-Tikki-

-Tikki- — CS2 Stats

BZ76561198980624355[U:1:1020358627]Steam profile ↗✓ No bans

717Tracked matches50%Win rate2021Tracked since
846Hours in CS
CSDB Rating5.2 DevelopingAll-Rounder
FaceitLevel 5Top 67.6% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then — still 717 tracked matches. Play, then come back: the next observation lands here.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 52 days played since 23 Jul 2025. Come back after the next session and the change shows above.

Is this you? Sign in with Steam to claim it and connect match tracking →

Rating over time

Premier CS Rating: 17,593 +6,979 21 Nov11 Mar · 18 days played
10,61417,593peak 17,59321 Nov11 Mar
17,593Peak Premier in tracked matches
52Days played since 2025-07-23

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 5 among CSDB-tracked players (n=12,274), 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 5 medianLevel 6 medianvs Level 6
Headshot rate42.9%43.8%44.8%2.0% short
Shot accuracy15.7%12.0%12.4%above
Kill/death ratio0.951.021.040.09 short
Match win rate42.6%44.7%45.2%2.6% short

This profile matches the typical Level 6 player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GG-Tikki-FACEITLevel 5STANDINGTop 67.6% of rankedcsdb.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

Aim62
Positioning51
Utility44

0–100 skill scores via Leetify.

Recent form

HOT47503Last 10047%Win rateLWWWLWWWWL

Last 10 vs previous 10: +40pp win rate · −0.02 avg rating · +0.3pp headshot accuracy · +78ms reaction

Win rate up 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 32 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 19%
  • Avg reaction 636ms

Last 10

  • 73 · 70% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 18%
  • Avg reaction 638ms

Last 20

  • 1091 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 18%
  • Avg reaction 600ms

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: All-RounderNo style dimension stands clear of the others in this profile.

Aim6.2
Utility4.4
Positioning5.1
Opening Duels3.4
Clutch4.4

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

jL

Plays most like jL 90% 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

T-side openings. Opening success drops from 51% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 590ms 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

Aim6.2
Positioning5.1
Utility4.4
Mechanics6.2
Opening Duels2.6
Win Impact5.0

Composite 5.2/10 (Developing), 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 rating0.01−0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time611ms+10ms
first ⅓ avg 601ms → last ⅓ avg 611ms
Headshot accuracy16.8%+2.7%
first ⅓ avg 14.2% → last ⅓ avg 16.8%

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 · 9–13 · inferno, 29 Jul
31%Best headshot accuracy · 2–13 · mirage, 26 Jan
438msFastest reaction time · 11–13 · ancient, 9 Nov
13–1Biggest win · ancient, 23 Jan

Across the last 100 tracked matches.

Highlights

6Longest win streak
58In matches decided by ≤2 rounds
6Overtime games

Map breakdown

overpassBest map · 69% over 13infernoWeakest map · 33% over 18
MapGradePlayedRecordWin rateAvg rating
mirageC2591636%0.03
infernoD1861233%0.02
ancientB178947%0.01
overpassS139469%0.01
nukeC125742%0.02
anubisA53260%0.00
dust2440100%0.07
train42250%0.04
vertigo110100%0.10
golden1010%-0.10

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 18). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

42,952Lifetime kills
0.95K/D
2,541Matches
42.6%Match win rate
42.9%Headshot %
15.7%Shot accuracy · Top 25% of Level 5 players
4,610MVPs
846Hours (in match)
2,406Bombs planted
455Bombs defused

Most-used weapons

Lifetime map wins

4,277inferno
3,233nuke
2,085vertigo
861dust2
225train
197lake
134cbble
57safehouse

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

Faceit stats

Combat

177Matches
51%Win rate
0.96Avg K/D
76.4ADR
46%Headshot %

Clutches & streaks

42%1v1 clutch win
20%1v2 clutch win
10Longest win streak

Recent Faceit resultsLWLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage3653%1.0915.1
Nuke3256%0.9514.9
Inferno3269%0.9013.0
Vertigo2045%0.9715.1
Ancient1443%1.1316.1
Anubis1155%1.0114.8
Dust2520%0.6911.4
Overpass3100%1.1522.7

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.

15.8%Headshot accuracy
31.9%Accuracy (enemy spotted)
38.0%Spray accuracy
77.9%Counter-strafing
9.9°Preaim
590msReaction time
29.7%T opening success
50.8%CT opening success
0.51Enemies flashed / flash
4.0%Flash assists
9.32HE damage / grenade
5.88Flashes / 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 29.6525% — below the 40% mark we flag

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.

