Stat Leaders
See who leads every division. Rank UFC fighters by CCR and TSR, striking, grappling, and control—with every metric measured against their weight class peers.
Makwan Amirkhani
Featherweight
86.1
CCR
Alan Patrick
Lightweight
86.1
CCR
Montserrat Conejo Ruiz
Women's Strawweight
86.1
CCR
Aleksa Camur
Light Heavyweight
86.0
CCR
Erick Gonzalez
Lightweight
86.0
CCR
Istela Nunes
Women's Strawweight
86.0
CCR
Marcelo Rojo
Featherweight
86.0
CCR
Niko Price
Welterweight
85.9
CCR
Michelle Waterson-Gomez
Women's Strawweight
85.9
CCR
Alex Oliveira
Welterweight
85.9
CCR
Jeremy Stephens
Lightweight
85.8
CCR
Hu Yaozong
Middleweight
85.8
CCR
Antonio Arroyo
Middleweight
85.7
CCR
Ashlee Evans-Smith
Women's Bantamweight
85.7
CCR
Kazula Vargas
Lightweight
85.6
CCR
Nazim Sadykhov
Lightweight
85.5
CCR
Tafon Nchukwi
Middleweight
85.5
CCR
Aaron Phillips
Bantamweight
85.5
CCR
Marlon Moraes
Bantamweight
85.4
CCR
Hyder Amil
Featherweight
85.4
CCR
Mike Rodriguez
Light Heavyweight
85.4
CCR
Johnny Eduardo
Bantamweight
85.2
CCR
Khalid Taha
Bantamweight
85.1
CCR
Sasha Palatnikov
Welterweight
85.0
CCR
Warlley Alves
Middleweight
85.0
CCR
Randy Costa
Bantamweight
84.7
CCR
Erik Silva
Featherweight
84.6
CCR
Fernie Garcia
Featherweight
84.5
CCR
Tai Tuivasa
Heavyweight
84.5
CCR
Jamie Siraj
Bantamweight
84.5
CCR
Mateus Mendonca
Flyweight
84.4
CCR
Livinha Souza
Women's Strawweight
84.4
CCR
Mariya Agapova
Women's Flyweight
84.3
CCR
Genaro Valdez
Lightweight
84.3
CCR
Cynthia Calvillo
Women's Strawweight
84.2
CCR
Mike Jackson
Welterweight
84.2
CCR
Rafael Cerqueira
Light Heavyweight
84.1
CCR
Omar Morales
Lightweight
84.1
CCR
Julian Marquez
Middleweight
84.1
CCR
Niklas Stolze
Lightweight
84.0
CCR
Khama Worthy
Lightweight
83.9
CCR
Denis Tiuliulin
Middleweight
83.8
CCR
Shannon Ross
Flyweight
83.6
CCR
Anton Turkalj
Light Heavyweight
83.6
CCR
Josh Parisian
Heavyweight
83.6
CCR
Herbert Burns
Featherweight
83.6
CCR
Alan Baudot
Heavyweight
83.6
CCR
Priscila Cachoeira
Women's Bantamweight
83.5
CCR
Kris Moutinho
Bantamweight
83.4
CCR
Takashi Sato
Welterweight
83.3
CCR
| Rank | Fighter | Weight class | CCR | Percentile | Percentile per weight class | SLpM | TD / min |
|---|---|---|---|---|---|---|---|
| 1001 | Makwan Amirkhani | Featherweight | 86.1 | 10.3% | 7.7% | 1.0 | 0.4 |
| 1002 | Alan Patrick | Lightweight | 86.1 | 10.2% | 10.3% | 2.6 | 0.0 |
| 1003 | Montserrat Conejo Ruiz | Women's Strawweight | 86.1 | 10.1% | 9.6% | 2.7 | 0.1 |
| 1004 | Aleksa Camur | Light Heavyweight | 86.0 | 10.0% | 16.9% | 4.5 | 0.0 |
| 1005 | Erick Gonzalez | Lightweight | 86.0 | 10.0% | 9.7% | 2.4 | 0.4 |
| 1006 | Istela Nunes | Women's Strawweight | 86.0 | 9.9% | 8.2% | 4.3 | 0.0 |
| 1007 | Marcelo Rojo | Featherweight | 86.0 | 9.8% | 7.0% | 4.8 | 0.0 |
| 1008 | Niko Price | Welterweight | 85.9 | 9.7% | 8.6% | 4.9 | 0.1 |
| 1009 | Michelle Waterson-Gomez | Women's Strawweight | 85.9 | 9.6% | 6.8% | 2.8 | 0.1 |
| 1010 | Alex Oliveira | Welterweight | 85.9 | 9.5% | 7.9% | 4.2 | 0.1 |
| 1011 | Jeremy Stephens | Lightweight | 85.8 | 9.4% | 9.0% | 2.3 | 0.0 |
| 1012 | Hu Yaozong | Middleweight | 85.8 | 9.3% | 15.7% | 1.7 | 0.0 |
