Eight Dimensions of Fighter Vetting: When the File Is Empty, 'Insufficient Data' Is the Right Answer

Last April, my inbox received a message from a fight broker I had known for years in Southeast Asia. Three lines, no greeting: "Need an urgent assessment. Fight next week. Check the injury file." Attached was a file under two hundred kilobytes.

I opened it. The first page carried a fighter's name, weight, and a record of 14-3. Everything else was blank. Date of birth blank. Number of bouts in the previous eighteen months blank. Injury history blank. A note at the bottom: "being updated". I wrote back four words: insufficient data. He called immediately, voice tight: "Just estimate it, everyone does it."

That sentence is the one I have heard most often in ten years of assessing injury risk. It is also the sentence that has pushed combat-sports analysis into a strange position: plenty of opinion, plenty of prediction, very little documentation. A fighter steps onto the scale with fourteen wins and three losses, and nobody in the room knows how swollen his left knee was two months ago.

I declined. Not because I did not want to help. I declined because in combat sports an empty file is not a clean file. It is a dark patch, and a dark patch is never neutral.

Injury data never lies; only the reader lacks patience. But data that does not exist leaves nothing to read, and at that point the only thing left is the analyst's imagination. That is the most dangerous substance in a sport where people hit each other in the head for a living.

This article is about an eight-dimension vetting framework that a small group of working professionals and I have used for years. It was built for one purpose: when information is missing, it must say so, rather than papering over the gap with a confident-sounding sentence. That sounds simple. Achieving it requires changing almost the entire way this industry tells stories.

Context: why an eight-dimension framework became necessary

Football has grown used to players with GPS files, load files, and weekly injury files. When I was working as a commentator at a Guangzhou television station, a club once asked me to review forty-seven matches of a Brazilian striker across eighteen months, cross-referenced with sensor data from training sessions. I found a small detail: his sprint output dropped roughly fifteen percent when playing on artificial turf. Six weeks later he tore a hamstring. My advice circulated through the transfer market, and from then on clubs began calling me before signing anything.

The quiet doctor of 2026 now prices transfers in risk. But that story only happened because football has a data foundation. Combat sports do not.

A professional fighter competes three to five times a year. Each bout lasts from three five-minute rounds to five five-minute rounds. Between bouts lie long gaps, and inside those gaps almost no public data is generated. Nobody publishes training load. Nobody publishes tendon ultrasound results. Nobody publishes the actual number of rest days taken after a knockout loss.

As a result, fans, bookmakers, and even fighters' own managers make decisions on a dataset thin enough to be frightening. And when data is thin, what fills the gap is always narrative. A fighter who wins three in a row is "on the rise". A fighter who loses two is "washed". Those labels are not data. They are metaphor, and metaphor predicts nothing.

The eight-dimension framework grew out of that discomfort. It divides fighter assessment into eight independent question groups, and for each group it forces the analyst to answer a second question: do I have enough information to conclude anything here. If not, the field must read "insufficient data". No blanks, no guesses, no vague sentences used as filler.

This sounds like a tedious administrative rule. Its consequence is large: it turns ignorance into information. When a file carries seven fields marked "insufficient data", the reader immediately knows that the sender is either hiding something or selling a story rather than a fact. Both possibilities are equally useful.

Axis one: technical capability and style matching

The first group is the most basic: how do these two fighters fight, and what shape emerges when one style collides with the other.

Four metrics matter most: finishing ability (what share of wins come from knockout or submission rather than a judges' decision), record quality (who did they beat, who beat them, and where those opponents sat in the rankings at the time), effective striking rate and absorbed strike rate per minute, and control of position on the ground.

These four metrics sound dry, but they tell a very concrete story. A fighter with a high output rate and a high absorbed rate is trading blood for blood. That approach works against slower opponents and collapses against opponents with good counter timing. A fighter with a high knockout rate where most knockouts arrive in round one is a fighter who wins fast or loses long. These patterns do not live in the record column. They live in the distribution of fight times.

This is where fans are routinely fooled by the aggregate number. A 20-1 record looks formidable. But if eighteen of those twenty wins came on judges' scorecards against opponents with losing records, then 20-1 is concealing a different reality: this fighter has never actually finished anyone at a high level. And when he meets an opponent who will not fold, he will have to do something he has never done.

