Market Insights Advertising & Media Sports

Baseball - Italy

Italy

Revenue in the Baseball market is projected to reach €3.22m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 3.09%, resulting in a projected market volume of €3.75m by 2029.
In global comparison, most revenue will be generated in the United States (€9,145.00m in 2024).
The average revenue per user (ARPU) in the Baseball market is projected to amount to €3.00 in 2024.
In the Baseball market, the number of users is expected to amount to 1.4m users by 2029.
User penetration in the Baseball market will be at 1.8% in 2024.

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Moneda

Analyst Opinion

The Baseball market in Italy is experiencing slow growth, due to various factors such as declining interest in watching and attending games, as well as a lack of new talent and promotion of the sport. Furthermore, increasing competition from other sports and lack of digital presence are also impacting the markets growth rate. However, there is still potential for growth with increasing investment in digital technologies and efforts to attract younger audiences through merchandise and ticket sales.

Customer preferences: In Italy, there has been a noticeable increase in consumer interest in alternative forms of entertainment, such as sports, in light of recent lifestyle changes and restrictions on indoor gatherings. This has translated into a growing demand for baseball, a sport that promotes physical activity and social camaraderie. As a result, there has been a rise in the popularity of local baseball clubs and amateur leagues, driven by a desire for community engagement and outdoor activities. Moreover, the incorporation of technology in baseball training and analytics has also attracted a younger generation of fans, who are drawn to the sports data-driven approach and interactive fan experiences.

Trends in the market: In Italy, the Baseball Market is witnessing a surge in online ticket sales as more fans opt for the convenience of purchasing tickets digitally. Additionally, the use of analytics in baseball is gaining momentum, with teams in Italy adopting advanced data analysis techniques to improve player performance and make strategic decisions. These trends have significant implications for industry stakeholders, as it allows for a more efficient and personalized fan experience and provides teams with valuable insights for maximizing performance. It also presents new opportunities for technology and data companies to enter the Baseball Market in Italy.

Local special circumstances: In Italy, the Baseball Market is heavily influenced by the countrys strong cultural attachment to the sport. Baseball has a long history in Italy, with the first official league being established in the late 1940s. This cultural significance has led to a strong fan base and support for the sport, making it a highly popular and lucrative market. Additionally, the geographical landscape in Italy also plays a role in the Baseball Market. With multiple professional teams located in different regions, the sport has a wide reach and attracts a diverse range of fans. Furthermore, regulatory factors, such as government support and investments, play a crucial role in the growth and development of the Baseball Market in Italy. These unique local factors differentiate the Italian Baseball Market from others, shaping its dynamics and contributing to its success.

Underlying macroeconomic factors: The growth of the Baseball Market within the Sports Market market in Italy is influenced by macroeconomic factors such as consumer confidence, government investment in sports infrastructure, and sponsorships. A strong economy with high levels of consumer spending and positive consumer sentiment can lead to increased interest and investment in sports. On the other hand, economic downturns and reduced government funding for sports can have a negative impact on the market. Additionally, a supportive regulatory environment and investment in sports facilities can promote growth by attracting top talent and hosting major events.

Methodology

Data coverage:

The data encompasses B2C and B2B revenues. Figures are based on media spending, merchandise spending, and ticket spending. All monetary figures for merchandise and tickets refer to consumer spending on goods or tickets in the respective segment, which can be online and offline.

Modeling approach / Market size:

Market sizes are determined through a combination of bottom-up and top-down approaches, building on specific predefined factors for each market segment. As a basis for evaluating markets, we use annual financial reports of the market-leading companies and industry associations, third-party studies and reports, survey results from our primary research (e.g., Consumer Insights), as well as performance factors (e.g., user penetration, price per ticket, price on sport goods). In addition, we use relevant key market indicators and data from country-specific associations, such as GDP, number of internet users, and internet consumption. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function or linear forecasting, as it fits the development of either strong growing markets or more sophistacted and saturated markets, such as soccer in Europe.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change. The impact of the COVID-19 pandemic is considered at a country-specific level. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. In some cases, the data is updated on an ad hoc basis (e.g., when new, relevant data has been released or significant changes within the market have an impact on the projected development). We also account for the different cycles of international tournaments, such as world cups or continent cups. Consumer Insights data is reweighted for representativeness.