The 2:09:56 Marathon and the Unsubtracted 4% Dividend in Athletics Records

On October 13, 2026, in Chicago, Ruth Chepngetich crossed the line in 2 hours 09 minutes 56 seconds. She became the first woman to run a marathon under 2:10. When the split sheet for that race was published, I did not look at the final number. I looked at the distance between that number and the limit I had once believed was untouchable. The previous women's marathon record was 2:11:53 by Tigist Assefa, set in Berlin in 2026. Before that, 2:14:04 by Brigid Kosgei in Chicago in 2026. And before that, 2:15:25 by Paula Radcliffe in London in 2026 — a number that sat still for sixteen years. Sixteen years for the first 68 seconds. Then five years for roughly five and a half minutes more. If someone handed me these two sequences without further comment, I would not ask which athlete ran. I would ask what changed in the equipment. I have followed road and track athletics for more than two decades, from my years writing for Runner's World to the period when I worked as a data advisor for a football club in Hai Phong. The day football stopped, I began counting running strides again. My counting method is no different from the way I once counted PPDA for a young midfielder: break the final number into its components, then test each component one by one. In athletics, the final number is the result. The components are: physiological capacity, the equipment dividend, the conditions dividend — course, wind, altitude, pacemakers — and random noise. Four parts. The current record table shows only the sum of all four. In January 2026, World Athletics issued regulations on competition shoes. Road shoes were capped at a sole thickness of roughly 40mm, allowed only one carbon plate or an equivalent rigid plate, and had to be available at public retail for at least four months before use in official competition. It was the first time in the history of the sport that the governing body acknowledged in writing that equipment had become a variable requiring management. But acknowledging a variable is not the same as subtracting it from the result. To this day, no official record table has published two parallel columns: the raw result and the equipment-adjusted result. That is the gap I want to address here. In 2026, a research group at the University of Colorado published measurements of oxygen cost while running in shoes with a carbon plate. The group recorded an improvement in running economy of roughly 4% compared with traditional shoes. That is why the first generation of that shoe was named "4%." Four percent sounds small. Put it on the marathon distance. For an athlete running 2:15, 4% equals roughly 5 minutes 24 seconds. For a 2:30 runner, the dividend is about 6 minutes. Later studies suggest that at real race intensity the improvement falls between 2.8% and 3.5% rather than exactly 4%. But even at the lower bound, the dividend sits at three to five minutes across the full distance. The equipment dividend, at 3 to 4% of running economy, mathematically already covers most of the drop in the women's marathon record since 2026. That is the crux. I am not saying Chepngetich did not run fast. I am saying that her speed, measured by the clock, blends two different things: the capacity of the body and the capacity of the sole. And the current record table displays only their sum. This is where my method differs from the usual reading. When a record falls, most spectators compare one athlete with another. I compare two equipment ecosystems with each other. Radcliffe in 2026 ran in a shoe whose sole had no high-performance carbon plate and no ultra-light responsive foam. Kosgei in 2026, Assefa in 2026 and Chepngetich in 2026 ran in shoes from an entirely different generation. Four women, four elite physiological machines — but only half of them had access to the latest technology at the moment they ran. So when someone asks me who the greatest women's marathoner is, I answer with a different question: what exactly are we comparing? Data is a mirror. Most of the market looks into it and sees only itself. The same principle applies to sprint and middle-distance events, where the super-spike revolution arrived roughly two years later than on the roads. From 2026, a wave of records at 400m, 800m, 1500m and 5000m fell within a very short cycle. Some analysts called it a golden generation. I call it an equipment change misread as a generational change. One detail deserves attention: in the 100m, World Athletics does not ratify a record if the tailwind exceeds 2.0 metres per second. That rule has existed for a long time, and it exists for a very data-driven reason: wind is an external variable that does not belong to the athlete. But the same organisation, to this day, has no equivalent mechanism for shoes. A 2.1 m/s gust is struck from the table. A propulsion plate is not. On longer distances, terrain and altitude create a similar asymmetry. Berlin and Chicago are famously flat and designed for fast times. The Boston Marathon has a net downhill and is a point-to-point course, so it is not eligible for world records despite many high-quality performances. Records set at altitude — such as the sprint marks in Mexico City in 2026 — are also often flagged separately by analysts, because thinner air aids speed. In other words, the sport already has a toolkit for flagging external variables: wind, altitude, terrain. What is missing is simply extending that toolkit to the equipment variable. Split data is more trustworthy than the final result. A well-paced record — with 5km splits varying within a narrow