mongol

mongol — CS2 Stats

US76561198078065340[U:1:117799612]Steam profile ↗✓ No bans

1,760Tracked matches52%Win rate2020Tracked since
CSDB Rating6.7 SolidSupport
CSDB Leaderboard#18301 of 251448 tracked
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Aug 2026 (45 days ago). Ranks are recorded once per day this page is viewed.

+8Tracked matches · now 1,760
−9.0ppWin rate · 60.7% → 51.7%

Rating over time

Premier CS Rating: 25,241 -1,670 13 Jul – 30 Aug · 10 days played
25,18927,631peak 27,63113 Jul30 Aug
27,631Peak Premier in tracked matches
39Days played since 2026-06-28

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim88
Positioning59
Utility59

0–100 skill scores via Leetify.

Recent form

COLD54–40–6Last 10054%Win rateLLLWLLLWLW

Last 10 vs previous 10: −30pp win rate · −0.00 avg rating · +4.8pp headshot accuracy · −35ms reaction

Win rate down 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 23%
  • Avg reaction 480ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 25%
  • Avg reaction 529ms

Last 20

  • 9–10–1 · 45% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 23%
  • Avg reaction 547ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+1.7 against its own average).

Aim8.8
Utility5.9
Positioning5.9
Opening Duels2.3
Clutch2.6

Sharp aimer

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

b1t

Plays most like b1t 94% playstyle similarity

Most alike: utility contribution, opening-duel success.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Strengths

Aim. Aim score of 88 — the mechanical foundation is a clear strength.

Areas to improve

Reaction time. 574ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim8.8
Positioning5.9
Utility5.9
Mechanics8.1
Opening Duels2.1
Win Impact5.6

Composite 6.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.00
Reaction time572ms−15ms
first ⅓ avg 587ms → last ⅓ avg 572ms
Headshot accuracy23.7%+0.4%
first ⅓ avg 23.3% → last ⅓ avg 23.7%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.10Best match rating · 13–3 · dust2, 10 Jul →
50%Best headshot accuracy · 11–13 · inferno, 9 Sept →
391msFastest reaction time · 3–3 · ancient, 23 Jul →
13–1Biggest win · nuke, 22 Jul →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L3Current streak
3–5In matches decided by ≤2 rounds
4Overtime games

Map breakdown

cacheBest map · 80% over 15dust2Weakest map · 42% over 12
MapGradePlayedRecordWin rateAvg rating
nukeB2413–1154%0.01
infernoB2311–1248%0.01
cacheS1512–380%0.01
dust2C125–742%-0.01
mirageA106–460%0.01
ancientB63–350%-0.01
train—42–250%0.01
overpass—32–167%-0.04
anubis—30–30%-0.03

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (42% over 12). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

845Matches
58%Win rate
1.31Avg K/D
81.8ADR
41%Headshot %

Clutches & streaks

33%1v1 clutch win
33%1v2 clutch win
11Longest win streak

Recent Faceit resultsLLLWW

MapMatchesWin rateAvg K/DAvg kills
Inferno4757%1.2215.5
Nuke3569%1.4815.8
Mirage2857%1.1316.0
Anubis2654%1.2115.5
Ancient1958%1.3016.5
Overpass1354%1.2615.8
Dust21070%1.1615.3
Cache862%1.0013.4

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

22.5%Headshot accuracy
37.7%Accuracy (enemy spotted)
44.1%Spray accuracy
86.6%Counter-strafing
9.0°Preaim
574msReaction time
36.0%T opening success
40.9%CT opening success
0.53Enemies flashed / flash
7.1%Flash assists
11.35HE damage / grenade
12.58Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 35.9592% — below the 40% mark we flag

