7/12/2026

My Model Learned a New Trick. It Immediately Changed Its Mind About Who Wins.

The quarter-finals are done, the field is down to four, and this week I did something I had been putting off: I let the model learn from the knockouts. Until now it froze every team’s strength at the end of the group stage and just tracked the bracket. Sensible, but half-blind. It could see who survived. It could not see how they were playing.

So I fed the knockout results back into the ratings. Now it knows the difference between winning well and just winning. And the instant it could tell them apart, it moved the favourite off Argentina.

Here is where it lands, what the upgrade changed, and the one call where I now disagree with my own code more sharply than at any point in this tournament.

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The state of the race

Conditioned on every result through the quarter-finals, and now with knockout form baked into the ratings, the title picture:

 Spain 30.6% ·  Argentina 27.9% ·  France 24.8% · gbeng England 16.7%

Forecast Wc2026 V10
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Four teams left, so those four hold the entire championship probability between them. The single most-likely final the model produces is still Spain vs Argentina, and its predicted champion is now Spain. Read the top two lines carefully, because the order just changed, and it changed for a reason.

The setup, for anyone new here

The engine is an ensemble of two models: a Dixon-Coles goals model and a World Football Elo rating, blended at the scoreline level and run through 10,001 Monte Carlo simulations from here to the final. It does not get nervous. It does not have a favourite nephew. It does maths, and this week it did some new maths.

The upgrade: I let the model watch the football

The old version had a blind spot I had been honest about since the group stage. It locked each team’s strength when the groups ended and then simply cascaded the bracket forward. That meant a team could win three knockout ties by a single goal, riding its luck, and the model would treat it exactly as it treated a team dismantling opponents 3-0. Survival and dominance looked identical on the page.

The fix was to feed the knockout results back into the ratings, so the model now updates on how teams are actually playing, not just on who is still alive. It is a small change in code and a large change in worldview. The moment the model could separate winning well from merely winning, it re-ranked the favourites. That is the whole story of this update.

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What the model now sees

 Argentina demoted, from 33.6% down to 27.9%. Three knockout wins, yes, but it conceded in every one of them. It survived Egypt and it survived Switzerland rather than dismissing either. The old model rewarded the clean bracket path. The new model looks at the performances underneath and marks them down. The bracket had been flattering it.

 Spain surged to number one, from 25.7% up to 30.6%. It took Portugal apart and then took Belgium apart, beating strong teams convincingly. That is what actually moves a rating once the model is allowed to watch. Spain did not back into this. It earned it on the pitch.

A quiet flex I have earned the right to: my pre-tournament top two, Spain and Argentina, are both still standing, and the entire final four is exactly the calibre the frozen forecast flagged before a ball was kicked.

The semis

 France v Spain  · gbeng England v Argentina 

A France v England final is very much alive, and if you have read these updates since the group stage you know exactly which of those two names I have been shouting about for weeks.

Where I overrule the machine, and it is not close

Here is the honest part, and it has sharpened since the last edition, so let me say it plainly.

Two rounds ago I said France and England, both, were operating on a different frequency. The bracket has since answered part of that for me: England drew Argentina, France drew Spain, and my two-team thesis has to survive contact with two very hard semi-finals. So I will narrow it and commit. The model has France third. I have France first, by a distance, and I will die on this hill.

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Look at what France has actually done in the knockouts: three games, three wins, zero goals conceded. Sweden, Paraguay, Morocco, all dispatched without a scare. Sharper, deeper, meaner than anyone left. To my eye they are operating a full level above the field, and the eye test has not been this loud all tournament.

The model docks them on two technicalities. They drew the now-strongest side, Spain, in the semi, which is a draw problem, not a quality problem. And their goals scored were only modestly above expectation, a 1-0 over Paraguay where the maths wanted more. Fair, on the model’s own terms. But the model counts goals and opponents. I am watching football, and I am watching the best team in the tournament stack clean sheet on clean sheet on its way to the final.

