with its FSportFree product and associated daily fantasy sports platform. By their agreement, TV4 will advertise the games on the website and social media platforms under a new customary fantasy sports brand and allow users to participate in free-to-play games.. Key drivers for this market are: Increasing Sports Fan Engagement, Technological Advancements might Drive the Market Growth. Potential restraints include: Low Awareness and Regulatory Framework, Competition from Traditional Sports Betting. Notable trends are: Increasing Sports Fan Engagement may Drive the Market Growth.

Sports Data Analytics Service Market Outlook

The global sports data analytics service market size was valued at approximately $2.3 billion in 2023 and is projected to reach around $6.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.6% during the forecast period. This robust growth is primarily driven by increased investments in sports technology, the rising importance of data-driven decision-making in sports, and the growing adoption of advanced analytics to enhance player performance and fan engagement.

The surge in the adoption of sports data analytics is attributed to the increasing competitive nature of sports, where teams and individual athletes are leveraging data to gain a strategic edge. Data analytics provides insights into player performance, injury risks, and optimal training regimens, which can significantly impact the outcomes of games and overall team performance. This, coupled with the rising investments in sports technology, is propelling the market growth. Additionally, the growing popularity of fantasy sports and sports betting has further fueled the demand for real-time data analytics to make informed decisions.

Another significant growth factor is the rising focus on enhancing fan engagement and experience. Sports organizations are increasingly using data analytics to understand fan preferences, behavior, and sentiment. This information is crucial for tailoring marketing strategies, improving fan interactions, and ultimately increasing revenue from ticket sales, merchandise, and digital platforms. The integration of advanced technologies, such as artificial intelligence (AI) and machine learning (ML), is also enabling more sophisticated data analysis, driving further growth in the market.

Performance Analytics plays a crucial role in the sports data analytics service market, offering teams and athletes the ability to delve deeper into their performance metrics. By leveraging performance analytics, sports organizations can track and analyze various aspects of athletic performance, from speed and agility to endurance and skill execution. This data-driven approach not only aids in identifying areas for improvement but also helps in crafting tailored training programs that enhance overall performance. The integration of performance analytics into sports strategies allows for a more comprehensive understanding of both individual and team dynamics, ultimately leading to more informed decision-making and competitive advantages on the field.

Moreover, the healthcare and fitness tracking aspects of sports data analytics are gaining traction. With a growing emphasis on athlete health and well-being, sports teams are using data analytics to monitor players' physical conditions, predict injuries, and design personalized training programs. This proactive approach not only enhances performance but also extends players' careers and reduces healthcare costs. The increasing availability of wearable devices and IoT sensors is further supporting the collection and analysis of health-related data.

Regionally, North America is expected to dominate the sports data analytics service market, driven by the presence of major sports leagues, high technological adoption, and substantial investments in sports analytics. Europe is also anticipated to witness significant growth, supported by the increasing popularity of sports analytics among football clubs and other sports organizations. The Asia Pacific region is expected to emerge as a lucrative market due to the growing sports industry and rising investments in sports technology in countries like China, India, and Japan.

The rise of Fantasy Sports Service has significantly contributed to the growing demand for sports data analytics. Fantasy sports enthusiasts rely heavily on real-time data and analytics to make informed decisions about player selections and game strategies. This burgeoning interest in fantasy sports has prompted sports organizations and analytics firms to develop more sophisticated data solutions that cater to the unique needs of fantasy sports players. By providing detailed player statistics, performance forecasts, and injury updates, fantasy sports services enhance the user experience and engagement, driving further growth in the sports data analytics market. The intersection of fantasy sports and data analytics continues to open new avenues for innovation and fan in

Comprehensive financial and analytical metrics for Fantasy, including key performance indicators, market data, and ecosystem analytics.

The Sports Data API Service market is experiencing robust growth, driven by the increasing popularity of sports betting, fantasy sports, and the broader digitization of the sports industry. The market's expansion is fueled by several key factors. Firstly, the rise of online and mobile sports betting necessitates real-time, accurate data feeds, creating a significant demand for reliable Sports Data APIs. Secondly, the growth of fantasy sports platforms relies heavily on comprehensive and timely statistical data, further driving market demand. Thirdly, advancements in data analytics and machine learning are allowing sports organizations and media companies to leverage data for enhanced fan engagement, performance analysis, and strategic decision-making. This creates opportunities for API providers to offer advanced data processing and analytical capabilities alongside raw data feeds. While challenges such as data security and regulatory compliance exist, the overall market outlook remains positive. The increasing sophistication of data analysis tools and the evolving needs of the sports industry suggest a strong trajectory for growth in the coming years. We estimate the market size to be $1.5 billion in 2025, with a Compound Annual Growth Rate (CAGR) of 15% indicating a projected value of approximately $3.5 billion by 2033. This estimation is based on current market trends, growth rates observed in related technology sectors, and the ongoing expansion of the sports betting and fantasy sports industries. Key players like Sportradar, Genius Sports, and Stats Perform are consolidating their positions through strategic partnerships and technological advancements, while newer entrants are focusing on niche markets like esports data and specialized analytical services. The regional distribution of the market is expected to reflect the varying levels of digitalization and sports betting regulatory landscapes across different geographical regions. The competitive landscape is characterized by a mix of established players and emerging innovative companies. Existing players are leveraging their extensive data networks and partnerships to maintain their market share. However, newer companies are focusing on innovative data products and specialized services to carve out a niche for themselves. The market is also witnessing increased consolidation through mergers and acquisitions, as larger players seek to expand their service offerings and data coverage. The future of the Sports Data API market hinges on continued innovation, strategic partnerships, and the successful adaptation to evolving regulatory environments across different regions. Expansion into new data types, like wearable sensor data and social media sentiment analysis, holds significant potential for enhancing the value proposition of Sports Data APIs.

Download Free Sample
This fantasy sports market report comprises information on key market sizing data. The market segment analysis and the market forecast help vendors to take informed decisions.

The various market segmentation are: TypeFantasy soccerFantasy baseballFantasy basketballFantasy footballOther sportsGeographyNorth AmericaEuropeAPACSouth AmericaMEA For more information on market segments click here

Context

I'm a huge fan of the Final Fantasy series, so I used this data as a project to help work on my exploratory data analysis and data visualization skills.

Content

The data was scraped from Lodestone, only scraping arms (weapons) which have a level higher than 250. There are over 200,000 data points in the complete weapons database, this was only meant to be a quick project so I've limited my scraper to speed things up. The scraper script is attached at the end of my notebook for this data if anyone would like to scrape more.

Columns

name - Name of the arm category - Category that the arm falls into level - Level of the weapon damage - damage of the weapon autoAttack - damage of the weapon when auto attacking delay - time delay between auto attacks (in seconds) isUnique - is the weapon unique? 1 - yes 0 - no isTradeable - is the weapon tradeable? 1 - yes 0 - no

The rest of the columns refer to the bonuses that the weapon has for in-game attributes. e.g. a Strength column value of 518 represents a bonus of +518 for the strength attribute.