Spend your practice time on Dust 2

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

42% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno6–130.057%10 Oct →
nuke0–7-0.0543%10 Oct →
nuke9–130.0129%25 Sept →
inferno13–110.0619%25 Sept →
mirage9–130.0118%22 Sept →
inferno11–130.0250%9 Sept →
overpass2–13-0.0727%6 Sept →
nuke13–70.0529%28 Aug →
inferno5–13-0.0613%20 Aug →
nuke13–80.0420%18 Aug →
cache13–40.0515%16 Aug →
mirage13–100.0128%16 Aug →
inferno7–13-0.0421%16 Aug →
inferno10–13-0.029%16 Aug →
dust23–130.0119%16 Aug →
dust213–10-0.0231%16 Aug →
cache13–100.0825%16 Aug →
dust213–10-0.0314%11 Aug →
nuke15–150.0820%10 Aug →
nuke13–9-0.0326%8 Aug →
ancient13–40.0437%8 Aug →
cache13–9-0.0721%5 Aug →
nuke13–9-0.0616%3 Aug →
nuke5–13-0.0820%2 Aug →
inferno6–130.0117%2 Aug →
inferno1–13-0.0442%2 Aug →
mirage13–11-0.0116%2 Aug →
nuke13–80.0619%28 Jul →
ancient1–13-0.0116%28 Jul →
inferno13–70.0425%28 Jul →
cache13–40.0048%28 Jul →
mirage13–10-0.0426%28 Jul →
dust210–130.0318%27 Jul →
inferno11–13-0.0027%27 Jul →
cache4–13-0.0128%26 Jul →
nuke12–120.0313%25 Jul →
ancient13–7-0.0120%25 Jul →
ancient3–3-0.1436%23 Jul →
cache13–7-0.0521%22 Jul →
nuke13–10.0630%22 Jul →
inferno5–13-0.1238%19 Jul →
nuke0–130.000%18 Jul →
inferno4–13-0.0830%18 Jul →
dust213–9-0.0210%18 Jul →
mirage11–13-0.0226%17 Jul →
nuke13–10-0.028%17 Jul →
inferno5–130.0236%17 Jul →
train12–12-0.0226%17 Jul →
cache13–30.0822%17 Jul →
nuke0–13-0.020%17 Jul →
cache8–13-0.0312%16 Jul →
inferno16–120.0517%16 Jul →
cache16–130.0128%15 Jul →
inferno13–50.0813%14 Jul →
dust210–13-0.0322%13 Jul →
inferno13–40.0010%13 Jul →
nuke13–50.0430%13 Jul →
nuke0–13-0.0511%13 Jul →
nuke13–70.0222%12 Jul →
dust215–15-0.0013%12 Jul →
ancient8–13-0.0217%12 Jul →
cache13–10-0.0225%12 Jul →
inferno13–5-0.0118%12 Jul →
nuke8–13-0.0025%12 Jul →
dust213–60.0533%12 Jul →
mirage13–70.0625%12 Jul →
nuke13–8-0.0117%12 Jul →
dust27–13-0.0326%11 Jul →
cache13–70.0829%11 Jul →
ancient13–70.0617%11 Jul →
dust213–30.1030%10 Jul →
mirage10–30.0823%10 Jul →
anubis0–7-0.0625%8 Jul →
train7–13-0.0316%7 Jul →
inferno13–50.0419%7 Jul →
cache13–70.0827%7 Jul →
dust27–13-0.0618%7 Jul →
nuke13–30.0124%7 Jul →
inferno13–80.0423%6 Jul →
mirage13–8-0.0319%6 Jul →
cache13–10-0.0026%6 Jul →
nuke13–60.0626%6 Jul →
inferno13–20.0733%6 Jul →
anubis6–130.0112%5 Jul →
inferno13–110.1015%5 Jul →
dust23–13-0.0515%5 Jul →
overpass13–10-0.0420%5 Jul →
train13–90.0722%5 Jul →
nuke13–90.0613%5 Jul →
cache13–80.0134%3 Jul →
inferno13–100.0230%3 Jul →
nuke6–13-0.0721%3 Jul →
mirage12–120.0322%1 Jul →
anubis7–13-0.0420%1 Jul →
overpass3–0-0.0238%1 Jul →
inferno12–120.0423%1 Jul →
mirage9–13-0.0520%29 Jun →
cache11–13-0.0441%29 Jun →
train13–10.0114%28 Jun →
nuke9–130.0430%28 Jun →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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