Every cricket academy we speak to assumes it needs to start collecting more data. Almost none of them do. The scorebook already exists, attendance is already taken, and most coaches already have opinions about every player they see. The gap is not collection — it is that none of it is written down in a form that lets you answer a simple question six months later: is this player better than they were?
So before buying anything, here is what is genuinely worth recording each week, and roughly in what order of value.
The five things worth recording weekly
- Match output per player — runs, balls faced, dismissal type, overs bowled, runs conceded, wickets. This already exists in your scorebook; the work is getting it into one place rather than fifty loose sheets.
- Deliveries bowled per bowler per week. The single most valuable injury-prevention number in age-group cricket, and almost nobody tracks it. A spike from 60 to 140 deliveries in a week is visible weeks before a side strain.
- Training attendance. Boring, and enormously predictive. Players who quietly drop from four sessions a week to two are usually about to disengage entirely.
- A short coach rating on two or three attributes. Not fifteen. Pick the attributes that actually drive selection at your academy and score them consistently.
- Fitness testing, once a term. Not weekly. A termly benchmark on a handful of tests is enough to show a trajectory.
What to ignore, at least at first
Ball-tracking, wearables and video tagging are all genuinely useful — at a level above where most academies are. If your scorecards are still on paper and your attendance is in a WhatsApp group, buying a tracking system solves nothing. It adds a second unconnected data source to the pile.
The academies that get value from data are not the ones with the most sensors. They are the ones who wrote the same five things down every week for a year.
Why age adjustment matters more than anything else
In age-group cricket, raw averages are close to meaningless as a comparison tool. A boy who is fourteen months older than his cohort will average more runs than a technically better player who happens to have been born in August. If your selection is driven by an unadjusted averages table, you are systematically selecting for birth month.
Adjusting for age and role is not complicated, but it does require that the birth dates are recorded properly and that comparisons happen within a defined cohort. That is a data-structure problem, not an analytics problem — which is why it is worth fixing at the collection stage rather than trying to patch later.
What good looks like after one season
After a full season of consistent recording, an academy should be able to sit down with any player's parents and show three things: what their child has done, how that compares to where they were at the start of the year, and what the coaching staff want them to work on next. That conversation is worth more to retention than any facility upgrade.
None of that requires hardware. It requires the discipline of recording five things a week, and somewhere sensible to put them.