What is the best solo mining strategy? (Probability)

Understanding Solo Mining Mechanics

1. Solo mining involves a miner attempting to solve a block independently without joining a mining pool.

2. The probability of successfully mining a block depends on the miner’s hash rate relative to the total network hash rate.

3. A miner with 0.1% of the network’s computational power has, on average, a 0.1% chance per block to find the solution first.

4. Block discovery follows a Poisson process; intervals between successes are exponentially distributed.

5. Variance is extremely high—long dry spells are statistically expected even for relatively large solo miners.

Hash Rate Thresholds and Feasibility

1. For Bitcoin, solo mining became practically infeasible below ~100 PH/s after 2016 due to rising difficulty and ASIC dominance.

2. On smaller proof-of-work chains like Monero or Ravencoin, solo mining remains viable at sub-1 GH/s levels if network hash rate stays low.

3. A consistent 50 MH/s setup on a chain with 200 MH/s total network hash rate yields an average block every 4 blocks—or roughly once every 40 minutes.

4. Real-world variance means actual inter-block times may range from seconds to several hours despite theoretical averages.

5. Hardware uptime, clock stability, and stratum connection latency directly impact effective probability—not just raw hash rate.

Block Propagation and Orphan Risk

1. Even when a solo miner finds a valid block, propagation delay can cause it to be orphaned if another miner broadcasts a competing block faster.

2. Orphan rates rise sharply for miners located far from major internet exchange points or running outdated node software.

3. Running a full node with optimized network settings (e.g., compact blocks, high outbound peers) reduces orphan probability by up to 37% according to empirical testnet data.

4. Blocks mined within 2 seconds of a prior block have over 60% higher orphan likelihood than those spaced >10 seconds apart.

5. Geographic proximity to top-10 mining pools’ relay networks indirectly increases solo success probability through faster confirmation visibility.

Difficulty Adjustment Cycles

1. Chains with short retargeting intervals—such as Ethereum Classic’s 10-block window—introduce volatility that benefits adaptive solo miners who monitor hash flux.

2. A sudden 30% network hash rate drop increases solo miner’s per-block win probability proportionally, but only until the next adjustment.

3. Some solo operators switch coins mid-cycle based on real-time difficulty-to-hash-ratio metrics scraped from explorers.

4. Historical analysis of Zcash shows solo miners captured 8.2% of blocks during periods where network hash rate fell below 25% of its 30-day moving average.

5. Predictive models using moving averages of difficulty and hash rate improve timing decisions—but do not eliminate variance inherent in cryptographic lotteries.

Frequently Asked Questions

Q: Does increasing nonce range improve solo mining probability? No. Nonce exhaustion is irrelevant in modern mining. ASICs iterate nonces at hardware speed; probability depends solely on hash attempts per second, not nonce space size.

Q: Can solo mining profitability be modeled with binomial distribution? Not accurately. Block discovery is memoryless and continuous; binomial assumes fixed trials. Poisson or exponential distributions reflect reality more precisely.

Q: Is GPU solo mining still viable on any major chain? Yes—on Kaspa, which uses GHOSTDAG and allows competitive GPU mining at current network hash rates.

Q: Does using a custom mining rig kernel affect win probability? Only indirectly. Kernel optimizations reduce driver overhead and thermal throttling, sustaining peak hash rate longer—thus preserving baseline probability over time.