KiqIQ is not a single tool — it is a connected set of models, calculators, and analysis features. This page covers every major use case with step-by-step examples of how to get the most from each one.
Use Case 01
Before any fixture, KiqIQ's predictions hub shows you xG-based probability estimates for every upcoming match. Rather than looking at recent results (which are heavily influenced by variance), you're seeing the underlying attacking and defensive quality of each team expressed as expected goals.
Go to the Match Predictions Hub
Visit /football. Every upcoming fixture shows home team xG, away team xG, and the resulting 1X2 probabilities from the Poisson model. Fixtures are grouped by date and filterable by league.
Identify fixtures where the model shows strong signal
A match where the home team generates 2.1 xG and the away team generates only 0.8 xGA (goals against) is a structural mismatch — the home team's attack is facing a weak defence. The model quantifies this gap as a probability advantage.
Cross-reference with the Poisson calculator
Want to test your own xG assumptions? Head to the Poisson Calculator and enter your own values. If you think the model underestimates the away team because a key home defender is injured, adjust the inputs and see how the probabilities shift.
Note the model tip and confidence level
Each prediction shows the most probable outcome (Home Win / Draw / Away Win) and the confidence percentage. A 62% home win confidence means the model believes the home team wins in 62 out of 100 similar matches.
Use Case 02
The Poisson calculator is KiqIQ's most powerful single tool. Given expected goals for each team, it generates probability distributions across all scorelines — and from those, derives 1X2, over/under, and BTTS probabilities. It is the same model used by professional betting analysts.
Worked Example — Chelsea vs Arsenal
Chelsea home xG avg
1.65
Arsenal away xG avg
1.40
Home advantage adj.
+0.15
Chelsea win prob
44%
Draw prob
25%
Arsenal win prob
31%
Over 2.5 goals
51%
BTTS
55%
Use Case 03
Value betting is the core of profitable sports betting. KiqIQ gives you a multi-tool workflow to systematically find situations where the bookmaker's price implies a lower probability than your model estimates.
Run the Poisson model
Get your model probability for the outcome you are considering (e.g. home win = 52%).
Convert bookmaker odds to implied probability
Enter the bookmaker odds into the Implied Probability Calculator. Subtract the margin using the Fair Odds Calculator to get the true implied probability (e.g. odds of 2.20 at 6% margin → fair implied prob ≈ 43%).
Calculate the edge
Edge = your model probability − fair implied probability. In this example: 52% − 43% = +9% edge. Positive = value. Negative = bookmaker has priced it correctly or you are wrong.
Confirm the EV is positive
EV = (probability × decimal odds) − 1 = (0.52 × 2.20) − 1 = +0.144 (+14.4% EV). A positive EV means this bet is worth making from a mathematical standpoint.
Size the stake with Kelly Criterion
Enter your edge and odds into the Kelly Calculator to get a mathematically optimal stake. Use quarter-Kelly to reduce risk during model calibration periods.
Use Case 04
Most people build accumulators based on gut feel. KiqIQ lets you build them based on model probabilities — selecting only legs where your Poisson estimate shows genuine value, then using the accumulator calculator to see exactly how the margin compounds.
Example: Building a 3-leg Saturday acca
Result: 2-leg acca (Arsenal + BTTS) at combined odds 1.72 × 1.75 = 3.01. Both legs have positive EV — the acca does too.
Use Case 05
Most bettors have no idea whether they are actually profitable. KiqIQ's bet tracker (available to registered users) lets you log every bet, tag it by market and league, and automatically calculate ROI, win rate, average odds, and profitability by segment.
Overall ROI
Total profit ÷ total staked across all logged bets. The single most important performance metric.
ROI by market type
Filter by 1X2, Asian Handicap, over/under, BTTS, goalscorer. Discover which markets you actually beat.
ROI by league
Which leagues are you profitable in? Are you actually good at Serie A or just running lucky?
Average odds vs win rate
If you are betting at average odds of 2.10 but winning 60% of bets, something is wrong with the odds line — investigate.
Strike rate over time
Track whether your win rate is consistent or deteriorating — a sign of a changing market or a closing edge.
Stake efficiency
Are you staking more on higher-confidence bets? Does that segment perform better? The tracker shows you.
Why this matters
Without systematic bet tracking, you are operating on memory — which is optimism-biased. People remember winning bets more vividly than losing ones. The tracker removes that bias with cold data.
Use Case 06
The scoreline tells you what happened. xG tells you whether it was deserved. Use KiqIQ after matches to understand whether a result reflects genuine quality or variance — and update your model accordingly for future analysis.
