ChumtGPT-di 1.2L

ChumtGPT-di 1.2L — CS2 Stats

76561199348558422[U:1:1388292694]Steam profile ↗✓ No bans

1,787Tracked matches52%Win rate2023Tracked since
1,945Hours in CS12Hrs last 2 wks
CSDB Rating6.4 SolidPositional Player
Premier CS Rating15,981Purple band · top ~24.5% of ranked players (population est.)
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 10 Nov 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 1,787 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 15,981 -2,484 14 Aug – 10 Nov · 31 days played
13,46419,279peak 19,27914 Aug10 Nov
19,279Peak Premier in tracked matches
34Days played since 2026-08-14

Premier CS Rating

  • 3,298 below peak (19,279)
  • +1,472 over 30 days · improving
  • -2,484 over 90 days
  • Next: Pink band at 20,000 — 4,019 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-11-01
  • Blue band first seen 2026-11-01

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

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=14,630), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 4 medianLevel 5 medianvs Level 5
Headshot rate56.9%42.7%43.8%above
Shot accuracy4.8%11.2%12.0%7.2% short
Kill/death ratio0.940.991.020.08 short
Match win rate39.2%43.9%44.7%5.5% short

This profile matches the typical Level 5 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGChumtGPT-di 1.2LFACEITLevel 4STANDINGTop 81.0% of rankedPREMIER15,981 · Purple bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim80
Positioning61
Utility48

0–100 skill scores via Leetify.

Recent form

STEADY50–47–3Last 10050%Win rateWWWLLLWTLW

Last 10 vs previous 10: 0pp win rate · +0.02 avg rating · +4.1pp headshot accuracy · −84ms 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

  • 3–2 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 24%
  • Avg reaction 558ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 23%
  • Avg reaction 540ms

Last 20

  • 10–9–1 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 21%
  • Avg reaction 582ms

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 (+2.5 against its own average).

Aim8.0
Utility4.8
Positioning6.1
Opening Duels3.4
Clutch0.0

Effective flashesLimited 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

Twistzz

Plays most like Twistzz 91% playstyle similarity

Most alike: positioning profile, opening-duel success.

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.

Reaction time. 561ms 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

Aim8.0
Positioning6.1
Utility4.8
Mechanics7.1
Opening Duels4.8
Win Impact5.6

Composite 6.4/10 (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+0.00
first ⅓ avg -0.00 → last ⅓ avg -0.00
Reaction time566ms−36ms
first ⅓ avg 602ms → last ⅓ avg 566ms
Headshot accuracy20.9%−5.1%
first ⅓ avg 26.0% → last ⅓ avg 20.9%

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

0.16Best match rating · 13–9 · inferno, 5 Nov →
100%Best headshot accuracy · 3–5 · mirage, 23 Aug →
375msFastest reaction time · 3–5 · mirage, 23 Aug →
13–0Biggest win · dust2, 15 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W3Current streak
7–9In matches decided by ≤2 rounds
10Overtime games

Map breakdown

infernoBest map · 75% over 12nukeWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
dust2A2212–1055%0.01
mirageB2111–1052%0.00
ancientC166–1038%-0.00
infernoS129–375%0.03
anubisA116–555%-0.03
nukeD103–730%-0.01
cacheD62–433%0.05
train—21–150%-0.03

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

67,124Lifetime kills
0.94K/D
3,544Matches
39.2%Match win rate
56.9%Headshot % · Top 10% of Level 4 players
4.8%Shot accuracy
7,277MVPs
1,205Hours (in match)
3,967Bombs planted
507Bombs defused

Most-used weapons

Lifetime map wins

10,186dust2
3,775inferno
1,837nuke
658vertigo
469train
77office
15lake
8assault

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

13Matches
31%Win rate
0.83Avg K/D
97.8ADR
50%Headshot %

Clutches & streaks

20%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Anubis520%0.539.4
Mirage367%0.9112.3
Ancient30%1.3423.3
Nuke1100%1.3225.0
Inferno10%0.000.0

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.