Model says Spain. I say France, comfortably. One of us is about to be very wrong, and I have never been more relaxed about it. A forecast you only ever nod along with is not worth much. The value is in the disagreement, and in being honest about which side of it you are standing on.

Under the hood

For the curious: the two models are blended at the scoreline level and the remaining tournament is simulated 10,001 times, now conditioned not only on every actual result but on updated strength ratings that absorb knockout form. The rigour from earlier editions still holds. FIFA’s 2026 tiebreaker puts head-to-head above overall goal difference, a break from every previous World Cup, and it is coded properly rather than approximated. The knockout third-place allocation follows FIFA’s official deterministic table. A forecast is only as trustworthy as the plumbing beneath it, and this week the plumbing got an upgrade.

What is next

The semi-finals are loading. France v Spain, England v Argentina, no redraws, no second chances. The model gets re-run after every round, and I will keep publishing where it lands, and where, like now, I loudly disagree with it.

Model says Spain. My eyes say France. We are about to find out who was right.

The Champion Predictor is a quantitative model built for research and curiosity, not betting advice. For round-by-round updates through to the final, subscribe. The next one lands after the semi-finals.



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7/08/2026

My Model Now Says Argentina by a Mile. My Eyes Say France and England.

The Round of 16 is done, the field is down to eight, and the model has re-run the whole tournament on the wreckage. Two title contenders gone from the same half of the bracket. The frozen pre-tournament forecast still standing on five of the eight quarter-finalists. And a champion probability that just lurched in one direction hard enough to make me suspicious of it.

Here is where it lands, who the penalty spot just swallowed, and the one call where I still refuse to agree with my own code

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The state of the race

Conditioned on every result through the Round of 16, the title picture:

 Argentina 29.2% ·  Spain 21.4% ·  France 19.2% · gbeng England 13.6% ·  Morocco 6.5%

The top four now hold 83% of the championship probability between them. The single most-likely final the model produces is still Spain vs Argentina. Read the top line carefully, because it moved for a reason that has nothing to do with Argentina playing well

Forecast Wc2026
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.

The setup, for anyone new here

The engine is an ensemble of two models: a Dixon-Coles goals model and a World Football Elo rating, blended at the scoreline level and run through 10,001 Monte Carlo simulations from here to the final. It does not get nervous. It does not have a favourite nephew. It does maths, and it occasionally embarrasses me by being right.

The part I am still proudest of

Anyone can look clever editing predictions after the goals go in. The honest test is the version you lock the night before the opener and never touch again.

That frozen forecast called five of the eight teams now in the quarter-finals, sight unseen: Argentina, Spain, France, England, Belgium. The three it missed are exactly the tournament’s fairytales: Morocco, Norway and Switzerland. A model built on 49,390 historical matches was never going to price a fairytale. That is not a bug. That is the fairytale doing its job.

For the record, the frozen forecast also nailed 12 group winners out of 12 before a ball was kicked. I will be mentioning this at dinner parties until roughly 2030.

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The fallen

The Round of 16 sent two genuine contenders to the airport, and it took them from the same corner of the bracket.

 Brazil, whom the model gave a 10.3% title shot at the last update, walked into Norway and lost 1-2.  Colombia, a 5.8% side going in, went out to Switzerland on penalties.

The penalty spot remains the place forecasts go to be humbled. A shootout is a coin flip in expensive boots, and no model that respects the data pretends otherwise. This time it did not just take two contenders. It gutted an entire half of the draw, which is the single most important fact in this update.

What moved since Version 7

Compared with the forecast I last published at the end of the Round of 32, the knockouts did what good information should do. They sharpened the picture, and in one case rewrote a team’s odds without that team doing anything at all.