Based on my experience tracking fights over many years, one rule holds fairly steadily: record quality matters more than record quantity, and the quality of losses matters more than the quality of wins. A fighter who lost narrowly to a world-class opponent usually has a better technical base than a fighter who won ten times against unknowns. Losses expose weaknesses. Wins tend to conceal them.

Here the framework forces me to stop. To judge record quality I need to know who the opponents were, where they ranked at the time, and what stage of their careers they were in. If the file contains only "14-3" with no opponent names, I cannot conclude anything. I can only write: insufficient data.

And that is exactly what I wrote into the April file.

Axis two: physical condition and career longevity

This is the group I care about most, and the group the industry ignores most.

Four variables: the age curve, weight-cut risk, injury wear, and camp quality.

The age curve in combat sports is not the football age curve. A fighter may peak technically at thirty-two while having lost defensive reflexes at twenty-nine. Conversely, a grappler may compete well into his late thirties because that discipline depends less on reaction speed. Age alone therefore says nothing. What is needed is age plus professional minutes plus the number of times the head has been struck.

This is the concept of mileage. Two fighters of the same age can carry very different mileage: one has fought forty rounds, the other two hundred. The second sits at an entirely different physiological stage.

Weight-cut risk is the most dangerous variable in the whole framework, and the one fans misunderstand most. Cutting weight is not an aesthetic matter. It is a controlled dehydration process used to temporarily reduce mass, followed by rehydration across the twenty-four to thirty-six hours before the fight. When that process is pushed too far, the consequences can include kidney failure, cerebral edema, or death. In 2026 a twenty-one-year-old fighter in ONE Championship died after a weight cut, and the event changed how that organisation screens urine hydration before official weigh-ins.

I once reviewed four years of weigh-in data for a single fighter. He competed in one weight class, but his out-of-competition weight sat nearly twelve kilograms above the limit. Every fight required his body to pass through a door it was never designed to pass through. Across three consecutive bouts, his round-three output fell nearly forty percent against his opening round. Nobody called that a conditioning problem. People called it "losing focus". The data said something else: his body was repaying a debt incurred twenty-four hours earlier.

Injury wear is the hardest variable to collect. In football, injuries are announced. In combat sports, injuries are concealed. A fighter with a sprained ankle three weeks out will not disclose it, because disclosure costs him the bout. The only way to read wear is indirectly, through behaviour in the cage: does he rotate to one side more than usual when evading, does he abandon his lead leg when striking, does his movement rhythm drift to one side.

That is why I always review prior footage, not to see whether he won or lost, but to see which part of his body he is protecting.

A body reader like me knows: every pain is an answer. The problem is that the question must be asked in the right place, and there must be enough frames to see the answer.

Camp quality is the most undervalued variable. A fighter training in a gym with a dedicated strength coach, a physiotherapist, and a calculated recovery schedule will follow an entirely different career trajectory from one training in a gym where the head coach also acts as manager, weight-cut supervisor, and driver. That difference does not appear in the record. It appears four years later, when the first is still competing at the top and the second has retired with a back injury.

Axis three: organisational and event landscape

The third group shifts from body to system. A fighter does not compete in a vacuum. He competes inside an organisational hierarchy with exclusive contracts and unwritten rules.

The hierarchy of professional combat sports is fairly clear: leading global organisations at the top, second-tier organisations in the middle, regional organisations below them, and local events at the base. A fighter climbs by winning at the lower tier and being invited upward. That path is not linear, and it is blocked by contracts.

Exclusive contracts are the largest barrier. A fighter signed exclusively to a top organisation cannot compete elsewhere, even when he has not been booked in ten months. During those ten months his career stands still, but his biological clock does not. This is a form of career risk no metric captures, and it is why many young Southeast Asian fighters sign with regional organisations rather than wait for a slot at a major one.

Title fragmentation is the second barrier. When one weight class has four champions across four organisations, fans do not know who is best, and fighters have no incentive to unify. This produces a market in which titles function as negotiating instruments more than as measures of ability.

Cross-promotional superfights are the third barrier, and the most interesting. They are rare because they require two organisations to share revenue and share risk. When they happen, they are usually the most uncertain bouts on the calendar, because the two fighters come from two different evaluation systems and have never been directly compared.

Within the framework, this group is usually the easiest to answer, since organisational information is public. It is also the easiest to overlook, because analysts tend to focus on the two people fighting and forget that the bout is staged by a third party with its own interests.

