Nine Strata of Football: The Discipline of an Analyst Who Dares to Say 'Not Enough Data'

In August 2026, on a fourth-tier pitch in Germany, I sat in the seventh row with a paper notebook and an old tablet. China's U-20 selection team played eight matches in the Oberliga under coach Sun Jihai. Twenty-three players. Forty-seven indicators I built myself, from twenty-metre sprint times to receptions between the lines, to the share of passes that broke into the final third. The team won only two matches.

On the last night of the tour, a colleague in Beijing called. He asked what I had written. I told him that my spreadsheet had an empty cell on the row for the third central midfielder, and until that cell was filled I could not write. He laughed down the phone: "A team that wins two matches — who wants to read analysis of that?"

I wrote anyway. But the piece had to wait six weeks, until Yan Dinghao improved his ball-handling speed by four tenths of a second and the number in that empty cell finally appeared. A year later, in June 2026, I sat in Russia recording seventeen sprints by Kylian Mbappé in the France-Argentina round-of-sixteen match, and noticed that the gap between his sprints never exceeded twenty-two seconds. The article had thirty reads on its first day. Three days later Mbappé scored twice, and the piece was shared more than five hundred times.

Both stories taught me the same thing: the real value of an analysis lies in whether it dares to stop when the data is insufficient, not in how fast it is published.

Modern football does not lack spectators. It lacks people who read footprints on melted snow.

After many years in this trade, I have come to see that most football content produced every day begins from a conclusion that already exists, and then goes looking for data to display on behalf of that conclusion. That process is the exact opposite of archaeology. An archaeologist does not descend into a pit with a date already in mind and then pick out the potsherd that fits it. He excavates the top layer first, records the depth, measures the angle of the fragment, photographs the soil, and only then says which stratum the fragment belongs to. The conclusion comes last. If the soil below is empty, he writes in his notebook: empty.

Football analysis today rarely dares to write the word "empty" in its notebook. The transfer market generates a continuous flow of information in which player agents are the largest hidden cost and also the largest source of noise. A rumour is pushed out from a small account, passes through three intermediary layers, and by the next morning it is a headline: "Club X closes in on deal Y." No one in that chain is accountable for verification. When I ask a young colleague for the original source of a rumour, he opens an aggregation piece, which cites another aggregation piece, and the original does not exist.

The transfer market is the dust layer; only the deeper soil decides the age of a talent.

Alongside that flow runs another pressure that is purely technical. Millimetre offside technology has turned referees into editors of the match. A goal is disallowed because a toe crossed the drawn line, and the fans in the stadium have no way of seeing that line. I have watched many VAR matches, and I have noticed a technical consequence that is rarely discussed: when the reward for a well-timed run is judged by a line whose margin of error is smaller than the margin of error of human movement itself, attacking instinct will self-correct toward risk avoidance. Players no longer dare to start half a step early, because half a step is now measured by a ruler. This is a tactical change, not a moral argument. And it can only be seen by an analyst patient enough to count early starts before and after the technology was introduced, rather than writing an angry piece overnight.

Based on my experience tracking matches across many seasons, I believe every decent football analysis must pass through nine layers of evidence. I call them the nine strata. Where a stratum lacks data, it must be recorded as lacking data, and the overall conclusion must wait until the deepest stratum has a sufficient sample.

The first layer anyone sees is tactics and technique. But seeing is not understanding. A formation on paper is a drawing; a formation in play is behaviour. To analyse this layer, a writer needs at least four things: the starting shape and the shape after substitutions, the core tactical idea, and at least one process metric. The most common process metric is xG, expected goals, an estimate of the probability that a shot becomes a goal based on position, angle, the type of pass leading to it, and defensive pressure. Its counterpart is xGA, expected goals against, which measures the quality of chances a defence concedes. Another metric rarely discussed in mainstream media but extremely useful is PPDA, passes allowed per defensive action. The lower the PPDA, the more aggressive the pressing. When I see a team whose PPDA has fallen steadily across three consecutive matches while ball recoveries in the opponent's final third rise, I know the coach has changed the approach, even if the scoreline does not yet reflect it. Conversely, if someone tells me a team "attacks more" without giving me a single process metric, I treat that as a description of feeling, not analysis.