 Argentina leapt from 21.8% to 29.2%, a +7.4 jump. It did not surge because Argentina played well. It needed a nervy 3-2 over Egypt just to get here. It surged because the two teams that could have stopped it, Brazil and Colombia, both went home on the other side of the bracket. The model is not pricing Argentina’s football. It is pricing Argentina’s suddenly empty path.

gbeng England is the quiet mover of the round, up +6.6 from 7.0% to 13.6% and climbing.  Spain also jumped hard, +5.8 from 15.6% to 21.4%, and now sits clear in second.  France barely budged, +0.8 from 18.4% to 19.2%, because unlike Argentina it is stuck in the hard half with Spain, Morocco and Belgium. Your odds are hostage to the draw as much as to your own form. Easy bracket and best team are graded on very different rubrics, and the bracket is the rubric that pays out.

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Where I overrule the machine

Here is the honest part, and it has shifted since the last edition, so returning readers deserve me saying so plainly.

Last time I overruled the model in favour of France, alone. I still believe in France. But watching this round, I now think there are two teams operating on a different frequency, not one. France and England, both. Sharper, deeper, meaner from front to back, peaking at exactly the right moment. To my eye that is your final. France vs England. Book it.

And Argentina? The model’s 29% darling looks, to me, the shakiest favourite of the lot. A 3-2 wobble past Egypt is not the swagger of a 29% team. It is a side being carried by a collapsing draw. The model rewards the path. I am watching the performances, and the performances are flashing yellow.

One of us is going to look very silly when this is over, and I am suspiciously comfortable betting against the algorithm’s pet. A forecast you only ever nod along with is not worth much. The value is in the disagreement, and in being honest about which side of it you are standing on.

Under the hood

For the curious: the two models are blended at the scoreline level and the remaining tournament is simulated 10,001 times, conditioned on every actual result so far. The same two acts of rigour from the last edition still hold. FIFA’s 2026 tiebreaker puts head-to-head above overall goal difference, a break from every previous World Cup, and it is coded properly rather than approximated. The knockout third-place allocation follows FIFA’s official deterministic table. A forecast is only as trustworthy as the plumbing beneath it.

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What is next

The quarter-finals are loading. The bracket is fixed, no redraws. The model gets re-run after every round, and I will keep publishing where it lands, and where, like now, I quietly disagree with it.

Model says Argentina. My eyes say France and England. We are about to find out who was right.

The Champion Predictor is a quantitative model built for research and curiosity, not betting advice. For round-by-round updates through the knockouts, subscribe. The next one lands after the quarter-finals.



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7/05/2026

Eight Novels for the Summer

The Economist ran its summer fiction list on June 26. Eight titles. A murder mystery, two Irish and Italian family sagas, a Bangladeshi rebellion, a Mississippi Depression story, a slim Ben Lerner puzzle box, and a Patchett reunion. All eight are new this year. Below is what each one is and why it earns a place on the summer stack, with nothing given away.

The Calamity Club, by Kathryn Stockett

Seventeen years after The Help, Stockett’s second novel. Oxford, Mississippi, 1933. Prohibition is fading, the Depression is biting. An eleven-year-old orphan, an unmarried woman down from the city, and a stranger with little left to lose cross paths. What follows is a story about women taking back agency in a place built to deny it. Two narrators, two timelines, one long-awaited return.

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The Kindness of Strangers, by Emma Garman

A debut, and a good one. London, 1953. A boarding house in Chelsea, a widow who runs it, and a stranger who arrives one foggy night and unsettles everyone under the roof. The book opens with a man dying on the drawing room floor. Everything after works backward and forward from that. Compared to Christie and Kate Atkinson, but the voice is its own. Postwar London rendered in smoke and food shortages. The Economist called it sharp and full of period detail.

Land, by Maggie O’Farrell

Her tenth novel, and her most ambitious. Ireland, 1865, a decade after the Great Hunger. A mapmaker working for the British Ordnance Survey has an epiphany at an ancient spring and abandons the official map for an unofficial one, told in the native language. A family saga that stretches from one life span to the age of the land itself. Colonization, displacement, folklore. The kind of book you live inside rather than read.

