NTOMTEM

NTOMTEM — CS2 Stats

76561198353878437[U:1:393612709]Steam profile ↗✓ No bans

850Tracked matches67%Win rate2020Tracked since
CSDB Rating5.7 SolidPositional Player
Premier CS Rating19,942Top 50% of 213,542 CSDB-tracked playersPurple band · top ~8.7% of ranked players (population est.)
CSDB Leaderboard#87032 of 260159 tracked
FaceitLevel 5 · 1,102 ELOTop 67.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Nov 2026 (3 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 19,942 → 19,942
0Faceit ELO · 1,102 → 1,102
+4Tracked matches · now 850
+2.4ppWin rate · 64.3% → 66.7%

Rating over time

Premier CS Rating: 19,942 +4,448 27 Jun – 3 Nov · 20 days played
13,62219,942peak 19,94227 Jun3 Nov
Faceit ELO: 1,102 +0 3 Sept – 3 Nov · 4 observations
1,1021,102peak 1,1023 Sept3 Nov
19,999Peak Premier in tracked matches
1,102Highest Faceit ELO seen on CSDB
36Days played since 2026-06-27

Faceit ELO

  • At peak — 1,102
  • 0 over 30 days · steady
  • Next: Level 6 at 1,201 — 99 to go
  • Reached: Level 5 · Level 4 · Level 3 · Level 2
  • Level 5 first seen 2026-09-03
  • Level 4 first seen 2026-09-03

Premier CS Rating

  • At peak — 19,942
  • +4,245 over 30 days · improving
  • +5,412 over 90 days
  • Next: Pink band at 20,000 — 58 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-03
  • Blue band first seen 2026-09-03

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGNTOMTEMFACEITLevel 5 · 1,102 ELOSTANDINGTop 67.6% of rankedPREMIER19,942 · Purple band30 DAYS0 ELOPEAK ELO1,102csdb.gg/stats

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Performance scores

Aim68
Positioning51
Utility36

0–100 skill scores via Leetify.

Recent form

STEADY52–44–4Last 10052%Win rateTLWWLWWWWL

Last 10 vs previous 10: 0pp win rate · +0.00 avg rating · +1.3pp headshot accuracy · −77ms reaction

Win rate 0pp 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

  • 2–2–1 · 40% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 13%
  • Avg reaction 474ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 13%
  • Avg reaction 495ms

Last 20

  • 12–6–2 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 12%
  • Avg reaction 533ms

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: Positional Player — Positioning stands above the rest of this profile (+2 against its own average).

Aim6.8
Utility3.6
Positioning5.1
Opening Duels1.5
Clutch2.2

Limited utility dependence

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

iM

Plays most like iM 93% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower aim profile; lower utility contribution.

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

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim6.8
Positioning5.1
Utility3.6
Mechanics5.7
Opening Duels2.7
Win Impact10.0

Composite 5.7/10 (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-0.03−0.02
first ⅓ avg -0.01 → last ⅓ avg -0.03
Reaction time547ms−37ms
first ⅓ avg 585ms → last ⅓ avg 547ms
Headshot accuracy12.1%−1.6%
first ⅓ avg 13.7% → last ⅓ avg 12.1%

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

0.15Best match rating · 13–3 · shelter, 29 Jul →
42%Best headshot accuracy · 13–1 · mirage, 23 Jul →
359msFastest reaction time · 4–9 · vertigo, 20 Sept →
13–1Biggest win · mirage, 26 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
7–4In matches decided by ≤2 rounds
8Overtime games

Map breakdown

anubisBest map · 86% over 7vertigoWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
mirageA2112–957%-0.00
cacheC167–944%-0.00
dust2A159–660%-0.01
ancientA106–460%-0.01
anubisS76–186%0.03
nukeS64–267%-0.04
vertigoD61–517%-0.04
overpassD62–433%-0.03
infernoC52–340%-0.03
train—41–325%-0.03
office—31–233%-0.01
shelter—11–0100%0.15

Across the last 100 tracked matches.

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

Faceit stats

Combat

246Matches
50%Win rate
0.98Avg K/D
74.1ADR
40%Headshot %

Clutches & streaks

31%1v1 clutch win
16%1v2 clutch win
10Longest win streak

Recent Faceit resultsWWLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage3656%1.0615.4
Ancient1457%0.7311.8
Dust21369%0.8612.5
Vertigo650%0.8615.3
Inferno540%0.9513.0
Nuke520%0.7112.4
Overpass425%0.709.5
Train450%1.0114.0

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.

