Mumbai Cricket Association Turns to Artificial Intelligence for Coaching Under Ajinkya Naik

Mumbai's Indoor Academy Becomes a Testing Ground for AI Coaching

A batter's foot position, the path of a bat swing or a fast bowler's release point can change subtly during a net session. An experienced coach may identify many of these details, but tracking their development consistently across weeks of practice is a different task. The Mumbai Cricket Association (MCA), under president Ajinkya Naik, is now exploring whether artificial intelligence can add a more systematic layer to its coaching programme.

The association has partnered with Singapore-based sports technology company Level Up Sportslytics. The initial implementation is planned at the Sharad Pawar Indoor Cricket Academy in Mumbai's Bandra Kurla Complex, where AI will be introduced into daily net sessions. The stated objective is to assess how technology can support conventional coaching and player development.

After years of watching matches and following training environments, one distinction remains important in my notebook: improvement in practice does not automatically translate into improvement under competitive pressure. A batter may show better timing in the nets but struggle to make the same decisions against a new-ball attack. A fast bowler may maintain a consistent line during practice before fatigue affects the run-up or release point. Any assessment of this initiative must therefore look beyond the volume of information collected and examine whether that information changes training decisions and, eventually, performance.

The MCA project remains at the pilot stage. The decision to introduce AI has been announced, but no quantified evidence has been provided to show that batting, bowling or match performance has already improved.

Connecting Technology with Conventional Coaching

Mumbai occupies an important place in India's domestic cricket structure. Its competitive cricket culture, history of producing players and established coaching traditions make the association's decision significant beyond the introduction of a new software system. The project represents an attempt to make parts of player development more measurable while retaining the existing coaching structure.

The partnership with Level Up Sportslytics provides the initiative with a specialist technology partner. The company is expected to work with MCA coaches and support implementation at the Sharad Pawar Indoor Cricket Academy. The emphasis on daily net sessions is particularly relevant because technical development usually comes through repeated practice rather than a single intervention.

The role of the coach should remain central. AI-generated information can support observation, but it cannot automatically determine whether a particular technical adjustment is suitable for an individual player. A batter's natural method, the opposition's bowling, pitch conditions and match circumstances all influence shot selection. Similarly, a bowler's action must be considered alongside physical capacity, natural rhythm and long-term workload.

In my training-ground notes, I separate three questions: what was observed, why it mattered and whether the same pattern appeared in the next session. That approach could also help evaluate technology-assisted coaching. One session should not determine a player's technical assessment. If a batter's footwork changes, coaches need to establish whether the adjustment is sustained. If a fast bowler's release point becomes more consistent, they must also check whether control and physical comfort remain intact.

The strongest potential of the MCA initiative lies in connecting coaching observation with consistent information, allowing player development to be reviewed against a more structured set of measures. However, the supplied information does not specify the technical capabilities of the Level Up Sportslytics system. There is no confirmation of whether it will use video analysis, movement tracking or biometric measurements. Its precise capabilities should therefore not be assumed before technical details are disclosed.

Daily Net Sessions Will Provide the Real Test

There is a practical reason for placing daily practice at the centre of the project. Match-day performance is usually the product of preparation over several weeks. A batter's movement towards the ball, balance at the crease and shot selection against different lines develop through repeated net sessions. For a bowler, the coordination of the run-up, landing and release point is equally important.

If the technology can reliably identify changes in these areas, coaches may find it easier to understand a player's development over time. It could also create opportunities to compare earlier and more recent practice sessions. Possible assessment indicators might include consistency in shot selection, responses to particular deliveries, a bowler's line and length control, and the effect of fatigue during practice. These are potential evaluation measures; there is no confirmation that the MCA has already introduced all of them.

A structured assessment framework would be useful. Coaches could establish an initial technical record before the intervention, then review comparable sessions at regular intervals. This would help distinguish sustained progress from a temporary improvement caused by additional attention or a change in practice conditions.

The success of AI-assisted coaching will depend less on how much information a system produces than on whether that information leads to reliable training decisions. Collecting more numbers does not automatically make a player better. Incomplete or inaccurate information could encourage unnecessary technical changes and interfere with a player's natural method.