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Other People’s Children, by Ben Faccini

Faccini’s third novel, and his first in nearly twenty years. A man named Tommaso holds his life together: a job that sends him abroad, a partner with two unruly sons, and an aging Italian grandmother, Alma, whose memories are turning strange. The past reaches back to the Italian resistance in the Second World War and forward into the chaos of modern London. A quiet, precise book about inheritance and the long shadow of what families keep hidden.

The Things We Never Say, by Elizabeth Strout

A new standalone from the author of Olive Kitteridge and the Lucy Barton books. Strout does what Strout does: ordinary people, subtle emotional weather, the things left unsaid between them. If you have read her before, you know the register. If you have not, this is a fair place to start.

Transcription, by Ben Lerner

Slim. Formally unstable, as the New Yorker put it. Lerner’s follow-up to 10:04 and The Topeka School, a novel that blends fiction, memoir, and essay, shot through with humor and anxiety. A meditation on memory, fatherhood, and the devices we use to store or erase experience in a digital age. It reads fast and settles slow. Winner of the Orwell Prize.

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Uprising, by Tahmima Anam

Inspired by the real women of Banishanta, Bangladesh. On a sinking island off the coast, a community of women live under a madam who was once sold into slavery herself. Their children narrate. When an educated young woman is forcibly brought to the island and refuses to yield, complacency turns to defiance. A fierce, slim, feminist novel of resistance and female power. Finalist for the Orwell Prize for Political Fiction.

Whistler, by Ann Patchett

Her tenth novel, and by several accounts her best. It opens in the Metropolitan Museum of Art, where a woman in her fifties notices an old man following her and her husband through the galleries. He is her former stepfather, whom she has not seen since she was nine. What binds them is a single winter day decades earlier and a story he once told her. Quieter than Bel Canto. A mystery of the heart rather than a body on the floor. Reconciliation, memory, and the small moments that define a life.


Eight books, one summer. Pick one, pick all of them. If you have read any, tell me where the rest of us should start.

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Philosophy majors are now the hottest asset in the labor market.

Surprised? Two years ago nobody would have called this.

Per the Economist, citing the Federal Reserve Bank of New York, American philosophy graduates are now more likely to hold a job than the computer science crowd. In 2024, the latest year available, 7% of computer science graduates were unemployed. For philosophers, 5.1%.

Is this really a shock when you sit with it? Probably not. Look at what AI has done to code generation. The scarce input stops being technical, how to code a given problem or hold base domain knowledge, and becomes thinking itself. General intelligence. The ability to ask the right question.

By that I mean: how to frame a problem, how to structure it, how to reason from first principles, how to use conceptual models to see the immediate consequences, the long term consequences, and the trade-offs you cannot dodge. All of it resting on solid ground drawn from ethics, deontology, moral reasoning, and legal principle.

Put that way, it comes as no surprise that philosophy majors are best equipped for the work.

We are coming full circle. I cannot say I am shocked. I’m really pleased.

Economist link: [link to article]

Hope you enjoy the piece as much as I did. What do you make of it? Let me know.



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La IA no es una herramienta. Es una palanca de propĂłsito general

Hay una forma barata de usar la inteligencia artificial y hay una forma que importa. La barata trata a la IA como una máquina de tareas concretas. Escribe este correo. Resume este informe. Traduce este párrafo. Funciona, ahorra minutos, y no cambia nada de fondo. Es usar un telescopio para leer la hora.

La que importa es otra. Y la entendí del todo un sábado por la tarde, resolviendo un problema que no tenía nada que ver con mi trabajo.

Mis tres hijos tienen vacaciones hasta el 8 de septiembre. Nueve semanas. Dos mellizos de 8 años que acaban de terminar 3º de Primaria y el mayor de 12 que cierra 1º de ESO. Cualquier padre conoce la física del asunto: el conocimiento adquirido durante el curso se evapora si no se toca, y en septiembre se empieza medio peldaño por debajo de donde se dejó.

