Crypto Sector Performance — L1, DeFi, AI, Gaming, Meme vs BTC

What does Crypto Sector Performance do?

Crypto Sector Performance tracks and compares price performance across six major crypto market sectors — L1, L2, DeFi, AI, Gaming, and Meme — by fetching historical prices from DefiLlama's coin API for 35 representative tokens. It outputs per-token price changes, per-sector aggregates (7d and 30d averages), and a portfolio-level summary that identifies which sectors are receiving capital inflows, which fit the current market cycle, and which carry the best risk-adjusted returns.

Why use Crypto Sector Performance?

• Sector rotation visibility in seconds. The sector_rotation_map in the portfolio summary groups all six sectors into receiving_capital, holding_capital, and losing_capital buckets so you can see where institutional and retail money is moving at a glance.
• BTC-relative strength scoring. Every sector gets a vs_btc_7d_pct and a relative_strength_vs_btc label (strongly_outperforming → strongly_underperforming) — the essential benchmark for judging whether a sector rally is alpha or just beta.
• Market cycle fit signal. The crypto_cycle_fit field maps each sector to the current BTC market phase (bull impulse, consolidation, or risk-off) so you can weight your exposure toward historically cycle-appropriate sectors.
• Momentum quality beyond raw returns. The momentum_quality field (accelerating / stable / decelerating / reversing) shows whether recent weekly gains are faster or slower than the monthly pace — catching blow-off tops and early trend reversals.
• Flat-rate pricing for full-portfolio scans. At $0.01 per run for all 35 tokens across 6 sectors, it is cost-effective to run on every scheduled interval without metering individual coin lookups.

How to use Crypto Sector Performance

1. Go to the Apify Store and find Crypto Sector Performance.
2. Click Try for free to open the input configuration page.
3. In the Sectors to Include field, specify which sectors to analyze (default: all six — L1, L2, DeFi, AI, Gaming, Meme).
4. Click Run. The actor fetches current prices and historical 7d/30d prices for all tokens in the selected sectors.
5. Consume the dataset — it contains four record types: token (one per coin), sector_summary (one per sector), sector_rank (sorted leaderboard), and portfolio_summary (cross-sector synthesis).

Input

Field	Type	Default	Description
sectors	array of strings	["L1","L2","DeFi","AI","Gaming","Meme"]	Which sectors to include. Valid values: L1, L2, DeFi, AI, Gaming, Meme.

Output

[
  {
    "type": "token",
    "sector": "L1",
    "symbol": "ETH",
    "current_price": 3412.55,
    "change_7d_pct": 8.32,
    "change_30d_pct": 14.71,
    "fetched_at": "2026-09-02T10:31:00Z"
  },
  {
    "type": "sector_summary",
    "sector": "AI",
    "token_count": 5,
    "avg_change_7d_pct": 12.41,
    "avg_change_30d_pct": 21.83,
    "best_7d": "TAO",
    "best_7d_pct": 22.14,
    "worst_7d": "AGIX",
    "worst_7d_pct": 3.81,
    "sector_health_score": 88,
    "institutional_interest_signal": "growing",
    "retail_fomo_index": 74,
    "momentum_score": 79,
    "rotation_signal": "accumulate",
    "breadth_positive_pct": 100.0,
    "vs_btc_7d_pct": 6.23,
    "trend_direction": "strong_up",
    "sector_performance_tier": "top_performer",
    "momentum_quality": "accelerating",
    "sector_breadth": "very_broad",
    "rotation_status": "receiving_capital",
    "crypto_cycle_fit": "fits_current_cycle",
    "relative_strength_vs_btc": "outperforming",
    "valuation_signal": "fairly_valued",
    "catalyst_presence": "known_catalyst",
    "fetched_at": "2026-09-02T10:31:00Z"
  },
  {
    "type": "portfolio_summary",
    "sector_leaderboard": [
      {"rank": 1, "sector": "AI", "avg_7d_pct": 12.41, "momentum_score": 79, "sector_performance_tier": "top_performer"},
      {"rank": 2, "sector": "Meme", "avg_7d_pct": 9.83, "momentum_score": 71, "sector_performance_tier": "top_performer"}
    ],
    "best_risk_adjusted_sector": "L1",
    "worst_performing_sector": {
      "sector": "Gaming",
      "avg_7d_pct": -4.12,
      "reason": "Worst 7d avg return -4.1%; momentum is decelerating."
    },
    "sector_rotation_map": {
      "receiving_capital": ["AI", "Meme"],
      "holding_capital": ["L1", "DeFi"],
      "losing_capital": ["L2", "Gaming"]
    },
    "macro_environment_fit": ["AI", "Meme"],
    "btc_7d_pct": 6.18,
    "sectors_analyzed": 6,
    "fetched_at": "2026-09-02T10:31:00Z"
  }
]

