Empty Cells in East African Women's Athletics: When the Fastest Runners Are Never Recorded

Inside a nine-dimension analytical framework built for athletics, there is a table with more than forty cells. I opened it one morning in Nairobi, and every cell was empty. No athlete names. No marks. No wind readings, no venue altitude, no track data. Nine analytical dimensions — from performance, athlete condition, qualification structure and national landscape to rules and anti-doping — all returned the same single sentence: insufficient information, cannot assess.

What made me pause was not the emptiness itself. What made me pause was the system's response. When data is missing, the framework does not collapse. It automatically stamps each cell "cannot assess," then quietly moves on. No one asks why the data does not exist. No one raises the question of how an athlete can be entirely absent from the data table yet still present on the track.

I have looked at tables like this for years. And I have come to understand one thing: an empty cell is not a sign of neutrality. An empty cell is the trace of a decision — a decision not to record.

Why an analysis framework demands so much data

The nine-dimension framework exists for one purpose: to turn a sports article into a verifiable test. It demands the competition name, the discipline, the exact mark with its wind reading, the athlete's date of birth, a multi-season personal-best series, the qualification system, the entry list, and the injury history. Without them, every conclusion becomes guesswork.

That is a sound methodological principle. But it raises a question few in the industry want to answer: what happens to the athletes no one records numbers for?

In Kenya, where I live and work, I am used to watching women's athletics meets where organisers publish no wind readings, record no split times, and sometimes do not even distribute a full start list. An athlete can break her personal best on a track in Eldoret, and three months later, when I go looking for that mark, it exists nowhere. She still ran. There was simply no one sitting there to write it down.

Layer one: competitive performance

To assess a performance, the framework needs to know where it stands against the world record, continental record, national record and qualifying standard. It also needs the wind reading. Under World Athletics rules, a sprint mark is only ratified when wind speed does not exceed 2.0 metres per second. A 2.3 m/s gust can turn a mid-tier athlete into a record-holder on paper, yet disqualify her from the official list.

Without wind data, venue altitude or shoe specification, every comparison is meaningless. And here is the deepest irony. At major Western meets, wind is measured to a tenth, every frame is replayed to count an athlete's stride pattern, landing angles are analysed. At the East African women's meets I follow, I have sometimes stood at the edge of the track with my own stopwatch, just to know who crossed the line first.

Layer two: athlete condition

The framework wants to build a multi-year progression curve and match it against the event-specific peak window — sprinters usually peak between 24 and 29, while middle and long-distance runners peak later. It also wants to examine the gap between personal best and current-season form, because an abnormal one-year jump is a signal warranting investigation.

For most African women athletes, that data series does not exist. I can name middle-distance girls in Iten whose exact birth dates no one has kept, let alone their year-by-year marks. When injury history goes unrecorded, a withdrawal stretching across two consecutive seasons — the framework's highest-risk flag — disappears from every report. It becomes a silence, not a warning.

Layer three: competition structure and qualification

The framework distinguishes tiers clearly. The Olympics are tier one. World Championships and Diamond League are tier two. Continental meets and national trials rank lower. It also stresses the dual qualification channel: hit the entry standard, or accumulate World Ranking points.

Notably, the American trials model — one race decides everything, so even a world champion can miss the Olympic team after one bad day — is a brutal structural risk. African athletes rarely face it. That is hardly a protection. It is because many national trials here are not organised transparently enough to become a definable competition.

Meanwhile, the rule of a maximum three athletes per country per event creates fierce competition in deep nations like Jamaica and the United States, where a fourth-place finisher is sometimes faster than another country's medallist but still stays home. This is a structural risk the framework wants to assess — but assessing it requires knowing the country, the event and the entry list.

Layer four: rules and anti-doping

The framework issues a warning I consider the single most important line in the whole document: the absence of doping data must not be read as "no doping risk." It is merely "not assessed."

I agree with that principle, but I want to push it one step further. In athletics, if an athlete is not in a regularly tested pool, if her marks are not stored for longitudinal biological-passport comparison, then whether she is clean or not is nearly impossible to prove in either direction. She cannot be convicted, and she cannot be cleared. She simply does not exist on the table.

Layer five: national landscape and training systems

The framework wants to map the sport's power structure: Jamaica and the United States dominate sprints; Kenya and Ethiopia dominate distance; Europe is strong in throws; China is strong in race walking and women's throws, with names like Su Bingtian and Gong Lijiao having reshaped Asia's limits in events once owned by other powers. The framework also wants to detect generational transition through the age structure of the leading group.

Kenya produces women's champions at 800m, 1,500m, 3,000m steeplechase and the marathon. But if you try to reconstruct one of their career curves from public data, you quickly hit large gaps: missing birth years, missing season-by-season marks, missing even the reasons they retired.

When I look at the leading group of East African women's 3,000m steeplechase, I do not see a data table. I see a generation of young women from the same few villages, running the same dirt roads, raised inside the same high-altitude training system above 2,000 metres, vanishing from the spotlight after two seasons with no one leaving a note on whether they left because of injury, childbirth, money or marriage.

The counterintuitive angle

This is where I break with false neutrality. A framework that declares "insufficient information, cannot assess" sounds scientific and honest. And it is honest in method. But it is also doing something else it does not say: it turns silence into a normal state.

When an empty cell is labelled "not assessed" rather than "abandoned," the entire sports industry is released from responsibility. No one has to apologise for the lack of wind data at a women's meet in Kisumu. No one has to explain why a 19-year-old broke her personal best at a competition no international broadcaster covered, and four years later no one remembers her name.

I once said East Africa does not lack women's football talent; it lacks record-keepers. The same holds for athletics, with one difference: athletics is the sport East Africa has dominated globally. So we live inside a vivid paradox — the fastest runners on the planet are among the least documented in detailed data.

And that nine-dimension framework, however well-intentioned, inadvertently mirrors the sport's power structure. It demands a kind of data only adequately funded, well-staffed, monitoring-obsessed systems produce. Those with data get deep analysis. Those without are filed under "cannot assess" — an organised silence.

I do not go looking for a level playing field. I draw my own lines. For years now, I have started recording what I witness from the stands and trackside: finishing times from my own hand, weather conditions, coaches' names, village names. Those notes are rough, uncertified, and will never enter any record book. But they exist. A notebook that exists is better than a record that has been forgotten, because in many cases a record only truly exists when someone writes it down.

And the framework itself quietly concedes something: it cannot distinguish between "no risk" and "no data to assess risk." Repeated long enough, that confusion becomes official truth. A generation of women athletes may be clean or may not — but they will be remembered as a set of empty cells rather than recorded marks.

Conclusion

The empty table I opened that morning ultimately carried more information than I expected. It did not tell me who ran how fast. But it told me precisely who the system left behind, and how.

When competitions stop, I see the invisible tacticians begin to speak. Women who write their own tactical notebooks, coaches without data-analyst assistants, athletes with no one recording their marks. They are not silent. No one has simply held a microphone in front of them yet.

If data is the language of power in modern sport, then who gets recorded is the next political question of athletics. And perhaps, before demanding ever more sophisticated analytical tables, we should start with something simpler: pick up a pen and write down the marks slowly disappearing from the track.