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The 15-minute Profit Window

February 21, 2026

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9 min read

Before we get into Part 3 of our data analysis, a quick reminder that you can currently save $100 on a Gecko Edge membership with coupon code: 100GECKO

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Part 1: We Analysed 8,439 Bets. Here’s What We Found. Part 2: The Bets That Win (And The Ones You Should Never Touch)

In Part 2, we showed you the +EV pre-match bets that had the strongest profit signals.

Today, we move InPlay and this is perhaps the one you have been waiting for, as it is the most actionable one so far.

5,465 in-play recommendations. 66 competitions. +208.07 points profit on flat 1pt stakes.

We quickly identified that the profit doesn’t spread evenly. It concentrates in a few places with one in particular.

First Half vs Second Half:

Let’s start with the simplest split in the data.

First-half entries (1-45′): 2,324 bets | -6.33 pts | -0.27% ROI | 48.9% strike rate

Second-half entries (46-90′): 2,923 bets | +203.10 pts | +6.95% ROI | 46.8% strike rate

First-half in-play entries are essentially a coin flip. You’re not losing much, but you’re not making anything either. Every point of in-play profit — all +208 points of it — comes from second-half entries.

Why? Because by half-time, the model has real match data to work with. It’s seen 45 minutes of actual play: shots, possession patterns, xG accumulation, which team is pressing, which team is sitting deep. Pre-match, the model relies on historical data and projections. In-play, it’s reading the game in real time. And that information advantage doesn’t properly kick in until the second half.

But it gets more specific than just “bet in the second half.”

The Six Windows

We split every in-play recommendation by the minute it was entered:

1-15′: 231 bets | +19.43 pts | +8.41% ROI | 55.7% SR
16-30′: 708 bets | -26.60 pts | -3.76% ROI | 49.7% SR
31-45′: 1,385 bets | +0.84 pts | +0.06% ROI | 47.4% SR
46-60′: 2,093 bets | +186.93 pts | +8.93% ROI | 48.9% SR
61-75′: 611 bets | +24.37 pts | +3.99% ROI | 42.8% SR
76-90′: 217 bets | -7.63 pts | -3.52% ROI | 38.4% SR

The 46-60 minute window generates +186.93 points — from a single 15-minute entry window.

The 1-15′ window shows a decent ROI (+8.41%) but from only 231 bets — too small to draw firm conclusions. The 16-30′ window actively loses money. The 31-45′ window is dead flat. Then 46-60′ explodes.

After 60 minutes, returns start fading. The 61-75′ window is still positive (+3.99%) but with a noticeably lower strike rate (42.8%) suggesting more supporting research or match watching is required to be more selective. By 76-90′, we’re see a drop off in profits— however one reason for this is that we see a lot of prompts run at 89’+ which may influence the overall performance due to the very late and high volatility of this period.
We may look to break our analysis down into 5 min slots during this period in future analysis, or even look at 10 minute slots throughout the match for more reflective analysis.

One thing is clear though, if you’re planning to bet or trade InPlay, include the InPlay analysis, during the 46-60 minute window, to improve your performance.

Why Is This Time Period So Important?

It’s not random. Three things converge in this window:

1. Maximum information, maximum time. The model has 45+ minutes of real match data — enough to read patterns accurately — and there are still 30+ minutes for the position to play out. Earlier than 46′ and the data is thinner. Later than 60′ and the remaining time compresses your edge.

2. Market inefficiency peaks. Bookmakers adjust their in-play odds based on the scoreline and time elapsed, but they’re slower to account for underlying match dynamics — shot patterns, xG accumulation, pressing intensity. At 46-60′, the gap between what the scoreline says and what the match data says is often at its widest.

3. Tactical shifts. Managers make substitutions. Teams trailing start pushing forward. Teams leading start protecting. The 46-60′ window captures the start of these shifts — and the model picks up on the resulting changes in goal probability before the market fully prices them in.

The Key Profit Signal: BTTS Yes at 46-75′

This is the single most profitable finding in the entire 8,439-bet dataset.

BTTS Yes entered between 46-60′: 546 bets | +121.78 pts | +22.30% ROI

BTTS Yes entered between 46-75′: 690 bets | +187.96 pts | +27.24% ROI

+27.24% ROI from 690 bets. Let that sit for a moment.

This is the easiest, actionable, angle for any aspiring trader to focus on when getting started with Gecko Edge. It has a high frequency of success, while it links well with other strategies which you can expand into over time.

Other Notable In-Play Bet Opportunities

Within the 46-60′ window, here’s how every bet type with meaningful volume performed:

Profitable:

BTTS Yes: +22.30% ROI | 546 bets | 48.0% SR
Over 1.5 Goals: +10.78% ROI | 234 bets | 51.3% SR
Match Result Draw: +8.62% ROI | 109 bets | 43.1% SR
Second Half Over 0.5: +7.92% ROI | 61 bets | 73.8% SR
Over 2.5 Goals: +4.98% ROI | 299 bets | 51.2% SR
Over 3.5 Goals: +3.76% ROI | 132 bets | 50.8% SR

Under-performing:

Second Half Over 1.5: -9.69% ROI | 128 bets | 44.5% SR
BTTS No: -29.85% ROI | 62 bets | 45.2% SR
Match Result Away: -7.53% ROI | 45 bets | 35.6% SR

An interesting contrast with pre-match: Over 2.5 Goals, which was slightly negative pre-match (-5.08%), turns positive in-play (+4.98% in the 46-60′ window). With more relevant and live data inputs, the Gecko Edge AI betting models are able to read the in-play goal flow better, resulting in stronger accuracy and higher returns.