Axis four: business model and market

This is the group I am least often asked about and the one that explains the most phenomena.

Event revenue has four components: ticketing and live gate, broadcast rights, sponsorship, and, for some organisations, pay-per-view. The balance among these four determines which kind of fighter gets promoted.

An organisation heavily dependent on pay-per-view needs a star who can sell an event, and will happily match that star against stylistically easier opponents. An organisation dependent on broadcast rights needs highly competitive bouts, because broadcasters pay for drama, not for a fixed outcome.

The divergence between commercial value and competitive merit is real and measurable. A fighter can be an organisation's best ticket-seller while sitting outside the top five of his division. There is nothing wrong with that commercially. It simply means the rankings and the revenue table measure different things, and readers need to know which table they are reading.

On pay structure, one question always matters: what percentage of event revenue flows to the fighters. In unionised sports that figure is published and collectively bargained. In combat sports it is almost never published. The consequence is that an undercard fighter, who supplies most of an event's running time, may receive a purse that does not cover camp costs. That is a sustainability problem for the industry, and it is why many young talents leave the sport before twenty-eight.

In 2026 a major organisation signed an exclusive uniform deal with an apparel brand, and that decision restructured the entire roster's income: individual sponsorship was restricted, and a portion of revenue was converted into a fixed disbursement. This is a clear example of a commercial decision at the organisational layer flowing all the way down to the wallet of the person doing the fighting. When assessing a fighter, I always want to know where his money comes from. A fighter living on personal sponsorship has different incentives from one living on per-fight bonuses.

Axis five: rules and compliance

This is the driest group and the one that decides the most fights.

Four checkpoints: scoring system, anti-doping compliance, weigh-in process and weight class, and disciplinary history.

The ten-point must system, in which the round winner takes ten and the loser nine or fewer, underpins both boxing and modern MMA. Its flaw is that it cannot distinguish a razor-thin round from a dominant one. Both are 10-9. A fighter who wins three narrow rounds and loses two dominant ones still wins the fight. Fans hate this, but it is the rule, and a good analyst must predict according to the rule rather than according to a sense of fairness.

Anti-doping compliance is a variable with large effects on predictability. A fighter previously suspended for a banned substance presents two possibilities: either he once competed with a chemical advantage, or he once competed in a body damaged by the cycle itself. Both make historical performance data harder to interpret.

Weigh-ins and weight classes concentrate the most risk. A fighter who misses weight faces fines, forfeited purse share, or a cancelled bout. A fighter who makes weight while severely dehydrated enters the fight in a body that has not recovered. In both cases the audience sees only a number on a screen.

Disciplinary history is the easiest part to research and the most frequently skipped. A fighter previously fined for out-of-competition conduct, removed from an event for contractual non-compliance, or engaged in a public dispute with his promoter usually displays a stable behavioural pattern. That pattern does not predict fight outcomes, but it does predict whether the fight happens at all.

In penalty simulation I always split into three scenarios: worst case, base case, best case. The worst case for a fighter mid-contract-negotiation is usually a twelve-month career freeze. The base case is the bout proceeding with an adjusted financial term. The best case is everything running normally and nobody mentioning what almost happened.

Axis six: health and career risk

This is the group I am most often asked about, and the one where I most often have to say "insufficient data".

Six risk categories: brain health, weight-cut incidents, musculoskeletal injury, post-retirement security, psychological safety, and systemic risk.

On the brain, the science has been clear for a long time. In 2026 a landmark study by Corsellis and colleagues on fifteen boxers documented cumulative neurological damage in that group. Decades later, the concept of chronic traumatic encephalopathy became the centre of every safety debate in combat sports. The crucial point: cumulative damage does not correlate with number of losses. It correlates with number of head impacts, including in fights that were won.

So when assessing a fighter I do not count knockout losses. I count rounds in which he absorbed a heavy volume to the head. A fighter can win ten straight and still be accumulating damage at an alarming rate.

On post-retirement security, this is the largest blind spot in the industry. Very few organisations provide pension funds, long-term insurance, or career-transition programmes. A fighter retiring at thirty-five after fifteen years of competition and three knee injuries usually enters the rest of his life without stable income and without transferable skills. That is a structural problem, and it cannot be solved by a charity bout.

