The Data Gap on East Africa's Women's Running Tracks

The Data Gap on East Africa's Women's Running Tracks In the summer of 2026, in a meeting room in Nairobi, I received a stack of documents less than twenty pages thick. That was all that remained after three months of competition in a national-level women's athletics meet: forty-eight athletes, twelve events, and not a single line of split-time data. The woman in charge of the stopwatch told me she had no time to record "that sort of thing." I nodded and folded the folder shut. That same week, a colleague sent me a technical analysis of the meet. The analysis ran nine pages, covering every heading from current form to competition structure, but in every content box sat the same single line: insufficient information. Nine pages of paper, and not one data point. I read it twice, then realized the analysis was honest in a frightening way. It did not invent conclusions. It simply said aloud what an entire system was quietly saying: we do not record enough to understand. After thirty years in this profession, I have learned that sports journalism does not lack news. It lacks numbers that are recorded properly. When a dataset is empty, what fills the void is usually prejudice. And prejudice, like anything else that runs fast, wins in the final sprint. A history written in diluted ink Women's athletics has a history of late record-keeping. In many events, women had to wait decades before competing officially at the highest level. The women's marathon only became an Olympic event in 2026, in Los Angeles. The women's 3000m steeplechase debuted at the Beijing 2026 Olympics. The women's 5000m only appeared at the Olympics from 2026. At every such milestone, a whole generation of female athletes had already run, trained, and left the track before anyone bothered to build a results table for them. In East Africa, the story is more complicated. Kenya and Ethiopia are known worldwide as distance-running powers, but that reputation was largely built on male images. Names like Eliud Kipchoge or Kenenisa Bekele are cited as global icons. Meanwhile, the female athletes of the same generation, who run just as fast in their events, usually appear in results as a single name and a single mark: no profile, no split data, no injury history. Faith Kipyegon had to break the 1500m world record before the media gave her the attention befitting an icon. Before that, her achievements were real, but her story was blurred. This gap is not Kenya's alone. It is a global pattern: sports data systems are built first for the events with the most money, the most viewers, and the most sponsors. Wherever men occupy most broadcast hours, there are also more measuring devices, more cameras, more analysts. Women inherit what is left. I remember 2026, when male colleagues in Nairobi still dismissed data analysis in women's football as pointless. I reviewed the national women's league myself and found a nineteen-year-old midfielder with the highest passing accuracy in the competition. No one called her up. I wrote about her, was mocked, and three months later she was called up and scored on her debut. The small girl with the old boots never appeared in a report, but I saw her in every number. That was the first time I understood that data, recorded properly, can pull a person out of the silence. Where the gaps lie When I speak of data gaps, I do not mean some vague shortage. I mean specific, measurable holes. The most visible hole is split-time data. In running events, the time through each lap or segment is the backbone of any tactical analysis. From it, you know who started fast and faded, who saved energy for the final four hundred meters, who sprinted too early. For men at major meets, this data is nearly default. For women at many regional meets, it barely exists. Without it, every commentary is a guess dressed in professional clothing. Another hole lies in injury data. An eighteen-year-old female athlete with two hamstring strains in a season needs a different training path than one who has never been injured. But if no one records the injuries, a national team coach will call her into a competition without knowing that her legs are carrying accumulated stress. I have seen this happen, many times, and it usually ends in a worse injury, the kind that can end a career at twenty-two. Beside that is physiological and training-environment data. East Africa has a natural altitude advantage that many places must simulate in laboratories. But rural training centers for women often lack devices to measure blood oxygen, lack training-load logs, lack menstrual-cycle tracking, a factor that directly affects performance and that many men's teams in Europe have studied seriously for years. The same body, the same track, but one side is measured and the other is guessed. Then there is administrative data. Contracts, prize money, sponsorship terms. In men's events, a representation contract can be published down to the last figure. In women's events, most deals happen in silence, making it impossible to judge whether an athlete is being paid fairly. A female distance runner may receive a few thousand dollars for an appearance, while a peer in a men's event receives ten times that, and no dataset lets the public see the gap. The most overlooked hole is competition-system data. The ranking systems that earn places at major championships rely on points accumulated across many meets. To accumulate points, an athlete must compete at recognized meets, and the results there must be recorded to standard. Where there are too few results officials and too few qualified referees, a female athlete can win a meet whose result is never recognized by the international system. She wins, but the points do not come. She runs fast, but the door stays shut. On the equipment side, the gap is also clear. Carbon-plate spiked shoes, marketed as a revolution in running, were first designed and tested for men. Studies of the biomechanics of the female foot have only gained attention in recent years. This means that for many years, a female athlete had to run on equipment made for a body unlike her own, and no one measured the consequences, because the data on it did not exist either. Looking even lower, at school level, the gap is larger still. School athletics meets are where talent is discovered in many places, but results are often not preserved. A fifteen-year-old girl who runs fastest in her school may never know that her mark was enough to catch a national coach's eye. When there is no data, talent discovery depends on luck, and luck is not fair. Why the gap is dangerous The danger of the data gap is that it is not neutrally empty. It is filled by ready-made stories, usually the easiest to tell rather than the truest. When there is no split data, people explain a female athlete's victory by "instinct." When there is no injury data, people call her decline a "lack of spirit." When there is no administrative data, people assume she is being treated fairly. Each time, a data hole becomes a prejudice, and