Second Half Over 0.5 has a striking 73.8% strike rate from 61 bets in the 46-60′ window. Small sample, but the logic is sound — if the model identifies attacking intent from both sides at the start of the second half, at least one more goal is very likely. For us, we would use this as a positive indicator but potential look higher up the goal markets and/or identify which team is the likely scorer.

Which In-Play Prompts Should You Use

Ten different InPllay prompt types are available through Gecko Edge. However, some are more advanced, being more indicators than directly actionable, gearing them towards specialist trade scenarios.

However, there are two core prompts that any Gecko Edge users should focus on, plus two additional ones for the more willing risk takers.

The workhorses:

InPlay Analysis: 4,229 bets | +188.26 pts | +4.45% ROI
Second Half Planner: 137 bets | +9.08 pts | +6.63% ROI

The specialists (small samples, strong signals):

High Risk / Reward: 29 bets | +17.80 pts | +61.38% ROI
Market Mispricing: 40 bets | +6.12 pts | +15.29% ROI

Under-performers / Specialist Prompts:

First Goal Predictor: 495 bets | +2.25 pts | +0.46% ROI
Late Goals: 181 bets | +2.12 pts | +1.17% ROI
Momentum Shift: 195 bets | -3.30 pts | -1.69% ROI
Lay The Draw: 26 bets | -0.49 pts | -1.88% ROI
Correct Score Trader: 45 bets | -5.12 pts | -11.38% ROI
xG Trends: 44 bets | -11.38 pts | -25.86% ROI

InPlay Analysis is the one to use. It accounts for 77% of all in-play bets and generates 90% of the in-play profit. It’s the prompt that produces the BTTS Yes, Over/Under, and match result recommendations that perform in the 46-60′ window.

Second Half Planner is the natural companion — specifically designed for second-half entries, which is exactly when in-play betting works best.

Market Mispricing and High Risk / Reward show exciting ROI numbers but from very small samples. Worth running alongside InPlay Analysis, but not enough data yet to call them proven.

More specialist prompts such as First Goal Predictor and Late Goals are essentially break-even on direct action but should be used more as indicators as their overal performance will depend on the skill of the trader and the entry points chosen.

What Trends Do We See InPlay?

In-play and pre-match league performance don’t always align. Some of the most interesting reversals:

Germany Bundesliga: mediocre pre-match (-6.56% ROI) but the top in-play performer at +22.31% ROI from 228 bets. In-play markets in major leagues may actually be less efficient than pre-match markets — a counterintuitive finding.

Other strong in-play leagues:

Switzerland Super League: +37.46% ROI (82 bets)
Portugal LigaPro: +35.65% ROI (96 bets)
Australia A-League: +34.99% ROI (112 bets)
Scotland Premiership: +28.28% ROI (124 bets)
Germany 2. Bundesliga: +14.97% ROI (200 bets)
Italy Serie A: +12.68% ROI (239 bets)
Spain La Liga: +11.97% ROI (218 bets)

Leagues to avoid in-play:

Saudi Arabia Professional League: -40.01% ROI (146 bets)
Poland Ekstraklasa: -25.61% ROI (138 bets)
France Ligue 1: -16.14% ROI (163 bets)

The Saudi league is a league that we have never placed a bet or trade on and based on the stats, we don’t see that changing anytime soon. We recommend skipping it.

What EV% Should We Target In-Play?

In Part 2, we showed that every pre-match EV% band is profitable. In-play, it’s different — there’s a floor.

EV 0-5%: -5.27% ROI | 285 bets (negative performance so far)
EV 5-10%: +9.29% ROI | 787 bets
EV 10-15%: +1.35% ROI | 348 bets
EV 15-20%: +5.57% ROI | 193 bets
EV 20-30%: +19.22% ROI | 165 bets
EV 30-50%: +8.67% ROI | 92 bets
EV 50%+: -4.14% ROI | 35 bets

In-play, anything below 5% EV is negative. The minimum threshold that you should consider for in-play should be 5% EV.

The 5-10% band is the volume sweet spot — 787 bets at +9.29% ROI. The 20-30% band delivers the highest ROI (+19.22%) but with much lower volume.

At the extreme end, 50%+ EV in-play actually loses money. When the model claims a massive in-play edge, it’s more likely a miss-read of rapidly changing match conditions than a genuine opportunity. Treat very high EV% in-play with a level of scepticism. If it does not match what you are seeing, move on.

AI Betting and Trading InPlay: Key Takeaways

When to enter in-play:

The 46-60′ window is the prime zone
61-75′ is still positive but fading
First-half entries are break-even — save your stakes
76-90′ requires trader assessment

What to bet in-play:

BTTS Yes at 46-75′ is the golden angle (+27.24% ROI, 690 bets)
Over 1.5 Goals at 46-60′ (+10.78% ROI)
Over 2.5 Goals turns positive in-play (unlike pre-match)

Which prompts to use:

InPlay Analysis — the most popular prompt
Second Half Planner — the natural companion
Skip xG Trends and Correct Score Trader – for more advanced traders only

Filters:

Minimum 5% EV in-play (below 5% loses money)
Avoid Saudi Pro League

What’s We’ll Be Sharing Next

Part 4: The Gecko Edge Playbook

This is where it all comes together. We’re taking every finding from Parts 1-3 — the bet types, the timing windows, the Sanity Score framework, the EV% bands, the league patterns, the prompt selection — and combining them into a single, actionable decision framework.

One document. Clear rules. Pre-match and in-play.