On psychological safety, I want to be direct: this is where my data is weakest. I can read dehydration from footage. I cannot read depression from footage. And I have been wrong because of that.

In 2026, at the World Cup quarter-final in Kazan, an online radio station invited me to commentate as a rehabilitation specialist. The world believed a certain star would shine after a foot injury. I presented data from twelve matches I had collected: change-of-direction capacity down roughly twelve percent in the second half, left thigh response slower by about three tenths of a second. I recommended an early substitution to protect him. His team lost, and that star mistimed several challenges in front of goal. The programme's listenership tripled overnight.

The Kazan night taught me: public opinion is noise, numbers are signal. But Kazan also taught me the opposite: mechanical signal says nothing about whether a human being can carry that pressure. That is the blind spot I must always declare, and that night I did not declare it clearly enough.

Axis seven: public narrative and market expectation

The seventh group is the one the media does best and analysis does worst.

A public narrative can be a coronation, a dynasty, revenge, redemption, a farewell, or a crossover. Each has a different life cycle. The revenge story runs until the rematch and dies immediately after. The dynasty story runs until someone beats the champion. The farewell story runs until the final fight, and sometimes longer, because farewell fights have a tendency not to be final.

Testing narrative sustainability has three steps: does it have a fundamental basis, does it survive the record-quality test, and how long is it expected to run.

A narrative with a fundamental basis is built on a verifiable technical fact. One without is built on a hand-picked win over a hand-picked opponent.

Expectation-gap analysis is the most useful tool in this group. It compares market expectation against objective assessment and locates the divergence. When the market expects a blowout and objective assessment shows a competitive fight, that gap is information. When the market expects a fighter to be washed and objective assessment shows his base is intact, that gap is also information.

On the authenticity of beef, I apply a simple rule: if the conflict is resolved by a bout signed in advance, it is a product. If the conflict continues after the contract is signed and nobody mentions it again, it may be real. Fans usually misjudge this because they assess by emotional intensity rather than by timeline.

On crossover bouts, the central question is the degree of competitive mismatch. A bout between an elite mixed martial artist and a celebrity from another field usually carries enormous mismatch, and the two sides' motives are entirely different: one wants money, the other wants fame. Reading such a bout, I always ask who signed first.

Axis eight: industry transmission

This is the most macro group: what change at which layer propagates to which other layer, and how long it takes.

Transmission has three layers. Upstream is gyms and talent supply. Midstream is organisations and events. Downstream is broadcast, data, betting, and consumer markets.

A change upstream takes three to seven years to reach downstream. If gyms in a region begin teaching grappling and submissions rather than only striking, then roughly five years later the midstream will hold more fighters with grappling bases, and the downstream will see fewer knockouts. Nobody calls that a trend. People call it "a new generation".

A change midstream propagates downward much faster. When an organisation signs an exclusive broadcast deal with a platform, the value of every fighter on that roster shifts within a season. When an organisation opens an office in a new region, bout volume in that region rises within eighteen months.

A change downstream can propagate upward. When betting markets begin pricing a division, more bouts in that division get booked. When a streaming platform needs short-form content, fights get designed for highlight moments rather than technical rounds.

On policy and region, this is the variable I once underestimated. In 2026, when the pandemic suspended the Chinese top flight and stadiums stood empty, every commentary contract I held was cancelled within a week. I contacted twenty-three youth players at a Guangzhou club, received sensor data from their at-home sessions via phone, and spent eight months building a load-and-recovery model. When the league returned in June, the team recorded only four injuries across its first ten matches, roughly thirty percent below the two-season average.

The 2026 spreadsheet taught me: the body does not rest; it only needs an algorithm patient enough. It also taught me something else: that model sat scattered across twelve spreadsheets and was never widely adopted, because I am poor at long-term planning. A good finding does not automatically become a systemic change. It needs someone to do that work, and that someone is usually not the person who found it.

An empty stadium does not make a fight cleaner; it only exposes the truth more nakedly. With no crowd, no roar to cover the gaps, what remains is footfall and breathing. 2026 was the year I learned that much of what this industry calls "analysis" is in fact a reaction to a crowd.

The contrarian angle: emptiness is a signal, not an obstacle

Now I want to say what I believe is the most important thing in this article, and it runs against the instinct of almost everyone in the profession.

