SwimSwam's 2028 Recruiting Database: When the Spreadsheet Steps Into the Youth Pool

On a July afternoon in 2026, sitting in a West End cafe in Brisbane, I reopened my own recruiting tracker. On screen was a fourteen-year-old's name, with seven columns of numbers: 50 free, 100 free, 200 free, 100 fly, 200 IM, twelve-month improvement, and a final column reading "committed". Seven columns for a child who had not yet finished middle school. Around the same time, SwimSwam published its 2028 Recruiting Database, built and introduced by Anne Lepesant, one of the site's lead writers.

I have covered swimming for five years as a data specialist, working as a sports betting analyst in Australia. When a new statistical product appears in the sport I live alongside, I do not rush to praise or dismiss. The first task is to determine three things: what the product measures, what it hides, and who actually reads it.

Numbers have no gender. But every table has a person behind it deciding which columns are shown and which are buried. A public database for fourteen-year-old athletes is not a small matter, and it should not be read as a simple ranking.

The system the spreadsheet serves

American high school swimming operates in an ecosystem outsiders rarely grasp. Each NCAA Division I university may award only a capped number of scholarship equivalents for swimming and diving, and that number is set by association rules. Head coaches must fill rosters within that frame, which means deciding very early who deserves which slice of the budget.

The recruiting timeline follows a familiar sequence. Athletes are spotted by programs from ninth or tenth grade. Roughly two years before graduation, the two sides reach a verbal commitment. In November of senior year, the athlete signs a formal commitment. The "class of 2028" are athletes who will graduate high school in 2028 - currently mostly fourteen or fifteen years old.

Anne Lepesant has run SwimSwam's commitment trackers for years, and she is one of the few people in the industry with a full picture of American swim recruiting at a granular level. Packaging that data into a database organised by graduating class is an organisational step forward. Readers can now filter by class, by school, by time, rather than reading piece by piece.

But this is a product introduction for a product. That should be stated plainly. The database serves SwimSwam's readership, and SwimSwam lives on traffic from exactly the audience interested in recruiting. A fuller tracking tool draws people back to check more often. That does not make the data wrong, but it shapes how we read it.

Seven columns and what they cost

Swimming is a sport of absolute time. Football has dozens of derived metrics, and I have spent a career dissecting them. Swimming is different. Whether an athlete swims the 100 free in 49 seconds or 52 is a fact beyond dispute. That is the sport's strength and its weakness.

Absolute time says very little about the future. A child may hit 52 seconds at fourteen because they matured early, their body nearly finished. Another child hits 54 seconds, but their frame is still developing, and by seventeen they will surpass the first. The database records the number at the moment of measurement. The table does not know which child will keep improving for two more years.

That is where recruiting data differs fundamentally from elite competition data. At the elite level, we measure the performance of a finished product. At the recruiting level, we measure a process still underway, and we treat the measurement as though it were a conclusion. I do not trust emotion. I trust a data series longer than your emotion. But I also know which series is long enough, and a fourteen-year-old's series is not.

The "twelve-month improvement" column is the most important and the most misleading. An athlete dropping two seconds in a year sounds impressive. But if those two seconds came from fixing a turn error, it predicts nothing about dropping another two. If they came from physical change during puberty, that is a number that happens once in a lifetime. The table does not distinguish the two.

From Transfermarkt to the high school pool

In football, I worked for years with valuation platforms. Transfermarkt assigns a number to each player, and that number operates as a psychological anchor for the market. Player valuation is not a calculation, it is a war between belief and the spreadsheet. The swim recruiting database is following a similar trajectory, with one difference: in football, the people being valued are adult professionals. In high school swimming, they are minors.

When a table is made public, it does not merely describe reality. It participates in creating it. An athlete near the top of the class of 2028 list receives more invitations, more meetings with coaches, more chances to race at major meets. Those opportunities improve their times. The loop closes, and the table proves itself.

The economics of a scholarship slot

Look at the real numbers. In Division I, a women's swim team may carry more than thirty athletes, but scholarships are split under association rules. Very few athletes receive full scholarships. Most receive partial awards, and a significant number compete as walk-ons or on academic scholarships alone. The recruiting database is essentially a tool for families to position their child in a market that is opaque about price.

The parents of a fourteen-year-old open the table and compare. The neighbour's child hits 51 seconds, mine hits 53. What does that two-second gap mean? It may mean the difference between a full scholarship and a partial one at a mid-tier school, or between two entirely different tiers of programs. That conversion is nearly impossible, yet families perform it every week.

The economics go beyond scholarships: travel to national meets, private coaching fees, year-round training costs. A family invests in a child for four years hoping to trade it for a scholarship. The database helps them estimate the odds. It may also push them into decisions based on a column the child has not had time to prove.

The paradox of a public table

The paradox sits here: a database created to make recruiting transparent may undermine the very athletes it aims to serve.

Head coaches understand this better than anyone. Some deliberately avoid commenting on uncommitted athletes, because any comment inflates value and strains relations with families. A public table makes that silence harder to keep. Once a name is ranked at the top of a class, staying quiet reads as insufficient interest.

And there is a group the database does not serve well: late developers, athletes from states that swim media rarely covers, and those who switched into swimming from another sport at fifteen. They are absent from the table because the table has not recorded them, and being absent makes them harder to discover. The table does not create that bias, but it amplifies a bias that already exists.

I live between two markets, Vietnam and Australia, and I have learned not to attribute every difference to culture. But one comparison on equal footing is worth making. Talent networks in developing countries both find geniuses and produce expensive gambles and broken families. A child is taken from home at fourteen to train at a major centre. When it works, we call it vision. When it collapses, we call it fate. The table records none of that story.

The limits of the data

Every piece I write includes this section, and this one is no exception.

The zone the data can confirm is fairly small. We know the exact time swum at a specific meet, on a specific date, in a pool of standard length. We know which athlete signed with which school and when. Those are certain facts.

The ambiguous zone is far larger. Improvement rate, growth potential, adaptability to a college environment, capacity to handle Division I training loads - all sit where the table offers only weak signals.

The zone that relies on feel is the one I know best: five a.m. practices, family pressure, a fourteen-year-old deciding whether to leave home or stay. We lack the tools to measure that in milliseconds. Emotion is data too, but we do not yet have the right instrument. Kazan was the day I learned that a 99 percent probability can still die on the betting table, and that lesson applies to every table, including one that tracks a fourteen-year-old.

Signals for the next cycle

Over the next three months, I will track one quiet indicator in this database: the rate at which athletes switch committed schools after a public commitment. That number says more than any time-based ranking. If the switch rate rises, families are using the table to renegotiate, and recruiting has become a real, moving market. If it falls, decisions are being made earlier and more rigidly - which, all things considered, may not benefit the fourteen-year-old sitting inside those seven columns.

SwimSwam's 2028 Recruiting Database is a good tool. It gathers scattered information into one readable place, and it does so with impressive precision by Anne Lepesant. I will use it. I only hope those who use it remember that behind seven columns sits a child who has no say in which column defines them.