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Quería un plan. No fichas sueltas descargadas de internet, sino algo estructurado, alineado con el currículo que de verdad han dado, dosificado día a día, y con un incentivo real para que lo hicieran sin que yo tuviera que negociar cada mañana.

Lo construĂ­ en una tarde con Claude.

La soluciĂłn

Dos cuadernos de ejercicios de verano. Uno para los mellizos, “Los Mellizos Exploradores”. Otro para el mayor, “Comandante del Cosmos”.

Cuaderno Gemelos 3primaria
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Cuaderno Mayor 1eso
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Los nĂşmeros:

  • 47 misiones en cada cuaderno. Una por dĂ­a lectivo, del 6 de julio al 8 de septiembre.

  • 4 asignaturas en rotaciĂłn continua: Matemáticas, Lengua, InglĂ©s y FrancĂ©s. Contenido alineado con el currĂ­culo LOMLOE de 3Âş de Primaria y de 1Âş de ESO.

  • 15 minutos por ejercicio. Ni uno más. La atenciĂłn de un niño de 8 años es un activo escaso y volátil, y un plan que lo ignora fracasa el segundo dĂ­a.

  • 188 retos por cuaderno, cada uno con su soluciĂłn razonada en un cuaderno del profesor aparte, para que mi mujer y yo podamos corregir y explicar el mĂ©todo, no solo el resultado.

Y el detalle que lo sostiene todo: un sistema de puntos. 1 punto por completar la misión, 2 más por acertarla. Cada 30 puntos, 10 euros. Economía conductual aplicada a la mesa de la cocina.

Todo envuelto en una temática espacial, porque “rellena la ficha” no vende, pero “Comandante del Cosmos” sĂ­. Los mellizos descomponen el 4.208 en unidades de millar mientras una nave espera para despegar. El mayor despeja x para desbloquear el siguiente nivel. La raĂ­z cuadrada de 144 abre una compuerta. Nadie lo llama deberes.

El sistema de incentivos funcionó antes de imprimirlo. Mi hijo de 12 ya había calculado su rentabilidad esperada por asignatura y decidido dónde concentrar el esfuerzo. Ese cálculo no venía en el temario.

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El patrĂłn

AquĂ­ es donde el cuaderno deja de ser lo interesante.

La misma semana que produje esos cuadernos, usé la misma herramienta para dos cosas que no podrían parecer más distintas. Valoré empresas del S&P 500 con un motor de Monte Carlo de 10.001 trayectorias, simulación de ingresos por segmento y reversión a la media en la estructura de costes. Y construí un modelo probabilístico del Mundial 2026, un ensemble de Dixon-Coles y Elo con miles de simulaciones sobre el nuevo formato de 48 selecciones.

Motor de valoraciĂłn. Modelo de fĂştbol. Plan de estudios de primaria con puntuaciĂłn gamificada.

Tres dominios sin nada en común. La misma herramienta, la misma semana, a veces el mismo día. No cambié de software entre uno y otro. No aprendí tres programas distintos. Cambió una sola cosa: la pregunta que hice.

Eso es lo que la mayorĂ­a todavĂ­a no ve. La IA generativa no es una aplicaciĂłn con una funciĂłn. Es un multiplicador de propĂłsito general, más cerca de la electricidad o de la hoja de cálculo que de un producto concreto. La hoja de cálculo no “sirve para” una cosa. Sirve para cualquier cosa que puedas expresar en filas y columnas. La IA sirve para cualquier cosa que puedas expresar con precisiĂłn en palabras.

Y ahí está el desplazamiento real de la ventaja competitiva.

Lo que de verdad cambia

Durante décadas, el valor profesional estuvo en saber la respuesta. En tener el conocimiento, la técnica, el dato que otros no tenían. Ese activo se está abaratando rápido, porque la respuesta está cada vez más disponible para quien sepa pedirla.