When a file is empty, the industry's default response is to fill it. The broker wants a number. The journalist wants a quote. The fan wants a prediction. And the analyst, wanting to be useful, produces a confident-sounding forecast built on whatever is available, usually the record and a highlight reel.

I did that for years. And I was wrong in the most uncomfortable way: not wrong because the data lied to me, but wrong because I manufactured data out of gaps.

An empty file has three possible causes, and each says something different.

The first is that the sender has no information. That means the fighter has never been properly tracked, and everything you are about to hear about him is hearsay.

The second is that the sender has information and will not share it. That means something in the file is something they do not want you to see. In my trade this is usually the most alarming signal, because it means someone has decided that information could damage a deal.

The third is that the collection process is broken. That means the organisation is operating without knowing that it does not know. This is the most common cause in combat sports, because most small organisations have no sports-medicine department of their own.

These three causes lead to three different actions. With the first, you build data from scratch, and that takes time. With the second, you find another source. With the third, you tell them where the process is failing.

In all three cases, the one action you must not take is to invent a conclusion.

This is where I differ from most people in commentary. I believe the value of an analyst lies not in how often he is right. It lies in whether he knows what he does not know, and says so at the right moment.

In combat sports this matters more, because the consequence of a bad assessment does not stop at a wrong prediction. It can be a fighter walking into a bout with an unhealed injury, because someone told him he was fine. It can be a fighter cutting twelve kilograms of water in four days, because nobody in the room could read his weight data. It can be a twenty-nine-year-old walking into his third fight in four months, because the schedule was set by the ticket-seller rather than by anyone who understands physiology.

I said at the start that an empty file is not a clean file. I would add: an empty file is often the most honest file in the room. It is the only thing that is not trying to persuade you of anything.

And here I want to address the state of combat-sports analysis in Vietnam specifically. In recent years the professional scene has grown quickly: more events, more professional fighters, and a few names who have stepped onto international stages. The data infrastructure has not kept pace. Most young fighters still have no systematic injury file, no training-load data, and nobody tracking their recovery curve across years.

That means when a Vietnamese fighter steps into a major international bout, the question of whether he has recovered is usually answered by feel. And feel has no spreadsheet.

I am not arguing that analysis must wait for complete data. I am arguing that analysis must state clearly what is missing. An assessment that says "I do not know the condition of this fighter's knee" is more useful than one that confidently asserts "this fighter is in great shape".

What the data cannot see

Every time I finish a framework assessment, I add a short section at the end. I call it "what the data cannot see", and it is the hardest part to write.

Data cannot see fear. A fighter may have perfect recovery metrics and still not dare throw a left kick after a broken leg from a lock. No sensor measures that instant of hesitation, but it exists, and it surfaces in round four.

Data cannot see culture. A fighter raised in an environment where admitting pain is treated as weakness will have an entirely different injury-reporting threshold from one raised where rest is treated as professionalism. Two people can carry the same injury and produce two different datasets, simply because one of them dares to speak.

Data cannot see personal circumstance. A fighter who needs money for his family will accept a third fight in four months while his body flashes red. A fighter mid-way through a residency application will not withdraw, even when a doctor advises it. Those decisions appear in no dataset, yet they shape outcomes more than any load metric.

This is why I always close with an open question rather than a closed conclusion. It is also why I never sign an assessment without stating the date, the data source, and who supplied it.

An undated report is an uncorrectable report. And an uncorrectable report is not worth trusting.

Looking forward

The April story ended like this: the broker called back three days later with a fuller file, complete with date of birth, opponent list, and a note about a wrist injury ten months earlier. I read it and replied within forty minutes. The fight happened, the fighter won on the scorecards, and in round three he stopped using his right hand after a collision.

My point is not that I got it right. My point is that if I had answered on day one with a confident prediction built on a 14-3 record, I could have said anything at all, and nobody could have proven me wrong.

That is the largest problem in combat-sports analysis today. Not a shortage of data. A shortage of the discomfort required to say that you do not know.

If you are reading an assessment where every field is filled, ask which fields were filled with data and which were filled with prose. If you are writing an assessment and notice you are describing a fighter with adjectives rather than metrics, stop and check whether you are selling a story.

And if you are the person holding an empty file, try saying those four words once. Insufficient data. Those four words do not make you less professional. They make you the only person in the room who can be trusted.

In a sport where people hit each other in the head for a living, honesty about what you do not know may be the last remaining form of protection.