A Twelve-Criteria Report That Says Nothing About the Match

In September 2026, at Stade Balmont, Lyon Duchère hosted Jura Sud in the CFA — the fourth tier of French football. Wooden stands, roughly four hundred people, one crackling loudspeaker and the sound of car horns drifting in from the avenue behind the north stand. I sat in the third row holding an A4 sheet handed out at the gate: both line-ups, shirt numbers, a few lines about the managers.

The match finished 2-1. Duchère's striker scored both goals, one with his left foot on 34 minutes, one with his head on 71. The next morning, three local papers ran three different match reports, and all three revolved around the same name. None mentioned the player wearing number 6.

It took me two weeks to rewatch Duchère's previous four matches. I counted by hand, pass by pass, minute by minute. The number 6 — Mohamed Sarr, twenty years old — touched the ball 58 times that afternoon. He completed 51 of 55 passes, 92.7 percent. Six interceptions. No goals, no assists.

The story was somewhere else. Eighty percent of Duchère's dangerous attacking sequences across those four matches ran through his feet. Not the final assist. The pass before the assist. The switch of angle that forced Jura Sud's back line to turn, and three seconds later the space opened on the right flank.

I wrote 1,800 words under a headline about a "diamond in shirtsleeves." It drew 1,200 reads. A Metz scout messaged me asking whether I had kept the data. Sarr joined Metz in 2026 for 1.2 million euros. I have never revised my original assessment.

Nine years later, I received a report far more polished than that A4 sheet at Balmont. It had a title, a data matrix, twelve structural criteria, a risk-level table, and a bolded conclusion section. And it said nothing at all about the match.

A decade later, the report became flawless

Reading reports like that is now my job. I work in Lyon, covering tactics for the French market, and most of my week is spent inside coding sheets.

Compare the two moments. In 2026, at Balmont, I had one A4 sheet and had to build everything from scratch: count, cross-check, timestamp. In 2026, a mid-table Ligue 1 club receives a data package containing hundreds of metrics per player, refreshed after every matchday, with heat maps, passing-network graphs, and composite positional scores.

Structurally, that is an enormous advance. Informatively, not necessarily.

The problem is not a shortage of data. The problem is that a report can be full and still empty. A document with twelve criteria, full charts, and a complete conclusion section — and if you delete every word inside it while keeping the frame, it still looks finished. The frame itself creates the impression that analysis has taken place.

I call it the structurally empty report: a product so correctly formatted that nobody checks whether it has any substance.

Ligue 1 is an ideal environment for observing this. From the 2026-24 season, the league cut down to 18 clubs, reducing the schedule from 380 matches to 306. Fewer matches means each one weighs more, each point costs more, and the pressure on analysis departments rises. Clubs do not cut staff in the data room. They cut rewatch time.

That is where everything starts.

Twelve criteria and the gap in the middle

In March 2026, every European league was suspended. I sat at home and collected footage of 120 matches across six competitions: Ligue 1, the Premier League, La Liga, the Bundesliga, Serie A and the Eredivisie, spanning the 2026-2026 seasons. I hand-coded every pressing sequence. I built twelve structural criteria: average distance between lines, preferred pressing direction, defensive angles on ball loss, timing of the block's advance, number of players in the first press, and seven others.

That framework became my master's thesis, later published in a French football analysis journal with 3,400 reads. It is what got me hired in 2026.

But it also taught me something I had not anticipated: a criteria system good enough will generate conclusions that look correct even when the match supplied no evidence for them.

The clearest example is PPDA — passes allowed per defensive action. Lower PPDA means more aggressive pressing. It is a good metric. It is only good when you read it in context.

A team with a PPDA of 8.4 may be pressing very high. It may also be a team that went a goal down on 20 minutes, had to push up chasing an equaliser, and whose 8.4 is a consequence of circumstance rather than tactical intent. The report does not distinguish the two. It prints 8.4 and writes "aggressive pressing."

That is the gap in the middle. Correct number. Wrong conclusion.

Over the past three seasons I have noticed a recurring pattern at mid-table Ligue 1 clubs: reported pressing metrics rise during a team's slump. On the sheet, the team is running more. On the tape, the team is running worse. The gap between midfield and defence widens from 12 metres to 19, and what gets labelled "aggressive pressing" is really three forwards chasing the ball while the back line drops deeper to protect itself.

The report has enough data to catch this. It has line-distance metrics. It has heat maps. It simply has nobody putting the two side by side and asking the right question.

What I counted by hand

Back to Balmont.