Lo que no se abarata es saber formular el problema. Descomponer una situaciĂłn confusa en una pregunta precisa. Saber quĂ© restricciones importan, quĂ© se puede ignorar, cĂłmo debe verse una buena respuesta antes de tenerla. Un cuaderno de 15 minutos por ejercicio no sale de pedir “hazme deberes de verano”. Sale de saber que la restricciĂłn real es la atenciĂłn del niño, que el incentivo tiene que ser tangible, que el currĂ­culo tiene que ser el correcto, y que el padre necesita poder corregir sin volver a estudiar.

La herramienta ejecuta. El criterio para dirigirla sigue siendo tuyo. Y por ahora, es lo Ăşnico que no se puede descargar.

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El cierre

Este verano mi problema era mantener tres cerebros activos hasta septiembre. Lo formulé bien y quedó resuelto en una tarde.

La pregunta que dejo abierta no es si vas a usar IA. Es qué problema tuyo, uno de verdad, estás formulando lo bastante bien como para resolverlo.

¿Cuál es el tuyo?


Si quieres ver cómo quedaron los cuadernos, o cómo está montado el motor de valoración y el modelo del Mundial, están en las notas y en publicaciones anteriores de Risk Premium Research.

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7/04/2026

My Model (Still) Says Argentina. My Eyes (Still) Say France.

The Round of 32 is done, the field is halved, and my forecasting model has re-run the whole tournament on the wreckage. Here’s where it lands, who it just lost to the cruelest lottery in sport, and the one call where I flatly refuse to agree with my own code.

Forecast Wc2026 V7
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Two heavyweights gone on penalties. Twelve group winners I called before a ball was kicked, all still standing. And France, the team the model keeps politely filing under second best, just handed a clearer road to the final without kicking a single different ball.

The first knockout round is complete, which means the Champion Predictor has been fed every result and rebuilt from the ground up. Before the Round of 16, here’s the state of play: what the model is sure of, what it got right when it actually counted, and the one place my eyes and my mathematics are no longer on speaking terms.

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The state of the race

After conditioning on every result through the Round of 32, the title picture:

🇦🇷 Argentina, 21.8% 🇫🇷 France, 18.4% 🇪🇸 Spain, 15.6% 🇧🇷 Brazil, 10.3% 🏴󠁧󠁢󠁥󠁮󠁧󠁿 England, 7.0%

Argentina sits clear at the top. France is now alone in second, Spain a length back, and the top four hold roughly two thirds of the title probability between them. The single most-likely final the model spits out is still Spain vs Argentina.

The setup, for anyone new here

The engine is an ensemble of two models: a Dixon-Coles goals model and a World Football Elo rating, blended at the scoreline level and run through 10,001 Monte Carlo simulations of the tournament from here to the final. It does not get nervous. It does not have a favourite nephew. It does maths, and it occasionally embarrasses me by being right.

The part I’m actually proudest of

Anyone can look clever editing their predictions after the goals go in. The honest test is the version you lock the night before the opener and never touch again.

Graded against reality through the Round of 32, that frozen forecast has:

  • Group winners: 12 out of 12.

  • Teams in the Round of 16: 12 of 16, chosen blind.

  • Match-outcome accuracy: 61%.

  • Mean Ranked Probability Score: 0.156.

That last number is the one I trust most, so it’s worth a sentence. The Ranked Probability Score grades not just whether you were right but how confident and how close you were. Missing a result “by a draw” barely stings; calling a home win that turns into the opposite hurts a lot. A blind guess scores about 0.278. My model’s long-run form is 0.169. So far this tournament it’s running 0.156, comfortably better than its own average. Translation: it isn’t just picking winners, it’s well calibrated on the probabilities underneath them.

But the line I keep coming back to is the first one. Twelve group winners out of twelve, and twelve of the sixteen knockout survivors, all committed to before a single ball was kicked. I’ll be mentioning this at dinner parties until roughly 2030.

