conti

conti — CS2 Stats

76561198856443498[U:1:896177770]Steam profile ↗✓ No bans

5,389Tracked matches41%Win rate2021Tracked since
4,628Hours in CS
CSDB Rating3.7 LearningPositional Player
Premier CS Rating2,610Grey band · top ~88.9% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 22 Oct 2026 (3 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 2,610 -1,583 8 Sept – 22 Oct · 16 days played
1,9984,193peak 4,1938 Sept22 Oct
4,291Peak Premier in tracked matches
17Days played since 2026-09-08

Premier CS Rating

  • 1,583 below peak (4,193)
  • -1,390 over 30 days · declining
  • Next: Light Blue band at 5,000 — 2,390 to go

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 Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate36.2%38.2%39.9%3.7% short
Shot accuracy7.9%3.6%7.0%above
Kill/death ratio0.650.830.920.26 short
Match win rate30.6%40.2%42.3%11.6% short

This profile matches the typical Light Blue band player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Light Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGcontiPREMIER2,610 · Grey 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

Aim37
Positioning59
Utility27

0–100 skill scores via Leetify.

Recent form

COLD41–55–4Last 10041%Win rateLWLLWLLLLL

Last 10 vs previous 10: −50pp win rate · −0.03 avg rating · −4.3pp headshot accuracy · −83ms reaction

Win rate down 50pp 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

  • 2–3 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 10%
  • Avg reaction 674ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 9%
  • Avg reaction 577ms

Last 20

  • 9–10–1 · 45% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 11%
  • Avg reaction 618ms

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 (+1.8 against its own average).

Aim3.7
Utility2.7
Positioning5.9
Opening Duels3.2
Clutch4.8

Strong CT-side opener

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

donk

Plays most like donk 71% playstyle similarity

Most alike: positioning profile, opening-duel success.

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

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

Reaction time. 625ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim3.7
Positioning5.9
Utility2.7
Mechanics3.8
Opening Duels6.0
Win Impact2.1

Composite 3.7/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time609ms+67ms
first ⅓ avg 542ms → last ⅓ avg 609ms
Headshot accuracy10.2%−5.3%
first ⅓ avg 15.5% → last ⅓ avg 10.2%

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 · dust2, 15 Oct →
50%Best headshot accuracy · 15–15 · dust2, 3 Oct →
344msFastest reaction time · 5–13 · inferno, 3 Oct →
13–0Biggest win · cache, 21 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
4–10In matches decided by ≤2 rounds
10Overtime games

Map breakdown

ancientBest map · 64% over 11infernoWeakest map · 25% over 16
MapGradePlayedRecordWin rateAvg rating
mirageD227–1532%-0.02
dust2B178–947%0.02
infernoD164–1225%-0.02
nukeC125–742%-0.01
ancientA117–464%0.03
anubisD93–633%-0.01
cacheB84–450%-0.02
train—32–167%0.06
rush_001—21–150%0.09

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

175,052Lifetime kills
0.65K/D
20,429Matches
30.6%Match win rate
36.2%Headshot %
7.9%Shot accuracy · Top 50% of Grey band
12,052MVPs
4,628Hours (in match)
9,568Bombs planted
1,281Bombs defused

Most-used weapons

AK-4727,645
AWP19,157
SSG 0812,583
SCAR-2011,247
MAC-107,889
G3SG16,279
MP95,110

Lifetime map wins

32,512dust2
9,369inferno
8,621nuke
4,475vertigo
2,090train
605office
318lake
291safehouse

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

Faceit stats

Combat

45Matches
38%Win rate
0.57Avg K/D
55.2ADR
42%Headshot %

Clutches & streaks

44%1v1 clutch win
6%1v2 clutch win
3Longest win streak

Recent Faceit resultsLWLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage1443%0.649.9
Dust21127%0.609.2
Ancient743%0.5210.3
Anubis633%0.478.5
Inferno30%0.325.3
Nuke2100%0.669.0
Train10%0.408.0
Overpass1100%1.0011.0

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.