12.4%Headshot accuracy
34.7%Accuracy (enemy spotted)
37.2%Spray accuracy
75.5%Counter-strafing
8.5°Preaim
536msReaction time
41.1%T opening success
40.6%CT opening success
0.63Enemies flashed / flash
4.8%Flash assists
7.68HE damage / grenade
4.06Flashes / 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 12.4249% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Vertigo

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Vertigo callouts & strategy →Vertigo grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis15–150.0012%3 Nov →
dust25–13-0.095%3 Nov →
mirage13–9-0.0311%3 Nov →
dust213–6-0.0717%3 Nov →
inferno7–13-0.0521%1 Nov →
cache13–11-0.047%1 Nov →
dust213–11-0.077%1 Nov →
anubis13–6-0.0018%31 Oct →
dust213–50.0318%31 Oct →
nuke2–13-0.0710%31 Oct →
anubis13–9-0.0311%31 Oct →
ancient13–8-0.029%31 Oct →
office8–13-0.0811%31 Oct →
nuke13–4-0.090%30 Oct →
nuke13–10-0.0513%30 Oct →
cache13–8-0.0113%30 Oct →
anubis13–40.0415%30 Oct →
inferno15–15-0.0313%30 Oct →
ancient3–13-0.0610%30 Oct →
mirage12–16-0.0719%30 Oct →
train13–9-0.0510%28 Oct →
cache13–40.0024%26 Oct →
mirage13–10.000%26 Oct →
mirage8–13-0.047%20 Oct →
train4–130.018%20 Oct →
vertigo6–13-0.0219%17 Oct →
inferno13–5-0.0519%17 Oct →
cache13–90.0312%16 Oct →
cache15–150.0617%15 Oct →
mirage13–7-0.0112%15 Oct →
cache9–13-0.0013%15 Oct →
mirage13–60.067%15 Oct →
dust28–13-0.0214%15 Oct →
nuke13–60.0717%13 Oct →
anubis13–40.0314%30 Sept →
vertigo4–9-0.0823%20 Sept →
ancient11–13-0.0511%9 Sept →
cache4–13-0.0515%8 Sept →
vertigo1–13-0.0629%6 Sept →
mirage9–13-0.066%1 Sept →
dust213–6-0.0610%1 Sept →
mirage16–14-0.0115%1 Sept →
ancient13–100.045%31 Aug →
inferno8–13-0.0211%31 Aug →
cache12–160.0313%31 Aug →
anubis13–70.1017%31 Aug →
overpass9–13-0.056%28 Aug →
mirage10–13-0.0216%24 Aug →
mirage13–60.0411%24 Aug →
dust213–60.0130%24 Aug →
mirage13–4-0.063%24 Aug →
vertigo0–13-0.100%24 Aug →
mirage12–12-0.0125%24 Aug →
mirage10–130.0114%15 Aug →
dust213–6-0.0610%15 Aug →
ancient16–13-0.0212%5 Aug →
mirage13–60.0312%5 Aug →
inferno13–100.0211%3 Aug →
dust27–130.0716%2 Aug →
cache2–13-0.0011%2 Aug →
ancient13–40.0314%2 Aug →
cache13–30.0913%2 Aug →
mirage3–13-0.008%30 Jul →
office13–80.0416%30 Jul →
vertigo12–20.0718%29 Jul →
shelter13–30.1510%29 Jul →
office9–130.015%29 Jul →
cache11–13-0.0220%23 Jul →
mirage13–9-0.058%23 Jul →
dust210–130.0118%23 Jul →
mirage13–10.0342%23 Jul →
mirage13–90.0610%22 Jul →
dust213–90.0414%15 Jul →
mirage13–110.0714%15 Jul →
nuke9–13-0.0415%14 Jul →
cache8–130.0315%13 Jul →
dust21–13-0.065%13 Jul →
train6–13-0.0712%7 Jul →
vertigo6–13-0.0514%7 Jul →
overpass13–100.0315%7 Jul →
ancient13–50.033%7 Jul →
cache11–13-0.0132%7 Jul →
cache6–13-0.029%5 Jul →
overpass13–11-0.0316%5 Jul →
ancient13–8-0.0115%5 Jul →
dust213–9-0.0022%5 Jul →
dust213–80.049%5 Jul →
anubis13–90.0516%5 Jul →
mirage13–16-0.0114%5 Jul →
nuke13–11-0.0413%4 Jul →
overpass8–13-0.0115%4 Jul →
train7–13-0.013%28 Jun →
mirage9–130.008%28 Jun →
dust27–130.015%28 Jun →
cache13–11-0.089%27 Jun →
cache13–2-0.0118%27 Jun →
overpass1–13-0.0515%27 Jun →
overpass4–13-0.0515%27 Jun →
ancient11–13-0.039%27 Jun →
ancient1–7-0.037%27 Jun →

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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