ulma

ulma — CS2 Stats

76561198202872084[U:1:242606356]Steam profile ↗✓ No bans

788Tracked matches41%Win rate2020Tracked since
CSDB Rating4.6 DevelopingSupport
CSDB Leaderboard#56573 of 251379 tracked
FaceitLevel 6 · 1,649 ELOTop 54.0% of ranked FACEIT players
WingmanLegendary Eagle
Ladder ranks via Leetify

Rating over time

22,045Peak Premier in tracked matches
1,649Highest Faceit ELO seen on CSDB
31Days played since 2025-12-27

Faceit ELO

  • At peak — 1,649
  • Next: Level 9 at 1,751 — 102 to go
  • Reached: Level 8 · Level 7 · Level 6 · Level 5

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

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CSDB.GGulmaFACEITLevel 6 · 1,649 ELOSTANDINGTop 54.0% of rankedPEAK ELO1,649csdb.gg/stats

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Performance scores

Aim65
Positioning54
Utility54

0–100 skill scores via Leetify.

Recent form

COLD46–51–3Last 10046%Win rateLLLLLLLWWW

Last 10 vs previous 10: −10pp win rate · −0.02 avg rating · −3.5pp headshot accuracy · +23ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 0–5 · 0% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 11%
  • Avg reaction 520ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 538ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 14%
  • Avg reaction 527ms

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 (+1.8 against its own average).

Aim6.5
Utility5.4
Positioning5.4
Opening Duels0.6
Clutch3.2

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

Twistzz

Plays most like Twistzz 82% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; lower opening-duel success.

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

CSDB Rating breakdown

Aim6.5
Positioning5.4
Utility5.4
Mechanics4.9
Opening Duels0.5
Win Impact2.1

Composite 4.6/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.00
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time518ms−22ms
first ⅓ avg 539ms → last ⅓ avg 518ms
Headshot accuracy14.0%−1.3%
first ⅓ avg 15.2% → last ⅓ avg 14.0%

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

0.11Best match rating · 13–3 · anubis, 18 Jan →
30%Best headshot accuracy · 10–1 · inferno, 27 Dec →
313msFastest reaction time · 5–7 · dust2, 12 Sept →
13–2Biggest win · nuke, 5 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L7Current streak
6–10In matches decided by ≤2 rounds
5Overtime games

Map breakdown

infernoBest map · 57% over 21ancientWeakest map · 35% over 17
MapGradePlayedRecordWin rateAvg rating
infernoA2112–957%-0.02
ancientC176–1135%-0.02
dust2B178–947%-0.02
mirageC135–838%-0.02
nukeB126–650%-0.03
anubisA95–456%-0.03
train—31–233%0.01
office—21–150%0.00
cache—20–20%-0.05
vertigo—21–150%0.04
overpass—21–150%0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (35% over 17). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

760Matches
49%Win rate
1.03Avg K/D
72.0ADR
35%Headshot %

Clutches & streaks

36%1v1 clutch win
22%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLLLL

MapMatchesWin rateAvg K/DAvg kills
Ancient8849%0.9814.7
Anubis7742%1.0314.8
Nuke7464%0.9814.4
Inferno5639%1.0013.9
Mirage4646%0.9713.9
Dust23139%0.9614.7
Overpass2759%0.9915.4
Vertigo2138%1.0114.6

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.

14.4%Headshot accuracy
34.0%Accuracy (enemy spotted)
37.7%Spray accuracy
71.9%Counter-strafing
10.1°Preaim
514msReaction time
27.6%T opening success
34.0%CT opening success
0.58Enemies flashed / flash
5.5%Flash assists
8.38HE damage / grenade
5.54Flashes / 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. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 14.4396% — below the 15% mark we flag

    Aim Training →
  2. 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 27.5794% — below the 40% mark we flag