band and a second half equal to or faster than the first — is a structured record. It shows the athlete controlled the rhythm and did not collapse at the end. A poorly paced record — an unusually fast first half, a marked second-half fade — is usually the product of an exceptionally well-arranged pace group, or a one-off surge that cannot be repeated. Without split data, every comparison becomes a comparison of the final number alone, which is the most noise-contaminated thing in the whole system. This is why I always check three layers before trusting a record: the split layer, the conditions layer and the equipment layer. If one is missing, I write two words in my own table — "insufficient data" — and I draw no conclusion. The day football stopped, I began counting running strides again. That method applies equally to a shot on goal and a long stride. One more category needs to be stated clearly: performances that are not ratified. In October 2026, in Vienna, Eliud Kipchoge completed a marathon in 1 hour 59 minutes 40 seconds. That mark was not entered into the world record table, because it was not an open race and rotating pacemakers joined mid-course. Earlier, in 2026, he also ran 2:00:25 in a closed event in Monza, likewise unratified. I cite both numbers not to diminish the achievement. I cite them to distinguish two kinds of data: competition data and exhibition data. Both have value, but they must not be blended into the same table. Now comes the part where I argue against myself. If carbon shoes gave everyone the same dividend, the gap between athletes would stay the same or even narrow, since all would benefit equally. But the observed pattern is the opposite: the leading group has pulled further away. That means my "subtract 4%" hypothesis is too crude. The equipment dividend is not added uniformly. It interacts with ability. An athlete with a strong physiological base, good running mechanics and the capacity to hold a steady rhythm extracts more from the same shoe than a weaker runner. One tool, two different multipliers. So the correct subtraction is not minus 4% for everyone. The correct subtraction is a function depending on athlete, distance and conditions. And today we lack enough public data to build that function. A dividend that holds at the distance level does not hold at the individual level. That is the conclusion I reached after re-examining my own method. I once made a similar error in another field. In 2026, when the pandemic halted every football league, I spent four months reviewing data from five V.League seasons and three major European leagues — roughly 2,300 matches — to build a pressure index combining PPDA, defensive distance and pressing speed. The result showed that teams with an average PPDA below 8.5 collected 1.8 points per match, clearly above the rest. That number was statistically sound at the collective level. But when I tried to apply it to individual matches, it failed repeatedly. An index that holds at the aggregate level does not hold at the individual level. That lesson applies directly to the carbon shoe story. There is another point rarely mentioned: the equipment dividend is distributed unevenly across countries. An athlete in East Africa or Europe may access the latest prototype through a sponsorship team. An athlete in Southeast Asia often has to wait for the commercial release, and sometimes runs in shoes two to three years older. An equipment gap becomes a performance gap, which is then read as an ability gap. At the Hai Phong club in 2026, I once brought the PPDA figure of 6.8 belonging to a young midfielder named Vu Minh Hieu into the meeting room and asked coach Truong Viet Hoang to give him a chance. In the match against Ha Noi FC on V.League round 17, he recovered the ball 14 times, provided one assist, and Hai Phong won 2-1. What I learned was not that data is always right. What I learned was that a measuring tool is not neutral, but it is fairer than reputation — provided you know what it is measuring, and in which ecosystem. Hai Phong taught me: the star is not on the shirt, it is in the index. But Hai Phong also taught me that an index borrowed from elsewhere, applied to a different ecosystem, will lie. So I do not conclude that Chepngetich does not deserve her record. She does. She ran the fastest time under the conditions she had. I only conclude that the record table we are reading is missing a column. The missing data here is very specific, and I list it so anyone who wants to verify can verify: sole thickness and foam type for every shoe used in every record; complete 5km split data; wind, temperature and humidity at the start; and each athlete's access to prototypes in the six months before the race. When those four data groups are available, we can build a genuinely comparable ranking. Until then, every cross-era comparison — including the most emotionally charged ones — is merely a comparison of the sum of two untangled variables. A season is a confession of tactics. A record is a confession of equipment. The next cycle will answer this question: when World Athletics reviews its shoe regulations, will it add an "adjusted" column, or will it keep leaving the subtraction to the audience's imagination? The ball rolls in only one direction, but data sees in all directions. Athletics is the same. The difference is that a stride leaves no mark on grass — it leaves a mark on the clock. And the clock, so far, has not been programmed to subtract the dividend the sole delivers. People call me a data monk. A monk needs no cathedral — only the truth. But the truth, here, is missing a column.