Kare (Bear)

Kare (Bear) — CS2 Stats

76561197967238748[U:1:6973020]Steam profile ↗✓ No bans

1,712Tracked matches63%Win rate2023Tracked since
5,768Hours in CS34Hrs last 2 wks
CSDB Rating6.0 SolidSupport
Premier CS Rating17,854Purple band · top ~17% of ranked players (population est.)
WingmanGold Nova III
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 31 Oct 2026 (5 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: 17,854 +3,346 28 Jul – 31 Oct · 18 days played
14,40417,854peak 17,85428 Jul31 Oct
17,854Peak Premier in tracked matches
1,182Highest Faceit ELO seen on CSDB
48Days played since 2026-07-21

Faceit ELO

  • At peak — 1,182
  • Next: Level 6 at 1,201 — 19 to go
  • Reached: Level 5 · Level 4 · Level 3 · Level 2

Premier CS Rating

  • At peak — 17,854
  • +1,385 over 30 days · improving
  • +3,074 over 90 days
  • Next: Pink band at 20,000 — 2,146 to go
  • Reached: Purple band · Blue band · 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 Purple band among CSDB-tracked players (n=37,767), 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 playerPurple band medianPink band medianvs Pink band
Headshot rate58.5%44.4%46.9%above
Shot accuracy4.2%11.9%13.0%8.8% short
Kill/death ratio1.651.031.08above
Match win rate39.0%45.2%46.7%7.6% short

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

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

Share this profile

CSDB.GGKare (Bear)PREMIER17,854 · Purple bandPEAK ELO1,182csdb.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

Aim70
Positioning56
Utility59

0–100 skill scores via Leetify.

Recent form

STEADY50–38–12Last 10050%Win rateLLWLWWWWLL

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · −0.8pp headshot accuracy · +9ms 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

  • 2–3 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 11%
  • Avg reaction 533ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 12%
  • Avg reaction 536ms

Last 20

  • 10–7–3 · 50% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 13%
  • Avg reaction 531ms

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: Support — Utility contribution stands above the rest of this profile (+1.9 against its own average).

Aim7.0
Utility5.9
Positioning5.6
Opening Duels1.3
Clutch3.2

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

iM

Plays most like iM 83% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; lower opening-duel success.

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

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

Aim7.0
Positioning5.6
Utility5.9
Mechanics4.3
Opening Duels3.5
Win Impact9.2

Composite 6.0/10 (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 rating0.01+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time520ms−72ms
first ⅓ avg 593ms → last ⅓ avg 520ms
Headshot accuracy13.8%−0.2%
first ⅓ avg 14.0% → last ⅓ avg 13.8%

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

0.14Best match rating · 13–6 · anubis, 31 Oct →
30%Best headshot accuracy · 13–5 · mirage, 25 Aug →
328msFastest reaction time · 6–13 · office, 2 Sept →
13–0Biggest win · ancient, 8 Aug →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L2Current streak
7–9In matches decided by ≤2 rounds
5Overtime games

Map breakdown

infernoBest map · 78% over 9cacheWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
ancientB199–1047%-0.01
dust2C177–1041%-0.01
anubisC94–544%0.02
infernoS97–278%-0.01
nukeA85–363%0.01
vertigoA74–357%0.02
mirageA74–357%-0.01
cacheD72–529%-0.01
officeB63–350%0.04
trainD62–433%0.01
overpass—22–0100%0.04
rush_001—11–0100%-0.06
fachwerk—10–10%-0.07
shelter—10–10%-0.03

Across the last 100 tracked matches.

Lifetime stats

214,421Lifetime kills
1.65K/D · Top 5% of Purple band
7,924Matches
39.0%Match win rate
58.5%Headshot % · Top 10% of Purple band
4.2%Shot accuracy
8,215MVPs
3,214Hours (in match)
3,334Bombs planted
790Bombs defused

Most-used weapons

Lifetime map wins

7,441dust2
4,346inferno
4,330nuke
3,227vertigo
1,622train
1,467office
408italy
119cbble

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

Faceit stats

Combat

120Matches
48%Win rate
0.98Avg K/D
74.8ADR
38%Headshot %

Clutches & streaks

36%1v1 clutch win
18%1v2 clutch win
4Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Dust22348%1.2915.9
Nuke2065%1.0014.8
Anubis1850%0.8715.2
Ancient1644%1.0514.3
Inferno1450%1.0413.4
Overpass1217%0.5911.3
Mirage944%1.1015.6
Thera10%0.5610.0

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.

