Who lands the most significant strikes per 15 minutes in the UFC?
A career leaderboard built from every fight's stat sheet, for a weight class, with a minimum number of fights so small samples do not top it.
Code verified October 10, 2026. One call to get_leaders, 5 credits.
The call
stat is one of sig_landed_per_15, sig_absorbed_per_15, sig_accuracy, sig_defense, td_per_15, td_accuracy, td_defense, knockdowns, sub_attempts_per_15, control_share or finish_rate.
import requests
import pandas as pd
API_KEY = "YOUR_API_KEY"
resp = requests.post(
"https://mcp.fighterapi.com/v1/get_leaders",
headers={"x-api-key": API_KEY},
json={
"stat": "sig_landed_per_15",
"weight_class": "Lightweight",
"since": 2020,
"min_fights": 8,
"limit": 15,
},
timeout=60,
)
resp.raise_for_status()
data = resp.json()["data"]
leaders = pd.DataFrame(data["leaders"])
print(data["label"], "(at least", data["min_fights"], "fights)")
print(leaders[["rank", "name", "fights", "value"]].round(1))
Replace YOUR_API_KEY with a key from your dashboard. Python needs requests and pandas (pip install requests pandas). JavaScript runs on Node 18 or newer, or in the browser.
What comes back
The data object of the response, trimmed to the first rows. Every field is real output from the run above.
{
"stat": "sig_landed_per_15",
"label": "significant strikes landed per 15 min",
"min_fights": 8,
"leaders": [
{
"rank": 1,
"fighter_id": "2502364",
"name": "King Green",
"weight_class": "Lightweight",
"fights": 19,
"value": 123.871
},
{
"rank": 2,
"fighter_id": "4425604",
"name": "Terrance McKinney",
"weight_class": "Lightweight",
"fights": 14,
"value": 119.303
},
"...13 more"
],
"count": 15
}What to do next
- get_fighter (5 credits). Look up any name from the list for the full record and rates.
- get_ratings (2 credits). See whether the volume strikers are also the highest-rated.
More guides
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