The second layer is club finance and the transfer market. This layer is the heaviest and the most easily skipped, because it has no imagery to put on screen. A club's revenue structure usually splits into broadcasting revenue, commercial revenue, and matchday revenue. Above that sits the wage bill, and the wage-to-revenue ratio is the real measure of health. A transfer cannot be judged by the headline total alone. You need the upfront fee, the number of instalments, performance add-ons, sell-on terms, buy-back terms, and release clauses. The sell-on clause is among the most undervalued items in media coverage: a small club that sells a young player for a modest fee while retaining twenty per cent of a future transfer can earn more than the original fee within three years. Without these data points, any judgement of "expensive" or "cheap" is guesswork. When analysing this layer, I force myself to mark clearly what is published data, what is an estimate, and what is an unverified gap.

The third layer is results and the public-opinion cycle. This is the layer the public sees most clearly and misreads most often. A five-match winning run can conceal a process in decline, and a five-match losing run can conceal a process that is improving. The best tool here is the comparison between process data and outcomes. If a team has generated more xG than its opponents in seven straight matches but has taken only four points, the problem lies in finishing or in the opposing goalkeeper, and it will very likely self-correct. If a team has won four of five through an abnormally high conversion rate, that run is not durable. This layer also carries public pressure. I measure pressure on a manager through three objective signals: the density of critical coverage over two weeks, the appearance of organised protests in the stands, and movement in the sack-race odds. These three signals typically precede a board decision by three to six weeks. When only one signal is present, I do not write.

The fourth layer is league landscape and club positioning. Every league has its own power structure, and that structure determines the value of each match. In some leagues the title is effectively decided by two clubs with outsized budgets, and everyone else competes for continental places. In others the gap between the relegation group and mid-table is a few points, turning every direct encounter into a six-pointer. A six-pointer is a match whose result directly changes the points gap between two rivals, and its psychological value exceeds its three points. To position a club I compare three things: squad value, financial power, and academy output. These three measures rarely align, and the gap between them is where the real story sits.

The fifth layer is rules and governance. This is the driest layer, but it is also the one most likely to invalidate an entire analysis if ignored. The rule system runs from world federation to continental confederation to national association to competition organiser. At the financial level, two regimes are commonly cited: UEFA's financial fair play, and the Premier League's profit and sustainability rules. Both limit losses within a defined accounting window and both require clubs to balance spending against revenue. A financial analysis without a loss figure and without an accounting window cannot conclude anything about breach risk. At the transfer level, there are rules on player registration, contract length, and unauthorised private approaches to contracted players. At the disciplinary level, there are accumulated-yellow suspensions, direct red cards, and sanctions related to supporter conduct. Each has different procedures and timelines. When it is impossible to determine which governing body has jurisdiction, the correct approach is to state that uncertainty, not to pick a rule system at random because it makes a better story.

The sixth layer is management and the dressing room. This layer has the least public data and the most speculation. Here I trust only three kinds of evidence: the coach's power model, meaning whether he is a full manager or a head coach with a narrower remit; the quality of recruitment decisions, measured by how many signings are still at the club after two seasons; and the contract years of key players. Contract year is the most underrated variable in modern football. A player entering the final year of his contract often shows performance swings, and those swings are not necessarily football-related. They come from renewal negotiations running parallel to the season, and from agents starting to generate market noise. Without knowing a player's contract expiry year, any assessment of his form in that period is missing an important piece.

