AI Prompt · Primary Product

Pre-Game Use Cases — No Calculators Required

The calculators are top-of-funnel — useful, free, indexed. The AI prompt is the product. These six pre-game workflows replace five tabs of stat sites and a half-built spreadsheet with a single structured conversation.

📖

Explain the bet

Before placing a wager, ask the AI to walk you through what the market is implying — what would have to be true for this price to be fair, and which historical comparisons are closest.

Example prompts

"Brighton -0.5 AH at 1.92 against Arsenal — what does the market think this game looks like, and what would have to be true for that price to be wrong?"

"Walk me through the implied scoreline distribution if I bet Over 2.5 at 1.85 in Bayern vs Dortmund."

"Explain why the BTTS market for Inter vs Atalanta is priced where it is, given recent xG."

🧪

Stress-test the assumptions

Once you have a thesis, ask the AI to find the weakest assumption in it — the input that, if wrong, would flip the bet.

Example prompts

"I think Liverpool are good value at 2.10 to win at Tottenham. What is the single biggest assumption in that view, and what would the price look like if I'm wrong?"

"Stress-test my view that Real Madrid are over-rated favourites in El Clásico based on recent form."

"Find the weakest link in this thesis: Newcastle Over 1.5 team goals at 1.95 because of high home xG."

🔄

Run what-if scenarios

Ask the AI to recompute under different assumptions — without touching the calculator. Lineup news, weather, motivation, refereeing — feed in changes and watch how the picture moves.

Example prompts

"What if Haaland is a late scratch — how does that change the City vs United probability picture?"

"Recompute the Brighton scoreline distribution assuming a 25mm rainfall reading at kick-off."

"If both managers are confirmed to rotate three players each, how should I update my expected goals?"

🎯

Generate market angles

Pre-game, ask the AI to surface the half-dozen markets where the line and your model disagree the most — including markets you might not normally check.

Example prompts

"Given my Poisson xG inputs of 1.7 / 1.1, list every market where bookmaker prices look at least 5% off vs fair value."

"Find me three corner markets, two card markets, and one player shot market where Brighton vs Arsenal looks mispriced."

"What's the highest-EV bet in the Bayern vs Dortmund Asian handicap ladder, given my xG model?"

🎓

Educate yourself on the fixture

Ask the AI to explain a fixture's history, tactical context, or relevant statistical patterns — so you're betting from understanding, not vibes.

Example prompts

"Brief me on the tactical pattern of the last 6 Real Madrid vs Barcelona matches — possession share, xG split, key chances."

"What's the historical scoreline distribution in Premier League fixtures with one home club above the European places and one in the bottom four?"

"What does the xG of 'host nation Saudi Arabia at the World Cup' say about a host-nation premium?"

🔬

Pre-match research workflow

Use the AI as your full pre-match research assistant — replace 5 tabs of spreadsheets and stat sites with a structured prompt sequence.

Example prompts

"Run the full KiqIQ pre-match brief on Atletico Madrid vs Sevilla: form, xG, set-piece exposure, manager record vs each other, and three best market angles."

"Build me a one-line summary I can copy into my bet notes for tonight's 8 PL fixtures."

"Compare the implied probabilities at Pinnacle, Bet365, and Smarkets for the Brighton vs Arsenal 1X2 market and tell me which one is closest to fair."

Ready to try it on tonight's fixtures?

The AI prompt is gated behind sign-up — but the first three queries are on us. No card required.

Open the AI prompt →See in-game use cases

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AI Prompt · Primary Product

Pre-Game Use Cases — No Calculators Required

📖

Explain the bet

Before placing a wager, ask the AI to walk you through what the market is implying — what would have to be true for this price to be fair, and which historical comparisons are closest.

Example prompts

"Brighton -0.5 AH at 1.92 against Arsenal — what does the market think this game looks like, and what would have to be true for that price to be wrong?"

"Walk me through the implied scoreline distribution if I bet Over 2.5 at 1.85 in Bayern vs Dortmund."

"Explain why the BTTS market for Inter vs Atalanta is priced where it is, given recent xG."

🧪

Stress-test the assumptions

Once you have a thesis, ask the AI to find the weakest assumption in it — the input that, if wrong, would flip the bet.

Example prompts

"I think Liverpool are good value at 2.10 to win at Tottenham. What is the single biggest assumption in that view, and what would the price look like if I'm wrong?"

"Stress-test my view that Real Madrid are over-rated favourites in El Clásico based on recent form."

"Find the weakest link in this thesis: Newcastle Over 1.5 team goals at 1.95 because of high home xG."

🔄

Run what-if scenarios

Ask the AI to recompute under different assumptions — without touching the calculator. Lineup news, weather, motivation, refereeing — feed in changes and watch how the picture moves.

Example prompts

"What if Haaland is a late scratch — how does that change the City vs United probability picture?"

"Recompute the Brighton scoreline distribution assuming a 25mm rainfall reading at kick-off."

"If both managers are confirmed to rotate three players each, how should I update my expected goals?"

🎯

Generate market angles

Pre-game, ask the AI to surface the half-dozen markets where the line and your model disagree the most — including markets you might not normally check.

Example prompts

"Given my Poisson xG inputs of 1.7 / 1.1, list every market where bookmaker prices look at least 5% off vs fair value."

"Find me three corner markets, two card markets, and one player shot market where Brighton vs Arsenal looks mispriced."

"What's the highest-EV bet in the Bayern vs Dortmund Asian handicap ladder, given my xG model?"

🎓

Educate yourself on the fixture

Ask the AI to explain a fixture's history, tactical context, or relevant statistical patterns — so you're betting from understanding, not vibes.

Example prompts

"Brief me on the tactical pattern of the last 6 Real Madrid vs Barcelona matches — possession share, xG split, key chances."

"What's the historical scoreline distribution in Premier League fixtures with one home club above the European places and one in the bottom four?"

"What does the xG of 'host nation Saudi Arabia at the World Cup' say about a host-nation premium?"

🔬

Pre-match research workflow

Use the AI as your full pre-match research assistant — replace 5 tabs of spreadsheets and stat sites with a structured prompt sequence.

Example prompts

"Run the full KiqIQ pre-match brief on Atletico Madrid vs Sevilla: form, xG, set-piece exposure, manager record vs each other, and three best market angles."

"Build me a one-line summary I can copy into my bet notes for tonight's 8 PL fixtures."

"Compare the implied probabilities at Pinnacle, Bet365, and Smarkets for the Brighton vs Arsenal 1X2 market and tell me which one is closest to fair."

Ready to try it on tonight's fixtures?

The AI prompt is gated behind sign-up — but the first three queries are on us. No card required.

Open the AI prompt →See in-game use cases