Scenario: Team wins 3-0 but xG was 0.8 vs 1.9
The winning team massively overperformed their xG — likely due to conversion luck and/or a brilliant goalkeeping display from the loser. The scoreline flatters the winner. Be cautious backing them next match at short odds.
HOW KiqIQ HELPS
Check the pre-match Poisson model vs actual xG — if your model already flagged this as an expected away win, the data confirmed it despite the result.
Scenario: Team loses 0-1 but xG was 2.8 vs 0.4
The losing team dominated the match statistically but were unlucky. Their expected points from this match: 2.6 (near-certain win). The 0-1 loss is a model error only, not a reflection of quality.
HOW KiqIQ HELPS
This team may be undervalued in next week's market if casual bettors react to the poor result. The xG data shows their quality is unchanged.
Scenario: Match ends 0-0 but xG was 1.8 vs 1.7
An attacking match that just did not produce goals. No goalkeeper heroics or poor finishing required — just the natural variance of football. Both teams played as expected; the 0-0 is not a signal of defensive quality.
HOW KiqIQ HELPS
Update your form model with xG values not actual goals. The 0-0 should not suppress either team's offensive projection for future fixtures.
Use Case 07
KiqIQ's arb calculator lets you enter odds from multiple bookmakers and instantly see whether a genuine arbitrage opportunity exists — and how much to stake on each outcome to lock in guaranteed profit regardless of the result.
Arb Calculation Example
Total staked: £100.70 → Guaranteed return: £100.00 → Not an arb (return < 100%)
Try finding better odds on any leg to push total implied probability below 100%.
Use Case 08
Once you have identified a value bet, the next question is how much to stake. The Kelly Criterion calculator gives you a mathematically optimal stake based on your perceived edge and the odds. Most bettors use quarter-Kelly or half-Kelly to reduce variance.
Kelly Formula
f* = (bp − q) ÷ b
where b = decimal odds − 1, p = your win probability, q = 1 − p
Example: odds 2.10, model probability 55%
f* = (1.10 × 0.55 − 0.45) ÷ 1.10 = 14.1% of bankroll
Quarter-Kelly stake: 14.1% × 0.25 = 3.5% of bankroll
Use Case 09
KiqIQ's fixture data, prediction probabilities, and AI assistant give fantasy managers a data edge over managers relying on FPL podcast consensus. Here is how to use each feature for fantasy decisions.
Captaincy decisions
Compare upcoming fixture difficulty using prediction probabilities. A striker with a 58% home win fixture is a better captaincy base than one with a 45% away win fixture — independent of price.
Transfer target xG analysis
Ask the AI assistant about a player's recent xG per 90 minutes. A striker on 0 goals but 4.2 xG in 4 matches is due positive regression — buy before the price rises.
Fixture difficulty across 5 GWs
Use the predictions hub to map each team's next 5 fixtures. A forward facing 3 of the bottom-6 defences in 5 GWs is a strong differential/template pick.
Budget player efficiency
Use the goals-per-game calculator to find players generating high xG at low FPL price points — value picks that are being ignored by the consensus.
Differential spotting
Low-ownership players with strong underlying xG who face easy fixtures. Ask the AI to help assess whether the differential risk is justified by the numbers.
Rotation risk assessment
Ask the AI about a player's rotation risk based on their squad position, manager's selection patterns, and competition schedule.
Use Case 10
You do not need to bet to get value from KiqIQ. Fans who understand xG, PPDA, and match probability think about the game more clearly — and have better conversations about it.
Use Case 11
KiqIQ's education library covers every football betting market with worked examples, mathematical explanations, and calculator links. Use the AI assistant to ask follow-up questions until you fully understand a concept.
Use Case 12
KiqIQ's tools are the building blocks for a personal betting model. You do not need coding skills — just a systematic process and the right calculators.
Data collection
Use the AI assistant to get xG, xGA, and form data for the teams you follow. Build a simple spreadsheet tracking home/away xG by team.
Match probability modelling
Use the Poisson calculator as your model engine. Enter your xG estimates for each fixture and record the output probabilities.
Market comparison
Use the implied probability + fair odds calculators to strip bookmaker margins and compare your model probability with the fair market price.
Bet selection
Only select bets where your model probability exceeds the fair implied probability by 3%+. Track every decision with the bet tracker.
Calibration
After 50+ bets, review in the bet tracker: is your model over- or under-estimating home wins? Adjust your xG inputs or home advantage factor.
All 28 calculators, the predictions hub, tools, and glossary are free with no account needed. Create a free account to unlock AI questions and bet tracking.
