How Monad parallelizes.
Real numbers from 1,224,981 blocks indexed over the last 7 days. The chart is the chain’s parallelism score, day by day. The list below is who caused the contention.
Bars are the chain’s average parallelism score, day by day. The orange line is daily transaction volume (right axis). Together they answer: does Monad parallelize worse under high load, or better?
How many blocks landed in each score bucket. The average is 81.4/100 but the shape tells the truth: most blocks are clean, a long tail is what hurts.
Ranked by total conflicts caused over the window. Click any row to inspect the contract’s parallelism profile.
The chain’s workhorses, ranked by raw tx count over all time pev has indexed. Compare to the contention leaderboard above: popular and contentious are different problems. A well-designed contract can be #1 by usage without ever appearing in the killer list.
One level deeper than the contract list, the exact (contract, slot) pairs causing the most contention. Click to inspect the contract.
Function selectors causing the most outbound conflicts. The contract count column tells the cross-contract story: swap() across 12 different DEXes is a category-wide pattern (the function shape itself is contentious); the same conflict count concentrated on 1 contract is one bad actor. Selectors resolved against 4byte when known.
Stats above are aggregated over blocks #80,823,350 to #82,048,350, roughly the last 7 days of mainnet at current cadence. Conflict counts are absolute (no rate normalization), so contracts with more total transactions naturally appear higher on the list. Names are shown when verified on Sourcify (rare on Monad mainnet right now); otherwise we show the short hex.