Breakouts led the week while sweet spot setups quietly held
Backtest patterns, sweet spot performance, and missed-trade analysis for July 06 to July 10.
THE EDGE THIS WEEK
Selective strength, broad failure pressure
The dominant pattern this week was not broad participation. It was selective follow through in a narrow set of symbols while the scanner as a whole struggled to convert setups into valid breakouts. With just 69 breakouts out of 468 setups, the market rewarded precision more than frequency, and the strongest names produced unusually clean outcome clusters.
The second important pattern was dispersion. High quality symbols delivered elite win rates and near 1R average outcomes, while weak pockets posted low win rates with consistently negative expectancy. That split suggests edge came from filtering for localized strength rather than assuming a favorable environment across the board. Traders looking for active candidates can see live setups in the scanner.
BY THE NUMBERS
Weekly performance snapshot
The headline numbers describe a difficult conversion environment. Average win rate across tracked symbols remained healthy at 65.0%, but scanner-level breakout efficiency was much weaker at 14.7%. That gap matters. It implies the edge lived after selection, not before it. In other words, once traders were in the right names, outcomes were still favorable, but the market offered fewer truly actionable entries than raw setup volume suggested.
The key structural takeaway is that setup count overstated opportunity. The market generated many appearances of pressure and proximity, but only a small share translated into clean expansion.
SWEET SPOT REPORT
The usual setup profile underperformed sharply
The sweet spot profile, defined as pressure below 60 with 3 to 5 bars, materially underperformed its long run baseline. This week it delivered a 32.7% win rate versus a historical 59.2% across 201 trades. That is not a marginal miss. It is a major regime mismatch.
When a setup family underperforms this decisively, the issue is usually not the setup itself but the surrounding market context. Lower pressure, shorter build structures tend to work best when the market is willing to reward early expansion. This week, the low breakout rate suggests the market required either stronger confirmation, more durable trend sponsorship, or cleaner relative strength than this profile typically provides.
Practically, that means traders should treat the sweet spot as conditional rather than automatic. In weak conversion weeks, lighter pressure setups can become traps because they trigger before conviction is broad enough to sustain follow through. The lesson is not to discard the pattern. It is to tighten the context filters around it.
A setup with strong historical expectancy can still fail when the market stops paying for early entries. This week, patience outperformed anticipation.
SYMBOL SPOTLIGHT
Where the signal was clearest
GDX stands out as one of the most informative symbols of the week. It posted a 94.44% win rate across 18 trades with 0.8863 average R, combining both scale and quality. That matters because extreme win rates on 5 or 6 trades can be noise, but 18 trades with that level of consistency points to a durable pattern. When an instrument produces repeated valid outcomes across many opportunities, it often reflects stable sponsorship rather than one-off momentum.
V and ZM showed a similar profile: 93.33% win rates across 15 trades each, with average R near 0.87. The notable feature here is not just the win rate. It is the combination of high hit rate and strong per-trade payoff. That pairing suggests entries were not merely surviving. They were progressing efficiently toward targets, which is often a sign of cleaner directional structure and less mean reversion friction.
On the opposite side, JPM and MA are useful cautionary cases. Both logged 13 trades and sub-39% win rates with negative average R. Symbols with this many attempts and persistently poor outcomes often reveal a recurring trap pattern: enough movement to attract breakout logic, but insufficient continuation to generate payoff. In research terms, these are not random misses. They are examples of where the market repeatedly advertised strength but failed to monetize it.
The 100% club also deserves attention, especially LLY, URI, and NOW. Perfect win rates across 9, 7, and 6 trades respectively, all with average R around 1, suggest these names aligned cleanly with the dominant microstructure of the week. The pattern here is straightforward: concentrated edge existed, but only in symbols with persistent relative demand.
WHAT THE BOTS MISSED
Filter protection came with a meaningful opportunity cost
The bots missed 22 trades worth +45.2R, including 4 runners that reached TP3. The largest blocking source was rvol_threshold with 17 misses, followed by spy_alignment with 5. Traders can watch the bots in the Edge Lab.
This distribution suggests the filters were doing exactly what defensive systems are designed to do: reduce participation in ambiguous conditions. The problem is that in a week defined by selective leadership, some of the best trades likely emerged from names that did not look broadly robust on aggregate market or volume metrics. That creates an important design tension. Protection filters help in noisy environments, but they can also suppress the very outlier opportunities that carry weekly performance.
The deeper question is not whether the filters were wrong. It is whether they were too blunt for a market with narrow leadership. Relative volume thresholds, in particular, may need more symbol-sensitive logic. A uniform threshold can exclude valid moves in names where clean trend continuation matters more than headline participation. $SPY alignment misses raise a similar issue. When index confirmation is weak but leadership is concentrated, requiring full alignment can reduce exposure to the best isolated trades.
The missed trade data points to a research priority: adaptive filters may outperform static filters when market strength is fragmented rather than broad.
SECTOR HEAT MAP
Breakouts clustered in a few productive pockets
Technology led with 16 breakouts, followed by ETFs with 9 and Consumer with 8. Financials contributed 6, while Healthcare and Chinese ADRs remained smaller but still produced isolated winners. There are also duplicate category labels in the source data, with lowercase consumer adding 4 and lowercase etf adding 4, which likely points to classification inconsistency rather than distinct groups.
The broader pattern is concentration, not balance. Breakouts did not distribute evenly across the market. Instead, they accumulated in sectors capable of sustaining thematic or relative strength while many other areas failed to convert. This fits the week’s main signature: opportunity existed, but it was clustered in specific pockets rather than available everywhere.
Technology’s lead is especially relevant because high-activity environments often lure traders into assuming broad momentum. This week’s scanner results argue the opposite. A leading sector can still contain the majority of valid breakouts even when the aggregate setup universe is weak. That means sector leadership should be treated as a narrowing tool, not proof of general market health.
RESEARCH NOTE
When breakout rates collapse, symbol selection becomes the strategy
This week offers a useful research principle: low market-level breakout efficiency does not automatically destroy edge. It redistributes edge. The scanner produced 468 setups but only 69 breakouts, while many individual symbols still posted excellent win rates and average R values. That combination tells us the strategy problem shifted from pattern detection to pattern discrimination.
For traders, the implication is important. In favorable broad conditions, a decent setup can be enough because the market supplies follow through. In selective conditions, a decent setup is rarely enough. The difference between winning and losing comes from whether the symbol has independent sponsorship strong enough to overcome weak market-wide conversion. That is why names like LLY, URI, and GDX mattered more than the raw scanner count.
The practical research question for next week is simple: which pre-entry variables best identify isolated strength when the general breakout tape is poor? Candidate areas include sector-relative momentum, repeated symbol-level success frequency, and softer treatment of broad market alignment when a symbol’s own structure is unusually strong. If breakout rates stay compressed, the traders who adapt fastest will be the ones who stop asking, “How many setups are there?” and start asking, “Which symbols keep proving they deserve risk?”