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The fallen

Two pre-tournament somebodies are already at the airport, and both left the cruelest way. Germany and the Netherlands, each dispatched on penalties in the Round of 32. Going into that round the model still gave them a live title shot, 4.6% and 2.2%, contenders, not passengers. But the penalty spot is where forecasts go to be humbled. A shootout is a coin flip in expensive boots, and no model that respects the data pretends otherwise. It took two live contenders with it, and there was nothing in the mathematics that could have saved them.

What’s moved since the last update

Compared with the forecast I last published, Version 6 at the end of the group stage, the first knockout round did what good information should do. It sharpened the picture, and in one case rewrote a team’s odds without that team doing anything at all.

France got a promotion for doing nothing. With Germany and the Dutch cleared out of its half of the bracket, its number jumped from 14.5% to 18.4% without France having to play a single different match. This is how tournament probability actually works. Your odds are hostage to the draw as much as to your own form.

Spain holds third at 15.6%, still one of the strongest sides in the field. Brazil firmed to 10.3%. And Morocco keeps sidling up the board with genuine dark-horse menace. Best team on paper and last team standing are graded on very different rubrics, and the bracket is the rubric that pays out.

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Where I overrule the machine

Here’s the honest part. The model’s pick is Argentina. I don’t think it’s right.

The machine watches football through a spreadsheet. It sees results, ratings, squad values, home advantage. What it can’t see is the thing I can’t stop seeing. From where I’ve been sitting, France aren’t just winning, they’re operating on a different frequency. Sharper, deeper, meaner from front to back. To my eye they’re at least a level above everyone else in this tournament, and the bracket has just tilted their way on top of it.

The model has them a close, climbing second at 18.4%. My eyes have them first, and it isn’t close. One of us is going to look silly when this is over, and I’m suspiciously comfortable with those odds. A forecast you only ever nod along with isn’t worth much. The value is in the disagreement, and in being honest about which side of it you’re standing on.

And the flip side, the team that let me down most: Portugal. A genuine pre-tournament dark horse who never got going, second in their group and out before the story ever started. For a side many of us fancied, a real disappointment.

Under the hood

For the curious: the two models are blended at the scoreline level and the remaining tournament is simulated 10,001 times, conditioned on every actual result so far. Two small acts of rigour, because details are the whole game in this work. FIFA quietly changed the 2026 tiebreaker rules so head-to-head now outranks overall goal difference, a break from every previous World Cup that materially changed who topped a group. And the Round-of-32 third-place allocation follows FIFA’s official deterministic table, not a convenient approximation. Both were caught and coded properly. A forecast is only as trustworthy as the plumbing beneath it.

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What’s next

The Round of 16 is loading, the bracket is fixed, no redraws. The model gets re-run after every round, and I’ll keep publishing where it lands, and where, like now, I quietly disagree with it.

Model says Argentina. My perception and football awareness says France. We’re about to find out which one of us was right.


The Champion Predictor is a quantitative model built for research and curiosity, not betting advice. If you’d like the round-by-round updates through the knockouts, subscribe. The next one lands after the Round of 16.



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6/28/2026

My Model Says Argentina. My Judgment Says France.

My Model Says Argentina. My Judgment Says France.

The 2026 World Cup group stage is done. Here’s how the Risk Premium Research Champion Predictor is calling the knockouts, and the one place I’m overruling my own machine.

Forecast Wc2026 V6 28062026
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Seventy-two matches. Three weeks. Not a single group winner the model didn’t see coming, and one team I can’t stop thinking about that the model keeps insisting is only the second-best in the field.

The group stage of the 2026 World Cup is complete, which means the Champion Predictor has now been fed every result and re-run from the ground up. Before the knockouts begin, this is where things stand: what the model is confident about, what it got right when it actually counted, and the one call where my own judgment and my own code refuse to agree.