10.5%Headshot accuracy
34.9%Accuracy (enemy spotted)
33.2%Spray accuracy
67.1%Counter-strafing
11.9°Preaim
625msReaction time
57.9%T opening success
50.4%CT opening success
0.54Enemies flashed / flash
4.0%Flash assists
2.08HE damage / grenade
6.76Flashes / 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 10.5102% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Inferno

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

25% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke9–13-0.0511%22 Oct →
mirage13–9-0.0522%22 Oct →
anubis13–16-0.026%22 Oct →
ancient11–13-0.0310%22 Oct →
cache13–7-0.030%22 Oct →
nuke10–130.000%22 Oct →
nuke6–13-0.0617%22 Oct →
ancient8–13-0.077%22 Oct →
dust210–130.0311%22 Oct →
dust23–13-0.027%22 Oct →
cache13–0-0.0124%21 Oct →
nuke13–4-0.0110%20 Oct →
mirage13–5-0.029%20 Oct →
nuke16–140.0713%20 Oct →
dust213–80.1011%20 Oct →
mirage10–13-0.0329%19 Oct →
dust211–13-0.0710%19 Oct →
mirage13–6-0.044%19 Oct →
inferno13–50.0611%19 Oct →
mirage15–15-0.0213%19 Oct →
mirage3–13-0.064%18 Oct →
inferno9–13-0.0720%18 Oct →
mirage11–130.069%18 Oct →
mirage11–13-0.038%18 Oct →
dust211–13-0.028%18 Oct →
anubis13–100.0012%18 Oct →
ancient13–100.1312%18 Oct →
anubis9–13-0.066%18 Oct →
inferno13–90.0510%18 Oct →
mirage11–13-0.001%18 Oct →
nuke4–9-0.1313%18 Oct →
dust210–130.0211%17 Oct →
mirage13–7-0.020%17 Oct →
dust213–90.0413%17 Oct →
mirage10–13-0.0210%17 Oct →
ancient13–110.069%17 Oct →
cache13–100.0715%17 Oct →
ancient16–130.0610%17 Oct →
cache5–13-0.0611%17 Oct →
dust29–130.0412%17 Oct →
inferno8–13-0.048%17 Oct →
mirage13–50.0416%15 Oct →
nuke7–13-0.0312%15 Oct →
anubis8–13-0.044%15 Oct →
ancient13–50.0513%15 Oct →
ancient13–90.0211%15 Oct →
cache13–40.008%15 Oct →
dust213–9-0.0313%15 Oct →
mirage4–13-0.0910%15 Oct →
inferno13–30.1318%15 Oct →
ancient13–50.1016%15 Oct →
dust213–30.1512%15 Oct →
nuke13–20.0421%15 Oct →
inferno5–9-0.0014%15 Oct →
dust213–20.0313%15 Oct →
nuke16–13-0.048%15 Oct →
inferno1–9-0.260%15 Oct →
inferno8–80.0816%15 Oct →
inferno9–50.0416%15 Oct →
nuke9–130.0216%14 Oct →
dust28–00.059%14 Oct →
nuke5–13-0.0516%14 Oct →
anubis14–160.0413%14 Oct →
inferno7–13-0.0711%13 Oct →
anubis14–16-0.0218%13 Oct →
anubis6–13-0.0318%13 Oct →
mirage13–5-0.0416%13 Oct →
dust29–13-0.0212%13 Oct →
nuke13–50.1110%13 Oct →
anubis13–100.036%8 Oct →
ancient13–9-0.0015%8 Oct →
ancient15–150.0411%8 Oct →
cache9–13-0.080%8 Oct →
inferno11–130.097%8 Oct →
mirage7–13-0.076%7 Oct →
ancient10–13-0.0412%7 Oct →
mirage5–13-0.1029%7 Oct →
train13–50.055%7 Oct →
train4–00.1143%7 Oct →
train6–130.0118%7 Oct →
cache2–13-0.0420%4 Oct →
dust213–110.0318%3 Oct →
mirage13–90.0322%3 Oct →
inferno5–13-0.130%3 Oct →
dust213–10-0.049%3 Oct →
mirage7–130.0417%3 Oct →
dust215–150.0650%3 Oct →
mirage9–13-0.0112%3 Oct →
mirage1–130.0111%3 Oct →
inferno10–13-0.0717%3 Oct →
dust24–13-0.0413%1 Oct →
rush_0016–80.0713%1 Oct →
rush_0018–60.1150%1 Oct →
inferno3–13-0.0311%30 Sept →
inferno9–13-0.015%30 Sept →
cache6–13-0.026%30 Sept →
mirage10–13-0.0318%30 Sept →
anubis13–70.0113%30 Sept →
mirage13–16-0.0417%23 Sept →
inferno2–9-0.0315%22 Sept →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.