Coach education will consequently be as important as the technology itself. Experienced coaches understand that batting stances and bowling actions vary between individuals. A recommendation that benefits a young batter may be unsuitable for an established player. If the system cannot account for these differences, its practical value will be limited.

Ajinkya Naik's Institutional Modernisation Effort

Ajinkya Naik's comments place the initiative within a broader argument about adapting cricket coaching to technological change. The association's intention is to examine whether AI can become part of routine training rather than remaining a tool used only in specialist analysis.

Leadership responsibility, however, extends beyond approving a partnership. The MCA will need clear objectives, a consistent evaluation process and regular feedback from the people using the system. The association intends to collect views from coaches and players. That is a useful starting point because the practical value of the technology cannot be judged without the experience of those working with it every day.

Positive feedback alone will not establish success. Players may welcome a new system without demonstrating lasting performance improvements. Coaches may find the technology interesting while still questioning whether it saves time, improves decisions or creates an additional information burden. Those issues should be examined separately.

The experiences of players at different stages of development will also matter. Younger cricketers may be comfortable receiving technology-based feedback, while experienced players may require more time to adjust long-established habits. Evaluation should therefore account for differences in age, ability and playing style rather than treating every participant as an identical case.

First-Mover Recognition Is Different from Measurable Progress

The initiative has been described as the first adoption of AI coaching by a cricket association. That distinction requires independent verification through information about technology programmes at other cricket organisations. There may already be examples of technology-assisted analysis in different countries and institutions. Being early to adopt a particular system is also different from demonstrating technical superiority.

It is natural for an institutional announcement to emphasise innovation. Yet a cricket association's progress is ultimately measured by outcomes. Introducing technology before another organisation does not guarantee faster player development. Conventional coaching can also produce successful players when supported by strong methods and consistent practice. A fair comparison would require similar player groups, comparable training conditions and sufficient time to measure results.

For Mumbai, the meaningful achievement would be to develop a coaching model that other academies can reproduce, rather than simply retain the distinction of being an early adopter. That would require evidence connecting technology-generated information, coaching decisions and actual player improvement.

Financial sustainability is another unanswered question. No details have been supplied about the partnership's contract value, software licensing, maintenance expenses or long-term technical support. A system may be practical at an established indoor academy but difficult to introduce at smaller facilities with limited budgets. If costs remain high, the benefits could be concentrated among a small number of well-resourced institutions.

Player Data and the Responsibility of Coaches

AI-assisted coaching also raises questions about information management. If the system collects player videos, individual performance profiles or movement data, the MCA will need clear rules about who stores the information, who can access it and how long it will be retained. The current announcement does not specify the categories of information being collected. These are prospective governance questions rather than evidence of an existing breach.

Human coaching responsibility must also remain clear. A system may recommend a particular shot, but deciding whether to play it under match pressure requires cricketing judgment. Analysis of a fast bowler's action must be considered alongside physical comfort and long-term workload. Excessive practice or an unsuitable technical adjustment could increase physical risk, particularly for fast bowlers.

My travel and training notebooks have always kept workload, rest days and practice frequency as separate entries. A technology-assisted programme should not overlook those variables. Increasing practice volume might produce a short-term improvement, but progress may not last if recovery is inadequate. There is currently no confirmed information that the MCA project includes a dedicated workload-tracking system.

The Next Stage Must Be About Evidence

The most important phase of the Sharad Pawar Indoor Cricket Academy project will be the evaluation of its results. The MCA needs to understand whether the system provides reliable information, whether coaches can integrate its recommendations and whether players make meaningful adjustments during practice. Only then will it be possible to judge whether the project is a technology demonstration or the beginning of a practical change in Indian cricket coaching.

The association should publish both the strengths and limitations of the pilot. An assessment covering player development, coaching experience, training efficiency and implementation costs would offer a useful reference for other cricket organisations. It would also prevent the announcement of a technology partnership from being mistaken for proof of sporting transformation.

The question to follow is straightforward: is AI helping coaches make better decisions, or is it simply presenting familiar training observations in a new statistical format? The answer will determine the real value of the MCA initiative under Ajinkya Naik. The technology has potential, but the final judgment must come from the quality of coaching and the performances produced on the field.