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The state of the race

After conditioning on all 72 group-stage results, the title picture looks like this:

🇦🇷 Argentina, 21.8%
🇫🇷 France, 14.5%
🇪🇸 Spain, 14.4%
🇧🇷 Brazil, 7.4%
🇨🇴 Colombia, 6.3%
🏴󠁧󠁢󠁥󠁮󠁧󠁿 England, 6.3%

Argentina sits clear at the top, with France and Spain locked together a length behind and a tightly-packed chasing pack after that. The single most-likely final the model spits out is Spain vs Argentina.

What’s moved since the last update

Compared with the forecast I last published, Version 4, just before the second round of group matches, the group stage has done what good information should do: sharpened the picture.

  • Argentina surged, 17.7% to 21.8%. They won Group J at a canter and the bracket fell kindly for them.

  • France firmed, 12.2% to 14.5%. Three wins from three, and a clear, rising No. 2.

  • Spain held at 14.4%, having recovered completely from a nervy opening draw.

  • England slipped, 8.5% to 6.3%, on a limp finish to the groups.

The part I’m actually proudest of

It’s easy to update a forecast as results roll in and look smart in hindsight. The real test is the version you commit to before you know anything.

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I locked one forecast the night before kickoff and never touched it again. Graded against reality across the entire group stage, that frozen forecast went:

  • Group winners: 12 out of 12.

  • Round-of-32 qualifiers: 26 of 32 (81%).

  • Match-outcome accuracy: 61% (44 of 72).

  • Mean Ranked Probability Score: 0.156.

That last number deserves a sentence, because it’s the one I trust most. The Ranked Probability Score grades not just whether you were right but how confidently and how close you were. Getting a result wrong “by a draw” costs far less than calling a home win that turns into the opposite. A blind, uninformed guess scores about 0.278. My model’s long-run benchmark is 0.169. Across these 72 games it landed at 0.156, comfortably better than its own average. In plain terms: the model wasn’t just lucky on the winners, it was well-calibrated on the probabilities underneath them.

But the line I keep coming back to is the first one. Twelve group winners out of twelve, called before a single ball was kicked.

Where I overrule the machine

Here’s the honest part. The model’s pick is Argentina. I don’t think it’s right.

For my money, France are the strongest team in this tournament and my pick to lift the trophy. They won all three group games, 3-1, 3-0, 4-1, and carry the best goal difference in the entire field at +8. More than the numbers, they simply look the most complete side from front to back. The model has them a close, climbing second. My judgment puts them first. I’m comfortable with the disagreement. A forecast you only ever nod along with isn’t worth much.

And the flip side, the team that’s let me down most: Portugal. A genuine pre-tournament dark horse who never got going. Second in their group behind Colombia, draws against DR Congo and Colombia, a single comfortable win, and now a distant eighth (3.6%) in the title race. For a side many of us fancied, it’s been a real disappointment.

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Under the hood

For the curious: the engine is an ensemble of two models, a Dixon-Coles goals model and a World Football Elo rating, blended together and run through 10,001 Monte Carlo simulations of the remaining tournament, conditioned on every actual result so far.

Two small acts of rigour worth mentioning, because details are the whole game in this work. First, FIFA quietly changed the 2026 tiebreaker rules so that head-to-head now outranks overall goal difference, a break from every previous World Cup, and one that materially changed who topped a group. Second, the Round-of-32 third-place allocation follows FIFA’s official deterministic table, not a convenient approximation. Both were caught and coded properly. A forecast is only as trustworthy as the plumbing beneath it.

What’s next

The knockouts begin now, and the bracket is fixed: no redraws. Argentina open against Cape Verde, France against Sweden, Spain against Austria. The model will be re-run after every round, and I’ll keep publishing where it lands, and where, like now, I quietly disagree with it.

Model says Argentina. My perception and football awareness says France. We’re about to find out which one of us was right.


The Champion Predictor is a quantitative model built for research and curiosity, not betting advice. If you’d like the round-by-round updates through the knockouts, subscribe. The next one lands after the Round of 32.



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