Liz Kirk

Liz Kirk — CS2 Stats

76561198120703302[U:1:160437574]Steam profile ↗✓ No bans

188Tracked matches60%Win rate2026Tracked since
155Hours in CS25Hrs last 2 wks
CSDB Rating4.1 DevelopingPositional Player
Premier CS Rating5,118Light Blue band · top ~78.2% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Oct 2026 (9 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: 5,118 +457 20 Sept – 3 Oct · 9 days played
4,5625,118peak 5,11820 Sept3 Oct
5,118Peak Premier in tracked matches
32Days played since 2026-08-27

Premier CS Rating

  • At peak — 5,118
  • Next: Blue band at 10,000 — 4,882 to go
  • Reached: Light Blue band

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 Light Blue band among CSDB-tracked players (n=8,820), 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 playerLight Blue band medianBlue band medianvs Blue band
Headshot rate44.0%39.9%42.0%above
Shot accuracy0.0%7.0%9.6%9.6% short
Kill/death ratio0.800.920.980.18 short
Match win rate43.4%42.3%43.8%meets

This profile matches the typical Blue band player on 2 of 4 comparable metrics.

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

Share this profile

CSDB.GGLiz KirkPREMIER5,118 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim44
Positioning54
Utility19

0–100 skill scores via Leetify.

Recent form

HOT46–49–5Last 10046%Win rateWWLWWWWLWW

Last 10 vs previous 10: +30pp win rate · +0.02 avg rating · −4.3pp headshot accuracy · −74ms reaction

Win rate up 30pp 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

  • 4–1 · 80% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 9%
  • Avg reaction 611ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 11%
  • Avg reaction 606ms

Last 20

  • 13–7 · 65% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 643ms

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 (+2.1 against its own average).

Aim4.4
Utility1.9
Positioning5.4
Opening Duels2.5

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

donk

Plays most like donk 83% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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

CT openings. Opening success drops from 57% on T to 37% on CT — first contacts on the defending side are being lost.

Reaction time. 662ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim4.4
Positioning5.4
Utility1.9
Mechanics4.2
Opening Duels4.2
Win Impact8.3

Composite 4.1/10 (Developing), 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+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time663ms+10ms
first ⅓ avg 654ms → last ⅓ avg 663ms
Headshot accuracy16.1%−3.3%
first ⅓ avg 19.4% → last ⅓ avg 16.1%

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

0.13Best match rating · 3–13 · cache, 9 Sept →
52%Best headshot accuracy · 7–13 · vertigo, 23 Sept →
484msFastest reaction time · 13–10 · dust2, 7 Sept →
13–1Biggest win · mirage, 25 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W2Current streak
7–5In matches decided by ≤2 rounds
5Overtime games

Map breakdown

anubisBest map · 75% over 12ancientWeakest map · 27% over 15
MapGradePlayedRecordWin rateAvg rating
ancientD154–1127%-0.04
vertigoB137–654%-0.00
anubisS129–375%0.02
dust2A116–555%-0.00
nukeB105–550%0.01
infernoB105–550%-0.02
trainA95–456%0.01
cacheD72–529%-0.02
mirageD72–529%0.02
office—30–30%-0.07
italy—11–0100%-0.01
overpass—10–10%-0.02
boulder—10–10%-0.08

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (27% over 15). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

3,415Lifetime kills
0.80K/D
297Matches
43.4%Match win rate · Top 50% of Light Blue band
44.0%Headshot % · Top 50% of Light Blue band
0.0%Shot accuracy
481MVPs
84Hours (in match)
197Bombs planted
54Bombs defused

Most-used weapons

Lifetime map wins

240vertigo
229nuke
185train
160dust2
127inferno
49office
27italy
9lake

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

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
38.6%Accuracy (enemy spotted)
32.3%Spray accuracy
68.9%Counter-strafing
13.0°Preaim
662msReaction time
56.7%T opening success
36.8%CT opening success
0.22Enemies flashed / flash
1.4%Flash assists
9.24HE damage / grenade
1.05Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 12.9703° — above the 12° mark we flag

    Aim Training →
  2. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.2199 — below the 0.5 mark we flag

    Grenade Lineups →
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.

27% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
train13–100.0219%7 Oct →
train13–4-0.018%7 Oct →
ancient8–13-0.019%7 Oct →
vertigo13–2-0.035%4 Oct →
anubis13–8-0.034%3 Oct →
nuke13–110.0413%3 Oct →
dust213–70.1017%3 Oct →
cache6–13-0.0310%3 Oct →
dust213–110.0419%3 Oct →
italy13–10-0.017%3 Oct →
mirage13–60.069%2 Oct →
ancient14–16-0.0712%1 Oct →
ancient8–13-0.069%1 Oct →
vertigo13–100.1017%1 Oct →
train13–50.0428%1 Oct →
ancient1–13-0.0911%28 Sept →
overpass2–13-0.0233%27 Sept →
inferno13–5-0.009%27 Sept →
dust211–13-0.1021%25 Sept →
mirage13–1-0.024%25 Sept →
cache10–13-0.0615%24 Sept →
vertigo7–13-0.0552%23 Sept →
nuke13–8-0.0122%23 Sept →
mirage5–130.0824%23 Sept →
inferno5–13-0.0621%22 Sept →
inferno13–8-0.0315%21 Sept →
ancient13–7-0.0311%20 Sept →
nuke10–130.0125%20 Sept →
anubis13–30.0513%20 Sept →
inferno13–2-0.038%19 Sept →
mirage8–130.0624%19 Sept →
anubis11–30.0124%18 Sept →
ancient15–15-0.0613%18 Sept →
ancient7–130.0310%17 Sept →
dust28–13-0.0322%17 Sept →
office6–13-0.0716%17 Sept →
anubis13–11-0.018%16 Sept →
anubis7–13-0.0115%16 Sept →
train0–5-0.138%15 Sept →
ancient16–14-0.026%13 Sept →
cache13–4-0.0826%13 Sept →
nuke15–15-0.0415%11 Sept →
inferno15–15-0.0415%11 Sept →
ancient11–13-0.033%11 Sept →
ancient13–6-0.069%11 Sept →
anubis13–40.024%11 Sept →
train12–120.0318%10 Sept →
inferno13–30.0812%10 Sept →
ancient13–6-0.0212%10 Sept →
inferno1–130.0025%10 Sept →
ancient9–13-0.057%10 Sept →
inferno13–6-0.0311%9 Sept →
cache3–130.1321%9 Sept →
vertigo13–20.0517%9 Sept →
inferno4–13-0.100%8 Sept →
ancient9–13-0.0411%8 Sept →
anubis13–90.0313%8 Sept →
anubis13–20.0417%8 Sept →
ancient0–3-0.090%8 Sept →
train3–130.0318%8 Sept →
dust27–130.0724%8 Sept →
dust213–8-0.0313%8 Sept →
dust23–80.027%8 Sept →
anubis3–130.0412%8 Sept →
dust213–30.0512%8 Sept →
dust213–5-0.0121%8 Sept →
nuke8–13-0.0519%8 Sept →
mirage10–130.0115%7 Sept →
dust213–100.0419%7 Sept →
cache6–13-0.0017%7 Sept →
vertigo13–3-0.1010%7 Sept →
anubis13–10-0.0014%7 Sept →
vertigo13–70.0914%7 Sept →
train13–110.0020%7 Sept →
anubis3–130.0542%7 Sept →
train5–120.0418%7 Sept →
vertigo13–50.0315%7 Sept →
vertigo9–130.0928%7 Sept →
vertigo0–13-0.0914%7 Sept →
train13–70.038%6 Sept →
boulder1–13-0.089%6 Sept →
mirage4–130.0028%6 Sept →
office7–13-0.0729%6 Sept →
mirage12–12-0.0621%2 Sept →
office11–13-0.0624%2 Sept →
nuke13–11-0.0427%1 Sept →
cache13–10-0.0413%31 Aug →
inferno7–13-0.0314%31 Aug →
cache4–13-0.0418%30 Aug →
ancient5–13-0.0122%30 Aug →
vertigo0–13-0.0836%29 Aug →
anubis13–100.0212%29 Aug →
nuke13–110.0840%28 Aug →
nuke13–6-0.0128%28 Aug →
nuke11–130.0734%28 Aug →
nuke10–130.0927%27 Aug →
dust20–6-0.140%27 Aug →
vertigo9–13-0.086%27 Aug →
vertigo4–130.0512%27 Aug →
vertigo13–80.018%27 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

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