Data fields

Field	Description
sector	Sector name: L1, L2, DeFi, AI, Gaming, or Meme
symbol	Token ticker (e.g. ETH, UNI, TAO)
current_price	Current USD price from DefiLlama
change_7d_pct	Price change over 7 days (%)
change_30d_pct	Price change over 30 days (%)
avg_change_7d_pct	Average 7d performance across all sector tokens
avg_change_30d_pct	Average 30d performance across all sector tokens
sector_health_score	0–100 health score based on 7d and 30d averages
momentum_score	0–100 momentum: 7d weighted 70%, 30d pace 30%
rotation_signal	accumulate / hold / reduce / avoid
breadth_positive_pct	% of sector tokens with positive 7d return (market breadth)
vs_btc_7d_pct	Sector 7d average minus BTC 7d return (alpha vs BTC)
trend_direction	strong_up / up / sideways / down / strong_down
sector_performance_tier	top_performer / outperformer / average / underperformer / worst_performer
momentum_quality	accelerating / stable / decelerating / reversing
sector_breadth	very_broad / broad / mixed / narrow / negative_breadth
rotation_status	receiving_capital / holding_capital / losing_capital
crypto_cycle_fit	fits_current_cycle / neutral / cycle_headwind
relative_strength_vs_btc	strongly_outperforming → strongly_underperforming
valuation_signal	undervalued_sector / fairly_valued / expensive_sector
catalyst_presence	known_catalyst / potential_catalyst / negative_catalyst / no_catalyst
institutional_interest_signal	high / growing / low
retail_fomo_index	0–100 retail FOMO intensity (highest for Meme, lowest for L1)
competitive_moat	strong / moderate / fragmented
best_risk_adjusted_sector	Sector with highest Sharpe-equivalent (return / within-sector volatility)
sector_rotation_map	Dict grouping sectors by capital flow status
macro_environment_fit	Sectors that historically fit the current BTC cycle phase
fetched_at	ISO 8601 timestamp of the data pull

Cost estimation

Pricing model: $0.01 flat per run — fetches all 35 tokens across all 6 sectors.

Scenario	Runs	Estimated cost
One-off sector snapshot	1 run	$0.01
Daily monitoring (30 days)	30 runs	$0.30
Hourly monitoring (7 days)	168 runs	$1.68

FAQ

Q: Which tokens are included for each sector? A: The default token set is: L1 (BTC, ETH, SOL, AVAX, BNB, SUI, ADA), L2 (ARB, OP, MATIC, STRK, MNT), DeFi (UNI, AAVE, CRV, MKR, PENDLE, MORPHO), AI (FET, RNDR, TAO, WLD, AGIX), Gaming (AXS, SAND, MANA, IMX, RON), and Meme (DOGE, SHIB, PEPE, BONK, WIF). The actor uses DefiLlama CoinGecko IDs for reliable price lookups.

Q: How does crypto_cycle_fit work? A: The actor uses the BTC 7-day return as a proxy for the current market cycle phase. If BTC is up >5% over 7 days (bull impulse), sectors like AI, Meme, and Gaming historically outperform and are labeled fits_current_cycle. If BTC is down >5% (risk-off), L1 and L2 are flagged as relatively defensive. During consolidation (-5% to +5%), DeFi and L1 tend to hold up best.

Q: Can I add custom tokens or sectors? A: The current version uses a fixed token list defined in the actor source. Custom token sets are planned for a future release. For now, run the default scan and filter post-processing.

Disclaimer: Price data is sourced from DefiLlama's public CoinGecko-backed endpoints and reflects best-available historical prices. Computed analytics signals (rotation status, cycle fit, momentum quality) are quantitative heuristics for research purposes only and do not constitute financial or investment advice.

Keywords: crypto sector performance tracker, crypto rotation strategy, DeFi sector analytics, L1 vs L2 performance, AI crypto sector, meme coin sector analysis, Bitcoin cycle fit, sector momentum score, crypto market breadth, altcoin sector comparison

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