33% win rate across 18 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
ancient10–13-0.0115%11 Jun
ancient13–50.0111%26 Mar
ancient13–6-0.0217%11 Mar
anubis4–1-0.0230%10 Mar
overpass9–13-0.0620%2 Mar
mirage13–30.1215%2 Mar
overpass13–90.0314%2 Mar
overpass16–14-0.0510%2 Mar
dust213–80.0624%2 Mar
nuke1–9-0.0523%12 Feb
mirage11–130.0518%12 Feb
mirage13–40.0511%11 Feb
mirage13–70.0410%11 Feb
mirage12–12-0.0110%11 Feb
mirage13–100.0521%10 Feb
inferno4–130.0112%8 Feb
mirage10–130.0622%3 Feb
mirage1–9-0.0115%27 Jan
nuke4–130.0025%27 Jan
mirage2–130.0131%26 Jan
ancient8–13-0.079%26 Jan
overpass2–9-0.0524%26 Jan
inferno3–13-0.078%26 Jan
anubis11–130.0114%26 Jan
inferno13–9-0.0517%23 Jan
ancient13–10.079%23 Jan
mirage13–16-0.0416%22 Jan
mirage16–140.026%22 Jan
anubis13–20.0216%20 Jan
ancient12–120.0927%19 Jan
train1–30.1127%19 Jan
vertigo13–30.1016%19 Jan
mirage13–40.0213%19 Jan
mirage9–13-0.0510%16 Jan
inferno13–10.136%13 Jan
nuke9–60.1131%13 Jan
overpass9–70.0121%13 Jan
mirage8–13-0.0415%13 Jan
nuke13–90.0520%12 Jan
overpass13–90.0419%12 Jan
mirage6–130.0510%12 Jan
ancient13–70.0214%12 Jan
dust213–100.0019%12 Jan
overpass13–90.0724%12 Jan
train13–80.0824%11 Jan
train9–13-0.0117%10 Jan
inferno13–60.0114%10 Jan
overpass13–100.0621%10 Jan
mirage6–130.057%9 Jan
nuke12–160.0113%9 Jan
mirage10–130.049%9 Jan
dust213–20.1316%4 Jan
inferno13–60.0414%4 Jan
nuke0–11-0.0410%3 Jan
mirage7–130.0729%3 Jan
inferno8–13-0.0511%2 Jan
mirage16–130.0410%31 Dec
inferno6–13-0.0419%30 Dec
nuke13–30.0814%30 Dec
train13–10-0.0114%30 Dec
inferno5–13-0.0415%25 Dec
mirage11–130.016%21 Dec
inferno8–130.0210%19 Dec
overpass13–100.0217%19 Dec
overpass13–90.1012%12 Dec
mirage4–130.0423%12 Dec
nuke9–130.0416%12 Dec
nuke8–130.0419%12 Dec
inferno13–30.0813%12 Dec
overpass8–13-0.0118%12 Dec
nuke13–11-0.0215%25 Nov
mirage13–50.1312%24 Nov
dust213–10.0716%24 Nov
mirage13–50.0520%24 Nov
ancient13–5-0.0613%21 Nov
inferno13–70.1119%19 Nov
inferno6–130.0113%19 Nov
ancient11–130.0016%9 Nov
ancient13–60.057%31 Oct
inferno9–10-0.028%26 Oct
nuke9–13-0.0521%24 Oct
golden1–6-0.100%22 Oct
ancient8–13-0.036%22 Oct
ancient13–50.0317%22 Oct
ancient11–13-0.0531%14 Oct
ancient13–10.0211%10 Oct
ancient13–160.0921%8 Oct
overpass13–11-0.0117%1 Oct
inferno10–13-0.0612%12 Sept
ancient8–13-0.084%12 Sept
overpass7–13-0.0413%27 Aug
nuke13–100.0911%25 Aug
ancient11–130.0315%23 Aug
anubis3–13-0.0712%23 Aug
inferno10–130.0317%7 Aug
mirage3–10-0.019%3 Aug
anubis13–70.0621%29 Jul
inferno9–130.1614%29 Jul
inferno12–120.0420%23 Jul
mirage0–13-0.046%23 Jul

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 →