| 1013 | Antonio Arroyo | Middleweight | 85.7 | 9.2% | 14.8% | 1.7 | 0.0 |
| 1014 | Ashlee Evans-Smith | Women's Bantamweight | 85.7 | 9.1% | 10.2% | 0.8 | 0.0 |
| 1015 | Kazula Vargas | Lightweight | 85.6 | 9.1% | 8.3% | 1.8 | 0.0 |
| 1016 | Nazim Sadykhov | Lightweight | 85.5 | 9.0% | 7.6% | 4.7 | 0.1 |
| 1017 | Tafon Nchukwi | Middleweight | 85.5 | 8.9% | 13.9% | 5.1 | 0.1 |
| 1018 | Aaron Phillips | Bantamweight | 85.5 | 8.8% | 6.7% | 1.1 | 0.2 |
| 1019 | Marlon Moraes | Bantamweight | 85.4 | 8.7% | 6.0% | 3.3 | 0.0 |
| 1020 | Hyder Amil | Featherweight | 85.4 | 8.6% | 6.3% | 7.3 | 0.0 |
| 1021 | Mike Rodriguez | Light Heavyweight | 85.4 | 8.5% | 15.6% | 3.3 | 0.0 |
| 1022 | Johnny Eduardo | Bantamweight | 85.2 | 8.4% | 5.3% | 3.4 | 0.1 |
| 1023 | Khalid Taha | Bantamweight | 85.1 | 8.3% | 4.7% | 2.1 | 0.0 |
| 1024 | Sasha Palatnikov | Welterweight | 85.0 | 8.3% | 7.2% | 0.4 | 0.0 |
| 1025 | Warlley Alves | Middleweight | 85.0 | 8.2% | 13.0% | 2.9 | 0.0 |
| 1026 | Randy Costa | Bantamweight | 84.7 | 8.1% | 4.0% | 5.8 | 0.0 |
| 1027 | Erik Silva | Featherweight | 84.6 | 8.0% | 5.6% | 1.5 | 0.2 |
| 1028 | Fernie Garcia | Featherweight | 84.5 | 7.9% | 4.9% | 1.9 | 0.0 |
| 1029 | Tai Tuivasa | Heavyweight | 84.5 | 7.8% | 14.5% | 2.6 | 0.0 |
| 1030 | Jamie Siraj | Bantamweight | 84.5 | 7.7% | 3.3% | 2.2 | 0.0 |
| 1031 | Mateus Mendonca | Flyweight | 84.4 | 7.6% | 5.4% | 1.4 | 0.2 |
| 1032 | Livinha Souza | Women's Strawweight | 84.4 | 7.5% | 5.5% | 0.7 | 0.2 |
| 1033 | Mariya Agapova | Women's Flyweight | 84.3 | 7.4% | 12.3% | 5.0 | 0.0 |
| 1034 | Genaro Valdez | Lightweight | 84.3 | 7.4% | 6.9% | 3.7 | 0.0 |
| 1035 | Cynthia Calvillo | Women's Strawweight | 84.2 | 7.3% | 4.1% | 5.0 | 0.1 |
| 1036 | Mike Jackson | Welterweight | 84.2 | 7.2% | 6.5% | 5.2 | 0.0 |
| 1037 | Rafael Cerqueira | Light Heavyweight | 84.1 | 7.1% | 14.3% | 1.6 | 0.0 |
| 1038 | Omar Morales | Lightweight | 84.1 | 7.0% | 6.2% | 2.9 | 0.0 |
| 1039 | Julian Marquez | Middleweight | 84.1 | 6.9% | 12.2% | 7.6 | 0.0 |
| 1040 | Niklas Stolze | Lightweight | 84.0 | 6.8% | 5.5% | 2.3 | 0.0 |
| 1041 | Khama Worthy | Lightweight | 83.9 | 6.7% | 4.8% | 4.0 | 0.0 |
| 1042 | Denis Tiuliulin | Middleweight | 83.8 | 6.6% | 11.3% | 3.6 | 0.1 |
| 1043 | Shannon Ross | Flyweight | 83.6 | 6.5% | 4.1% | 4.9 | 0.0 |
| 1044 | Anton Turkalj | Light Heavyweight | 83.6 | 6.5% | 13.0% | 2.9 | 0.2 |
| 1045 | Josh Parisian | Heavyweight | 83.6 | 6.4% | 13.2% | 2.9 | 0.1 |
| 1046 | Herbert Burns | Featherweight | 83.6 | 6.3% | 4.2% | 2.0 | 0.1 |
| 1047 | Alan Baudot | Heavyweight | 83.6 | 6.2% | 11.8% | 5.5 | 0.0 |
| 1048 | Priscila Cachoeira | Women's Bantamweight | 83.5 | 6.1% | 8.2% | 4.7 | 0.0 |
| 1049 | Kris Moutinho | Bantamweight | 83.4 | 6.0% | 2.7% | 2.3 | 0.0 |
| 1050 | Takashi Sato | Welterweight | 83.3 | 5.9% | 5.8% | 1.3 | 0.1 |
Analytics guide
CCR
What it calculates
Current Competitiveness Rating (CCR): a composite score—like an Elo rating in chess—that evaluates advanced striking, grappling, pace, and opponent-quality stats into one number.
