The Pick Engine How the engine works

Methodology

How the engine works

Every probability on a match card is read from a single scoreline grid, built from six seasons of data and checked forty ways before it is sent.

Premier League · Sample card
Fulham v Brentford Sat · 15:00
Over 0.5 goals
Neither side has been in a 0-0 since February
93% ANCHOR
Under 4.5 goals
One of their 38 combined matches reached five goals
88% ANCHOR
Over 1.5 goals
Cleared in 14 of Fulham's last 19 at home
73% STRONG
Over 2.5 cards
The referee averages 3.4 cards a match
71% STRONG
Fulham over 4.5 shots on target
Fulham average 5.8 on target at home
69% STRONG
Over 9.5 corners
Both sides sit above the league corner rate
55% PROBABLE
Both teams to score
Brentford have scored in 15 of 19 away matches
51% PROBABLE
Fulham to win
Shot quality favours Fulham; the draw stays live
49% LONGSHOT

Probabilities are the model's estimates, not recommendations. Sample shown with illustrative figures.

A card as it arrives by email. Each selection carries a probability, a tier, and one line of evidence.

01 — The card

What a card contains

Each match gets one card. The engine prices around 47 markets on every fixture. Roughly 14 make the card: match result, both teams to score, goals from 0.5 to 5.5, corners from 6.5 to 15.5, cards from 0.5 to 4.5, total shots, and shots on target. Every line is priced on both sides. A market without enough evidence behind it is withheld.

The tiers are fixed probability bands. Nothing below 35% is published. A tier describes likelihood. It is not a promise.

85% floor 68% floor 50% floor 35% floor ANCHOR STRONG PROBABLE LONGSHOT ANCHOR STRONG PROBABLE LONGSHOT 85% 68% 50% 35%

Each band is the probability range a tier covers; the tick marks its floor.

02 — The pipeline

From fixture to card

STEP 1Fixture STEP 2Record STEP 3Goals STEP 4Grid STEP 5Evidence STEP 6Checks 123 456 Fixture Record Goals Grid Evidence Checks
STEP 1
Resolve the fixture

Confirm the match itself: teams, competition, venue, referee, kick-off.

STEP 2
Gather the record

Six seasons of match records, including the current one. Shot-quality data, club strength ratings, referee history, injury news.

STEP 3
Estimate the goals

Each side receives an expected-goals figure — the chances a team creates, weighted by how often chances of that kind are scored. Figures are adjusted for division strength, so a promoted club is not rated on numbers earned in an easier league.

STEP 4
Build the grid

A scoreline model turns the two figures into a grid: every possible final score and its probability. Every market on the card is read from this one grid, so no two numbers can contradict each other.

STEP 5
Weigh the evidence

The model is recalibrated against settled results as they arrive. The evidence behind each market is scored, and under-supported markets are withheld. What remains is assigned a tier.

STEP 6
Check the card

Forty automated checks run against the finished card. A single failure and the card is not sent.

03 — A worked example

One fixture, worked through

Newcastle at home to Wolves. The model puts Newcastle on 1.8 expected goals and Wolves on 0.9.

The grid turns those two figures into a probability for every scoreline. The single most likely score is 1-0, at 12%. 0-0 sits at 7%. Even the most likely score is unlikely, which is why the engine never predicts one. It answers market questions by adding cells.

Newcastle to win. Add every cell where Newcastle score more than Wolves: 59%.
Over 2.5 goals. Add every cell containing three goals or more: 51%.
Both teams to score. Add every cell where neither side is on zero: 50%.

Tiers follow from the same grid. Under 4.5 goals sums to 86% and publishes as ANCHOR. Over 1.5 goals sums to 75%, STRONG. Over 2.5, at 51%, is PROBABLE.

7% 12% over 2.5 goals · 51% 012 345 6 Newcastle goals 012 345 6 Wolves goals

Darker cells are likelier scorelines. The dashed outline groups every scoreline that clears 2.5 goals; those cells sum to 51%.

Two-leg combination

Newcastle v Wolves · same grid

Newcastle to win0.59
Over 2.5 goals0.51
multiplied as if independent30%
Read from the grid 36%

The legs overlap: a 3-1 win counts toward both. The grid adds only the cells where both are true, so the combination is priced on its real joint probability. A combination whose legs cannot all be true sums to zero and is refused.

04 — The record

Stated probability against reality

Calibration is the test of whether stated probabilities match reality: outcomes given 80% should happen about 80% of the time. The engine is measured on every pick it publishes.

perfect calibration 6080100 6080100 stated probability actual hit rate

Backtest · Premier League 2025-26 · all 5,356 published picks, settled. Each dot is a band of stated probabilities plotted against how often those selections landed.

By stated probability

StatedWhat happenedSample
70–80%73.7%1,200+ picks
80–90%85.5%1,200+ picks
90–100%94.0%1,200+ picks

By tier

TierStrike ratePicks
ANCHOR91.9%2,848
STRONG77.4%2,269
PROBABLE59.0%239

These figures describe how the engine has performed, not how it will.

05 — Limits

What it does not do

It does not beat bookmakers. Measured against the sharpest closing prices, the engine's numbers are slightly worse. A four-season simulation that staked one flat unit on every published pick lost 3.2%. The engine exists to describe matches accurately, not to promise profit.

A strike rate is not a return. Over 0.5 goals lands about 94% of the time and pays about 1/12. High percentages and high payouts rarely coincide.

It does not price player markets. Goalscorer and other player markets are not offered.

It does not recommend bets. The engine states probabilities. Decisions belong to the reader.

It does not curate its record. Settlement runs daily, and every published figure comes from settled matches. Picks that cannot be verified are counted, never dropped. A win rate never appears without the number of picks behind it.