At eighteen I had no tools. I had a notebook and a pen. When I counted Sarr's 58 touches, I counted by rewinding and rewinding and drawing a stroke after each one. When I calculated 51 from 55, I checked every pass individually, and I removed two that a defender had grazed before arrival — passes automated stat sheets still log as accurate.

That is the first difference: raw statistics and what happened on the pitch never align perfectly, and the divergence sits precisely where it matters most.

The second difference matters more. Rewatching those four tapes, I noticed Sarr doing something no metric records: he deliberately received the ball with his back to his own goal, roughly 45 metres from the opponent's box, and always on his weaker foot so he could rotate and open the right flank with a single touch.

No metric is called "receiving on the weaker foot to open the attack." You only see it if you sit and watch and ask why Jura Sud's back line kept turning right while the ball went left.

From that I set a standing rule: never conclude from raw statistics; rewatch tape at least three times; note the exact timestamp of every sequence; and cross-check at least two data sources before publishing.

The rule sounds redundant. It is not. It is the line between a report with information and a structurally empty report.

Kanté and the void nobody measures

In 2026, off the back of the Sarr piece, a student newspaper invited me to contribute during the World Cup in Russia. I analysed 22 matches, with France's run as the focus.

France's 4-2 win over Argentina in the round of 16 is the match everyone remembers. I remember it because I spent the entire first half logging 14 French pressing sequences instead of watching the ball. Not because I enjoy note-taking. Because if I watched the ball I would be swept along and would end up writing about four goals.

My longest piece at that tournament was about the Pogba – Kanté – Matuidi trio. I argued something considered odd at the time: Kanté was not simply "cleaning up" the way match reports described it. He was screening the space in front of the back line, and because that space was screened, Pogba had licence to advance and Matuidi had licence to drift inside.

In other words, Kanté's value was not in his tackles. It was in the sequences that never happened.

The 2026 World Cup taught me that a midfield does not need a hero; it needs a tempo-keeper.

This is where the structurally empty report exposes its fatal weakness. A sequence that never happens generates no data. No event means no log entry. No log entry means no metric. And when the report is packed with Pogba — most touches, assists, goals — Kanté appears seventh in the ratings.

I re-checked those 14 first-half pressing sequences. In nine of them, Kanté moved first — not to win the ball, but to block the lateral pass. The Argentine carrier was forced backwards. The attack died there.

The stat sheet does not log a dead attack. It logs a successful attack. And on average, a team that loses the ball in midfield repeatedly will post prettier defensive numbers than a team that blocks the lane from the start — because the team that blocks the lane never has to defend.

This is the measurement paradox I run into almost every week in my current work.

Heat maps as the new astrology

The heat map is the tool I use most and distrust most.

Technically, it is a set of touch points smoothed into colour zones. It is accurate as data. But it says nothing about a player's role in the system unless you already know that role.

Take a central midfielder whose heat map glows red across the middle, slightly left. The reader concludes: wide-ranging player, left-leaning, a box-to-box type.

The truth may be this: the team plays a back three, the midfielder is instructed to hold the left touchline in possession to stretch the opposition block, and he only touches the ball there because that is the safest circulation channel. He is not box-to-box. He is a cog in a stretching structure, and his real value lies in being the first man back to seal the opposition's inside lane when possession turns over.

The heat map shows you where he was. It does not show you why he had to be there.

In several consultancy meetings I have attended, heat maps were used as a valuation basis. I call it football's new astrology: detailed enough to feel prophetic, vague enough never to be wrong.

The only way to break it is to go back to the tape. Watch three consecutive matches of the same player and record not where he touched the ball, but where he had to move when a teammate touched it. Those are two different maps, and the second one is the tactical map.

Balmont does not produce stars; it only reveals who is willing to run more in order to shine.

What the pandemic season taught me — in reverse

My 120-match project produced a side finding I left out of the thesis.

Coding six leagues across two seasons, I found that teams forced into rotation by congested schedules — particularly during the period when competitions compressed to finish their seasons — showed more stable pressing structures than teams with settled line-ups.

That sounds backwards. The logic is simple: when you cannot rely on a specific individual, you are forced to build a frame. That frame does not depend on who plays. It depends on the distance between lines, on who steps first, and on who drops first when possession is lost.

The pandemic did not destroy football; it stripped away the illusion of attack and exposed the pressing frame.

Compare that with teams who only function when their best eleven are available: they collapse fast when one link goes, because the entire system was designed around that individual. In the data from that season, those teams still posted high attacking metrics. In the table, they dropped points steadily.