20.7%Headshot accuracy
36.9%Accuracy (enemy spotted)
34.2%Spray accuracy
81.7%Counter-strafing
8.6°Preaim
561msReaction time
51.7%T opening success
46.7%CT opening success
0.72Enemies flashed / flash
6.4%Flash assists
11.02HE damage / grenade
4.66Flashes / match

Recommended for you

Spend your practice time on Nuke

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

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–90.1626%5 Nov →
ancient13–110.0427%5 Nov →
dust213–90.0224%5 Nov →
anubis5–13-0.0530%5 Nov →
ancient10–13-0.0813%3 Nov →
anubis9–13-0.0229%2 Nov →
ancient13–90.0722%2 Nov →
ancient15–150.0216%2 Nov →
dust28–13-0.0315%1 Nov →
dust213–6-0.0026%1 Nov →
nuke13–80.0229%1 Nov →
mirage13–90.0334%1 Nov →
dust28–13-0.0510%31 Oct →
ancient14–16-0.0219%31 Oct →
ancient9–13-0.0318%31 Oct →
dust211–13-0.0313%29 Oct →
anubis16–14-0.0215%29 Oct →
nuke13–9-0.0319%29 Oct →
ancient14–16-0.0113%28 Oct →
inferno13–30.0515%28 Oct →
nuke9–13-0.0325%28 Oct →
nuke13–16-0.0121%27 Oct →
mirage11–13-0.0328%27 Oct →
ancient10–13-0.0420%25 Oct →
inferno13–5-0.0123%25 Oct →
nuke14–16-0.0224%25 Oct →
inferno13–50.0129%25 Oct →
dust213–40.1120%25 Oct →
ancient13–11-0.0213%25 Oct →
anubis13–20.0411%25 Oct →
nuke10–13-0.0021%25 Oct →
inferno13–10-0.0417%25 Oct →
mirage13–16-0.0226%24 Oct →
anubis6–13-0.0319%24 Oct →
nuke13–70.0224%24 Oct →
cache8–130.0323%23 Oct →
cache13–60.1616%21 Oct →
mirage13–70.0422%21 Oct →
mirage13–60.039%21 Oct →
dust213–90.0116%21 Oct →
mirage13–70.0224%21 Oct →
mirage8–13-0.070%20 Oct →
inferno9–130.0115%19 Oct →
cache15–150.0924%19 Oct →
inferno8–13-0.0017%19 Oct →
ancient13–7-0.0118%19 Oct →
anubis8–13-0.047%18 Oct →
ancient10–130.0615%18 Oct →
dust23–130.0417%18 Oct →
inferno13–40.1020%18 Oct →
mirage8–130.0013%18 Oct →
dust29–13-0.0416%17 Oct →
mirage13–30.0222%17 Oct →
cache7–13-0.0532%17 Oct →
mirage13–70.0524%15 Oct →
mirage13–70.0320%15 Oct →
anubis13–10-0.0217%15 Oct →
anubis4–13-0.0914%15 Oct →
ancient13–80.0426%15 Oct →
train13–5-0.0125%13 Oct →
inferno13–60.0126%12 Oct →
dust213–90.0333%12 Oct →
dust213–50.0829%12 Oct →
mirage10–130.0025%12 Oct →
dust29–13-0.0521%30 Sept →
anubis13–90.0317%29 Sept →
mirage11–13-0.0016%29 Sept →
ancient6–13-0.0118%27 Sept →
mirage7–0-0.0020%26 Sept →
dust210–13-0.0811%28 Aug →
ancient10–13-0.0319%28 Aug →
dust213–50.0447%28 Aug →
cache7–13-0.0029%28 Aug →
mirage8–13-0.0633%26 Aug →
cache13–110.0515%26 Aug →
inferno11–130.0229%25 Aug →
nuke6–13-0.0611%25 Aug →
dust213–11-0.0341%25 Aug →
anubis13–11-0.0431%24 Aug →
inferno13–6-0.0235%24 Aug →
ancient13–8-0.0132%24 Aug →
mirage14–160.0323%23 Aug →
mirage3–5-0.05100%23 Aug →
dust22–130.0236%23 Aug →
nuke8–130.0031%22 Aug →
dust213–80.0420%20 Aug →
mirage13–9-0.0131%20 Aug →
nuke5–13-0.0123%17 Aug →
mirage13–100.0222%17 Aug →
dust213–5-0.0119%16 Aug →
dust27–13-0.0112%16 Aug →
mirage15–15-0.0323%16 Aug →
inferno13–90.0314%16 Aug →
ancient10–13-0.0116%16 Aug →
train0–13-0.0620%15 Aug →
mirage13–110.0721%15 Aug →
dust213–00.0220%15 Aug →
dust25–130.0623%15 Aug →
anubis13–8-0.0510%14 Aug →
dust213–60.0521%14 Aug →

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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