The seventh layer is the risk profile. I split risk into six categories: sporting, financial, personnel, rules, public opinion, and systemic. Each needs its own type of input data. Sporting risk needs fixtures and injury history. Financial risk needs revenue figures and wage structure. Systemic risk needs the league's macro context, such as the threat of losing a continental place or relegation dragging broadcasting revenue down. Here there is a principle I consider among the most important in the whole trade: a null result is not a low-risk finding and it is not a high-risk finding. It is the absence of a finding. Reading a missing-data cell as "no problem" is a serious logical error, and in this trade that error is as dangerous as fabricating numbers.

The eighth layer is media narrative and expectation. Here I care about the heat cycle of a story. A new story usually passes through four phases: emergence, spread, peak heat, and cooling. The duration of each depends on whether the story rests on real data. When a young player scores three goals in his first two matches, the spread phase is fast and so is the cooling phase, unless further evidence shows the ability is durable. Alongside that sits the credibility of transfer sources. I grade sources into three tiers: journalists with direct relationships and an accurate track record, professional outlets that cite with verification, and aggregator accounts with unclear sourcing. The third tier accounts for most traffic and nearly all error. When a rumour comes from the third tier, I do not put it into an analysis, even if it is the most shared item of the day.

The ninth layer, the deepest and slowest to settle, is industry transmission. Football runs along a chain from upstream to downstream: the academy system supplies talent, clubs and competitions operate that talent, and derivative markets such as broadcasting, commerce, data, and betting absorb the value created. A change upstream takes five to seven years to surface downstream. A change in transfer rules takes one to three years. A change in competition structure takes less than a season. Because the lags differ so much, the analyst must choose the right time horizon for the right question. Writing about the impact of an academy generation on broadcasting value within the same season is asking at the wrong layer. So is writing about the impact of a single transfer on academy structure within three months. Six months of freezing is not an empty space; it is where value settles.

The Oberliga map is still lying there; few people are patient enough to dig.

Let me return to the question my colleague asked that night in Germany. He said that a team with two wins produces no analysis anyone wants to read. He was right about the market and wrong about the craft. The market pays for certainty, for a tidy conclusion, for a list of players worth buying. But most of the time the data does not permit that certainty. And when a writer must choose between telling the truth that the data is insufficient and producing a conclusion that merely sounds plausible, market pressure tilts heavily toward the second.

The value of a map lies in the lines left blank, not the lines drawn.

There is a paradox I think about often. A fabricated analysis sounds more persuasive than an honest one, because fabrication can be engineered to match reader expectations. It has club names, player names, transfer fees, formations, and a decisive prediction. An honest analysis, when data is thin, can only say that there is currently insufficient information to conclude. Place the two side by side, and a busy reader picks the first. That is why fabrication in football analysis cannot correct itself through market mechanisms.

The only way I know to resist this is to publish the method. Every measurement I take is time-stamped, annotated with observation conditions, and sourced. When I write that a midfielder improved his ball-handling speed by four tenths of a second over six weeks, I state how I measured it, across how many situations, and in what weather. Readers have the right to verify or reject it. Keeping the process secret to protect a personal discovery is a very human temptation, but it turns that discovery into an unverifiable belief, and unverifiable belief does not accumulate into knowledge.

Every strong generation of players begins as a generation of archaeologists who know how to wait.

Looking ahead, I believe the next generation of analysis will be judged by a different criterion than the current one. The current generation is judged by reads, citations, and speed of publication. The next may be judged by the share of conclusions that still stand after eighteen months, and by whether the writer dares to write empty cells into the notebook. As data becomes cheap and ubiquitous, value shifts from having data to knowing which data is insufficient to conclude. The best analyst of the next ten years will be the one who can read footprints on melted snow, not the one who stands in the storm and shouts a prediction.

I still keep the notebook from that Oberliga season. In it there is a note beside Yan Dinghao's name, written in pencil, with a clear date: "Insufficient sample. Measure again in six weeks." That note is not a failure. It is the most honest part of the entire notebook, and it is the part I want to leave to my youngest reader.