That is why I started keeping a separate column in my notebook: "does the structure depend on individuals." Not a data column. A judgement column.

That column was not among my twelve criteria. I added it in 2026, after realising I had been missing it for two seasons.

Loans with purchase obligations

Now to the market.

Small French clubs — and small clubs elsewhere — are being pushed into a model I consider financially harmful: the loan with an obligation to buy.

The mechanism works like this. A big club wants a young player off its books but will not sell cheaply. It loans him to a smaller club with a clause: if the smaller club hits a certain threshold — survival, a top-ten finish, or simply the player appearing in enough matches — the permanent transfer triggers automatically at a pre-agreed fee.

From the big club's perspective, this is a good deal: the player plays, his value is confirmed, and the fee is guaranteed.

From the smaller club's perspective, it is a contingent liability recorded before the corresponding income exists.

The problem is that the analysis report used to green-light these deals is very often the structurally empty report I described earlier. Smaller clubs have limited scouting budgets. They do not have someone watching four fourth-tier tapes. They receive the data package, read the metric sheet, and decide.

Transfers are not a race for money; they are a race to find the right person for the right gap.

In many cases I have reviewed, the loanee arrives with strong defensive metrics but is placed into a system that does not need that profile. The team sits in a low block, defends zonally, and needs a reader of space. The player brought in is a duel-winner. He duels a lot because the system forces him into duels. His metrics improve. The team still loses.

At the end of the season, the obligation triggers. The smaller club pays for a player who does not fit its model, and loses the budget it should have spent on someone who does.

This is the direct consequence of valuing players off heat maps and composite indices rather than off squad structure. And it repeats every transfer window.

Two football cultures, two kinds of discipline

I was born in Vietnam and live in France, and the contrast between the two football cultures shapes how I read matches.

Vietnamese football runs on intuitive discipline. That discipline is real and it is strong. Players hold their positions because they understand each other, because they know where a teammate will be, because the relationships were built over years. When that system breaks, it breaks fast, because there is no underlying structure to catch it.

French football runs on structured systems. Players hold their positions because there is a rule, a shape, a coach who has defined the distance between lines in metres. When that system breaks, it breaks more slowly, because the structure remains even after belief has gone.

This shapes how I write. When I analyse a Vietnamese team, I have to understand the relationships between players before reading the shape. When I analyse a French team, I read the shape first and then look at who is breaking it.

And I have to guard against one trap: assuming that familiar concepts mean equivalent things across the two. "Pressing" in a V.League match is not "pressing" in a Ligue 1 match. Same word. Completely different distances, trigger moments, and numbers of participants.

Whenever I reference a specific context, I try to add a short clarifying sentence. That is professional discipline, not politeness. French readers do not know how the V.League operates, and Vietnamese readers do not know what a mid-table Ligue 1 club lives on.

Football and esports: the same transition lesson

I follow esports closely enough to recognise a familiar pattern.

Viewers tend to judge an esports match by its brilliant teamfights. Five players collide, abilities fly across the screen, the crowd roars. But the part that decides the game is usually the part nobody cheers: vision control, ward placement, wave pushing, squeezing the opponent into an information vacuum.

Esports is no different from football in transition: both reward the side that errs less.

An esports team wins because it controls information before the fight breaks out. A football team wins because it controls space before the ball reaches the striker. Both are preparation problems.

And both are misjudged by the same category of data. In esports, the post-match scoreboard offers damage dealt, kills, deaths. In football, the scoreboard offers goals, assists, pass counts. Both are metrics of moments, not of structure.

When I watch a top-level esports match, I usually switch the scoreboard off. I want to see who placed their vision in the right spot at minute three, when nothing was happening. That is the equivalent of sitting at Balmont counting the 58 touches of a twenty-year-old midfielder nobody noticed.

I trust the pressing map more than the post-match quote.

What to verify next matchday

Across the last three matches of every team I am tracking, there is one metric I always check first, and it appears in no public data sheet: the average distance between the midfield line and the defensive line at the moment possession is lost.

If that distance widens while the pressing metric rises, it is not a sign of a proactive team. It is a sign of a block splitting in two.

In modern football, space does not appear on its own; it is forced open by a moving block. And a block split in two has already lost before the ball rolls.

What I would like you to do next matchday is not read another metric sheet. Pick a player who does not score and does not assist, and watch him three matches in a row. Record where he moves when a teammate has the ball. Compare it with where he touches the ball.

The two maps will not overlap. The gap between them is exactly what the twelve-criteria report left out.