that prejudice is passed from one article to the next, until it becomes something everyone "knows" without anyone verifying. I once stood at the 2026 World Cup and saw only one thing: prejudice. Then I counted every pass to erase it. I tell this story not to talk about myself, but to point to a mechanism. Prejudice does not win by argument. It wins by vagueness. Where the numbers are clear, prejudice struggles to dwell. This is especially true in developing sports nations. A female athlete running in Nairobi, in Kampala, in Addis Ababa may reach marks enough to compete in Europe, but if those marks are not recorded properly, not compared against international standards, she is invisible to scouts. Talent does not send its own signal. Data sends the signal. And here is the point I want to stress: the data gap makes us misread female athletes, and beyond that, it directly costs them opportunities. A scholarship, an invitation to an international meet, a first sponsorship deal, all pass through a door called data. When that door closes, the person stuck outside is usually the one with the least voice. I once watched a young female athlete lose her place at an international meet because the domestic organizer did not submit results on time. She had no idea it was happening. She only knew she had run fast enough, and then her name was not on the list. It was an administrative failure, but its consequence was sporting: a lost opportunity, a year of youth taken away, and no one held responsible. Even the way a women's race is organized reflects this gap. In distance events, pacemakers, the runners who lead to hold the tempo, are often allocated differently between men's and women's fields. A women's race lacking good enough pacemakers can finish with marks below the athletes' true ability, and those low marks are then used to argue that the women's event is less attractive. A closed loop: less investment leads to lower marks, lower marks lead to less investment. The industry of silence There is a paradox: the sports industry talks more and more about data, yet concentrates data ever more tightly in a small group. Major meets invest millions of dollars in tracking technology, in video-analysis systems, in sports-science departments. Meanwhile, regional women's meets still struggle with handwritten score sheets and old stopwatches. This paradox did not arise by accident. It follows a commercial logic: data follows money, and money follows wherever returns come fastest. But that logic has a flaw. The competitive value of an event does not always match its short-term commercial value. A female 3000m steeplechaser can give the sport a bigger story than any advertising contract, if that story is recorded well enough to be told. I once followed a women's training center in the Kenyan highlands. It had young middle-distance runners with real potential. But when I asked about data, they handed me a notebook with figures written in ballpoint, many smudged. There is nothing wrong with that notebook. What is wrong is that we built an entire analytics industry without leaving them a single tool. If you are a European scout, who will you sign? Someone with a full profile, split data, and an injury chart, or someone with a single best time scribbled hastily on a piece of paper? The answer is obvious. And precisely because it is obvious, it shows that the data gap is not an accident. It is a choice, however unconscious, made by an entire system. Here I must add something about the transfer market. In football, people talk endlessly about contracts, transfer fees, and release clauses. In athletics, that market exists in a different form: appearance fees, management contracts, deals with major marathons. And just as in football, small teams and athletes with little voice are often the ones raising semi-finished products for the big centers. An athlete trained in Iten or Eldoret can be signed by a foreign management company very early, on terms she is not equipped to fully read. By the time she becomes famous, most of the value already belongs to someone else. The line between silence and erasure I want to pause on a distinction I consider important. Silence and erasure are not the same. An athlete can be silent because she chooses to be, because she focuses on the track, not on noise. But being erased is different: it is when people have no way left to know about you, even if they want to. The data gap turns silence into erasure. It takes from the athlete the right to be judged fairly, the right to be compared with her own past season, the right to prove that her progress is real. Without data, an athlete cannot prove she is improving; she can only hope someone trusts their instinct about her. The year 2026 taught me that the truest star is not the fastest runner, but the one who holds herself together in silence. When the pandemic froze world sport, I called women's coaches across East Africa and found that many players had gone back to farming, and many athletes were training with equipment made from scraps of cloth. I wrote about them, alongside figures on how many had left the sport. That series did not change the world, but it forced a federation to publish a support budget for women. Sometimes a number recorded at the right moment carries more weight than a thousand appeals. What is changing Not everything is bleak. In recent years, some national athletics federations in East Africa have begun hiring data analysts, though few. A handful of regional women's meets now have electronic timing instead of hand-held stopwatches. Online performance-tracking platforms, once male-only, are gradually adding women's events. But real change does not come from technology. It comes from someone willing to sit down and keep records. I still believe that after all these years. When numbers can name names, the whole field must listen. Our problem is not a lack of tools, but a lack of people willing to record every lap, every injury, every sum of money. At sixty-one, I have learned that sport is never old; only our way of looking grows worn. I have looked over results tables for four decades, and what excites me most is not a new record, but the moment an unknown name suddenly becomes clear on a page of data, because someone bothered to record it. I think of the nine-page analysis I received, with its empty boxes full of the words "insufficient information." Some will read it and feel disappointed. I read it and feel a reminder. It reminds me that behind every empty box is a real athlete, running each morning on a dirt road, waiting for someone to record her steps. Closing thought The sports world always wants rankings. I only want to understand why they run, why they cry. And to understand that, I need honest numbers, recorded fully, not left blank because someone decided "that sort of thing" does not matter. The data gap on East Africa's women's running tracks will not fill itself. It closes only when someone decides that every step of a female athlete is worth counting, not to rank her, but so she is not erased.