Why it matters
Weights recent performance much more heavily than older fights and incorporates factors like age. Use it to see who is fighting at an elite level right now.
TSR
What it calculates
True Skill Rating (TSR): the same composite approach applied across a fighter’s full UFC body of work, like an Elo rating built from advanced stats.
Why it matters
Does not overweight recency or adjust for age—it is a pure career evaluative metric. Helpful for separating sustained elite careers from short hot streaks.
SLpM
What it calculates
Total Significant Strikes Landed ÷ Total Fight Time (minutes)
Why it matters
Captures offensive pace and sustained scoring output — high SLpM forces opponents to fight at your tempo.
SApM
What it calculates
Total Significant Strikes Absorbed ÷ Total Fight Time (minutes)
Why it matters
Shows defensive efficiency and risk exposure — low SApM usually means better defense, distance management, and fewer damaging exchanges.
KD/M
What it calculates
Total Knockdowns ÷ Total Fight Time (minutes)
Why it matters
Measures a fighter’s ability to create high-impact, fight-changing moments that swing rounds or lead to finishes.
TD/M
What it calculates
Total Takedowns Landed ÷ Total Fight Time (minutes)
Why it matters
Signals wrestling pace and phase control — fighters who can reliably force grappling exchanges can neutralize dangerous strikers.
CTRL
What it calculates
Total Control Time ÷ Total Fight Time (minutes)
Why it matters
Quantifies positional dominance and round-winning leverage — control time often correlates with judges’ scoring and opponent suppression.
SUB/M
What it calculates
Total Submission Attempts ÷ Total Fight Time (minutes)
Why it matters
Reflects finishing threat on the mat — frequent submission attacks force defensive reactions that open up control and damage.
Rev
What it calculates
Total Reversals ÷ Total Fight Time (minutes)
Why it matters
Highlights scrambling and escape ability — reversals turn bad positions into scoring opportunities and can flip momentum.
C/15
What it calculates
(Total Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Standardizes grappling control to a 15-minute baseline so fighters with different bout lengths can be compared fairly.
TOP/15
What it calculates
(Total Top Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Separates high-quality control (top position) from other control contexts — strong top control is a reliable path to winning rounds.
CLN/15
What it calculates
(Total Clinch Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Measures fence control and pace management — clinch time can mute opponent offense and bank scoring minutes.
GRD/15
What it calculates
(Total Ground Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Shows takedown follow-through and top pressure — ground control often creates long stretches of safe scoring and attrition.
CAGE
What it calculates
(Total Cage Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Quantifies time spent driving position against the fence — useful for understanding style matchups and opponent disruption.
BACK
What it calculates
(Total Back Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Back control is premium dominance — it strongly predicts submission threat and long, uncontested control sequences.
CHIN
What it calculates
Model score (0–100): durability under damaging strikes
Why it matters
A quick durability signal — higher scores suggest a fighter can survive danger and remain competitive deep into fights.
TDAtt
What it calculates
Career total takedown attempts (UFC bouts)
Why it matters
Represents grappling intent and game-planning tendency — high attempt totals usually indicate a wrestler-first approach.
TDLnd
What it calculates
Career total takedowns landed (UFC bouts)
Why it matters
Proof of conversion and control potential — landed takedowns often precede control time, damage, and submission attempts.
TDAg
What it calculates
Career total opponent takedown attempts faced (UFC bouts)
Why it matters
Shows how often opponents choose to wrestle them — a proxy for perceived defensive striking threat or exploitable takedown defense.
TDDef
What it calculates
Career total opponent takedown attempts defended (UFC bouts)
Why it matters
Highlights defensive wrestling volume — strong defense keeps fights in a preferred phase and preserves striking efficiency.