SBC News Aldo Comi: Football can gain advanced AI techniques from betting experts

Aldo Comi: Football can gain advanced AI techniques from betting experts

As an industry that is always on the lookout for new technological innovations, betting has kept a close eye on Artificial Intelligence (AI) developments in recent years. 

The potential of the technology is a regular talking point among stakeholders, examining how it can benefit in commercial aspects as well as for player protection.

Aldo Comi, CEO of football analytics provider Soccerment, gives his insight on how professional football clubs can learn more from the betting industry in terms of the future of data science. 

In my view, the betting sector as a first mover in AI adoption offers valuable lessons for professional football. 

SBC News Aldo Comi: Football can gain advanced AI techniques from betting experts
Aldo Comi

What’s evident is that the predictive prowess showcased by betting agencies through their sophisticated algorithms to optimise odds and enable “arbitrage” can offer insights into how football clubs approach match strategy, player performance, and even transfer market decisions.

The betting sector, with its real-time data analysis and predictive modelling, has significantly evolved in its use of AI to forecast match outcomes, player performances, and betting patterns. Professional football can leverage these insights to enhance their game strategies, scout potential talents, and predict opponent tactics.

The skills required for predictive modelling in betting – such as machine learning, data analytics, and algorithmic decision-making – are transferable to sports data science teams. 

By hiring professionals experienced in the betting sector or collaborating with betting data providers, football clubs can gain access to these advanced analytical techniques. Training sessions and workshops can help assimilate these skills into the sports realm, adapting them to address football-specific challenges.

A breakdown of clubs that have incorporated this approach:

  1. i) Brentford: Owned by an entrepreneur from the betting industry, the club has adopted a data-driven approach, leveraging analytics to make informed decisions on player recruitment and match strategies. 
  2. ii) Brighton: Similarly, Brighton’s ownership, active in the betting sector, has facilitated the club’s use of data analytics, enhancing their strategic and player scouting capabilities. The success of the latter is particularly evident now, with so many players being transferred to Chelsea and other top clubs at very high fees and capital gains.

    While these clubs provide a blueprint, there’s ample room for development. Many clubs are yet to harness the full potential of AI and data analytics, indicating a vast untapped potential for integrating betting sector strategies.

    Barriers to cooperation and potential solutions: 
  3. i) Regulatory changes: As regulatory bodies scrutinise the relationship between betting and football more closely, there might be restrictions on the direct collaboration between clubs and betting agencies. To navigate this, clubs can ensure transparency in their operations, making clear distinctions between their sporting decisions and any associations with the betting world. 
  4. ii) Commercial challenges: The commercial interests of betting companies and football clubs may not always align. To overcome this, clear contractual agreements specifying the nature and extent of collaboration can be established, ensuring both parties benefit equally.

iii) Ethical concerns: The integration of betting insights might raise ethical questions, especially if it influences game outcomes. Clubs can address this by establishing ethical guidelines and ensuring that the primary aim remains enhancing team performance rather than commercial gain.

In conclusion, while challenges exist, the potential rewards of integrating AI expertise from the betting sector into professional football are vast. With careful planning, transparency, and ethical considerations, football clubs can harness this potential to revolutionise their strategies and operations. 

A crucial point to consider, in my perspective, is that AI’s efficacy is contingent upon receiving vast quantities of high-quality and well-structured data. In England, numerous clubs have initiated efforts to develop their own proprietary databases for strategic use. 

Conversely, in much of Europe, particularly in Southern Europe, clubs are trailing behind in this regard. This disparity could afford English clubs a significant competitive edge in the coming years.

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