Spend your practice time on Ancient

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

35% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient2–13-0.047%26 Sept →
anubis4–13-0.103%12 Sept →
ancient7–13-0.059%12 Sept →
dust25–7-0.0423%12 Sept →
nuke0–6-0.0112%8 Sept →
ancient11–13-0.0123%6 Sept →
inferno9–13-0.069%5 Sept →
mirage16–13-0.0213%5 Sept →
anubis13–5-0.018%5 Sept →
nuke13–2-0.0019%5 Sept →
dust213–7-0.0011%5 Sept →
ancient6–13-0.0611%5 Sept →
office13–4-0.039%5 Sept →
office3–130.0314%5 Sept →
mirage9–130.0218%4 Sept →
nuke5–13-0.0521%4 Sept →
inferno11–13-0.0015%4 Sept →
dust24–13-0.0423%4 Sept →
ancient13–80.0215%4 Sept →
nuke13–9-0.0123%3 Sept →
dust26–13-0.0821%3 Sept →
cache3–13-0.0818%26 Aug →
dust213–10-0.0225%23 Aug →
inferno6–13-0.0418%23 Aug →
nuke16–13-0.0513%23 Aug →
mirage13–70.0212%22 Aug →
cache12–12-0.0316%22 Aug →
inferno13–3-0.0512%22 Aug →
ancient8–130.074%22 Aug →
ancient13–30.044%18 Aug →
mirage13–8-0.057%18 Aug →
nuke13–60.009%18 Aug →
train13–60.0216%14 Aug →
train12–120.0111%14 Aug →
anubis13–10-0.0411%9 Aug →
mirage6–13-0.0513%6 Aug →
inferno13–8-0.0113%6 Aug →
vertigo4–13-0.0024%4 Aug →
vertigo13–80.0823%4 Aug →
dust24–130.0312%13 Apr →
nuke13–8-0.0512%13 Apr →
inferno13–100.009%13 Apr →
mirage11–13-0.0213%5 Apr →
inferno3–13-0.0423%2 Apr →
dust213–7-0.0220%2 Apr →
mirage3–13-0.087%2 Apr →
nuke10–13-0.0624%2 Apr →
dust213–110.010%22 Jan →
inferno11–13-0.010%22 Jan →
anubis13–90.000%22 Jan →
ancient2–13-0.050%22 Jan →
inferno13–60.058%18 Jan →
anubis13–110.0011%18 Jan →
dust213–70.0214%18 Jan →
anubis13–30.116%18 Jan →
anubis1–10-0.118%18 Jan →
mirage4–130.0117%15 Jan →
ancient5–13-0.009%15 Jan →
dust26–13-0.0918%15 Jan →
anubis3–13-0.0613%15 Jan →
mirage19–17-0.029%13 Jan →
inferno13–5-0.0311%13 Jan →
dust214–16-0.056%13 Jan →
mirage5–100.0315%12 Jan →
dust22–13-0.0322%12 Jan →
anubis14–16-0.0312%11 Jan →
nuke13–110.0319%11 Jan →
ancient10–13-0.0211%11 Jan →
inferno3–13-0.0717%11 Jan →
dust210–13-0.0220%11 Jan →
dust211–130.0115%11 Jan →
mirage13–11-0.0216%10 Jan →
inferno13–10-0.0424%10 Jan →
nuke11–13-0.0512%4 Jan →
inferno6–13-0.064%4 Jan →
mirage4–13-0.0310%4 Jan →
ancient13–9-0.0218%4 Jan →
mirage11–13-0.006%4 Jan →
dust213–60.0528%2 Jan →
inferno7–13-0.1118%1 Jan →
overpass13–80.019%1 Jan →
dust213–10-0.0114%1 Jan →
ancient13–70.0214%29 Dec →
ancient2–13-0.1021%28 Dec →
nuke4–13-0.0419%28 Dec →
train9–13-0.009%28 Dec →
ancient13–9-0.0919%28 Dec →
dust213–10-0.0114%28 Dec →
nuke6–13-0.068%28 Dec →
overpass2–130.0215%28 Dec →
ancient13–10-0.029%28 Dec →
ancient4–13-0.0517%28 Dec →
ancient12–12-0.0611%28 Dec →
inferno13–11-0.0617%27 Dec →
inferno13–30.0715%27 Dec →
inferno13–4-0.0119%27 Dec →
inferno13–30.0111%27 Dec →
inferno13–30.0516%27 Dec →
inferno9–13-0.0219%27 Dec →
inferno10–10.0530%27 Dec →

Match data via Leetify.

Recent teammates

Milestones

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

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