13.6%Headshot accuracy
39.7%Accuracy (enemy spotted)
42.8%Spray accuracy
69.5%Counter-strafing
11.3°Preaim
517msReaction time
44.9%T opening success
43.4%CT opening success
0.57Enemies flashed / flash
4.6%Flash assists
6.72HE damage / grenade
15.76Flashes / 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 13.5688% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Cache

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

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
nuke8–13-0.0116%3 Nov →
ancient7–13-0.0411%1 Nov →
anubis13–60.1413%31 Oct →
office8–13-0.039%31 Oct →
vertigo13–10-0.009%30 Oct →
dust213–70.0511%30 Oct →
nuke13–90.0313%29 Oct →
office13–70.088%29 Oct →
dust24–130.059%29 Oct →
dust26–130.0224%27 Oct →
ancient13–110.0311%25 Oct →
overpass13–20.0416%25 Oct →
train13–100.039%25 Oct →
ancient7–13-0.049%20 Oct →
dust212–12-0.0215%20 Oct →
anubis5–13-0.0315%19 Oct →
office13–70.0622%19 Oct →
inferno13–20.014%19 Oct →
nuke12–120.0518%18 Oct →
train12–120.0610%18 Oct →
mirage15–15-0.045%17 Oct →
rush_0017–3-0.0617%14 Oct →
mirage13–10-0.0312%7 Oct →
train12–12-0.0815%7 Oct →
nuke13–4-0.057%6 Oct →
ancient6–13-0.0313%6 Oct →
ancient13–50.0212%6 Oct →
nuke13–100.0627%6 Oct →
inferno13–6-0.0214%6 Oct →
dust212–12-0.0328%5 Oct →
ancient10–13-0.0020%1 Oct →
dust28–130.0119%1 Oct →
dust213–40.0416%30 Sept →
vertigo13–90.0216%24 Sept →
vertigo13–40.078%24 Sept →
ancient15–15-0.0212%22 Sept →
dust216–14-0.0211%20 Sept →
anubis13–50.099%20 Sept →
anubis13–80.029%16 Sept →
cache8–13-0.039%16 Sept →
ancient13–7-0.027%16 Sept →
mirage12–12-0.0113%16 Sept →
train13–100.0619%12 Sept →
nuke13–30.0515%12 Sept →
dust29–130.0218%9 Sept →
ancient13–30.0815%9 Sept →
cache11–13-0.0613%8 Sept →
mirage13–110.029%8 Sept →
office13–20.128%5 Sept →
anubis10–130.0813%5 Sept →
dust213–8-0.047%5 Sept →
vertigo11–13-0.0212%3 Sept →
office7–13-0.0320%2 Sept →
office6–130.0526%2 Sept →
train12–12-0.0315%1 Sept →
ancient13–8-0.017%1 Sept →
fachwerk2–13-0.0711%1 Sept →
dust213–10-0.0616%1 Sept →
dust28–13-0.0115%27 Aug →
ancient10–130.0213%26 Aug →
dust213–9-0.047%26 Aug →
inferno13–70.0310%25 Aug →
mirage13–50.0230%25 Aug →
dust213–8-0.0616%24 Aug →
dust215–15-0.0518%18 Aug →
cache7–13-0.0813%11 Aug →
ancient3–13-0.0613%11 Aug →
anubis13–7-0.0315%9 Aug →
cache13–100.069%9 Aug →
anubis10–13-0.0816%8 Aug →
ancient13–6-0.0413%8 Aug →
ancient13–0-0.040%8 Aug →
train9–130.0520%8 Aug →
cache12–120.0113%8 Aug →
dust212–12-0.0116%8 Aug →
vertigo11–130.0915%8 Aug →
inferno13–5-0.0216%8 Aug →
mirage17–19-0.0313%6 Aug →
vertigo10–130.0113%4 Aug →
ancient9–13-0.0610%4 Aug →
mirage13–10-0.0014%3 Aug →
ancient4–13-0.0515%30 Jul →
vertigo13–11-0.0214%29 Jul →
shelter11–13-0.0311%28 Jul →
inferno13–7-0.0130%28 Jul →
cache10–130.0113%28 Jul →
ancient13–30.0211%28 Jul →
ancient7–13-0.0416%28 Jul →
inferno11–13-0.0113%27 Jul →
anubis2–13-0.0511%25 Jul →
ancient13–110.0419%25 Jul →
anubis11–130.0513%25 Jul →
nuke11–13-0.0120%25 Jul →
inferno13–10-0.0116%25 Jul →
cache13–110.0320%24 Jul →
nuke13–10-0.0115%23 Jul →
inferno13–10-0.0811%22 Jul →
dust210–13-0.0410%21 Jul →
inferno11–130.048%21 Jul →
overpass13–110.0417%21 Jul →

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.