Bear Grylls

Bear Grylls — CS2 Stats

CK76561199084944247[U:1:1124678519]Steam profile ↗✓ No bans

534Tracked matches45%Win rate2020Tracked since
1,097Hours in CS
CSDB Rating5.9 SolidPositional Player
FaceitLevel 5Top 67.6% of ranked FACEIT players
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Sep 2026 (53 days ago). Ranks are recorded once per day this page is viewed.

+15Tracked matches · now 534
+6.9ppWin rate · 37.9% → 44.8%

Rating over time

Premier CS Rating: 25,768 -1,463 29 Dec – 8 Apr · 26 days played
23,70528,627peak 28,62729 Dec8 Apr
28,627Peak Premier in tracked matches
37Days played since 2025-12-29

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=14,283), 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 rate44.9%43.8%44.8%meets
Shot accuracy15.2%12.0%12.4%above
Kill/death ratio0.821.021.030.22 short
Match win rate42.6%44.7%45.2%2.7% short

This profile matches the typical Level 6 player on 2 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.GGBear GryllsFACEITLevel 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

Aim82
Positioning56
Utility27

0–100 skill scores via Leetify.

Recent form

STEADY51–47–2Last 10051%Win rateLLLWLWWLWW

Last 10 vs previous 10: +20pp win rate · −0.01 avg rating · +1.9pp headshot accuracy · −52ms reaction

Win rate up 20pp 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 (−0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 20%
  • Avg reaction 635ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 26%
  • Avg reaction 627ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 25%
  • Avg reaction 653ms

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).

Aim8.2
Utility2.7
Positioning5.6
Opening Duels4.1
Clutch0.0

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 89% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower opening-duel success; 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. 661ms 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

Aim8.2
Positioning5.6
Utility2.7
Mechanics7.8
Opening Duels4.3
Win Impact3.3

Composite 5.9/10 (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-0.01−0.04
first ⅓ avg 0.03 → last ⅓ avg -0.01
Reaction time650ms+45ms
first ⅓ avg 605ms → last ⅓ avg 650ms
Headshot accuracy29.1%+3.3%
first ⅓ avg 25.8% → last ⅓ avg 29.1%

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

0.16Best match rating · 13–8 · ancient, 29 Dec →
58%Best headshot accuracy · 8–13 · dust2, 21 Oct →
422msFastest reaction time · 2–13 · inferno, 28 Mar →
13–2Biggest win · mirage, 6 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L3Current streak
17–11In matches decided by ≤2 rounds
10Overtime games

Map breakdown

mirageBest map · 66% over 29nukeWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
mirageS2919–1066%0.03
infernoC167–944%0.04
ancientB136–746%0.02
nukeD103–730%-0.00
anubisA95–456%0.02
overpassC94–544%0.03
dust2B84–450%0.01
cache—42–250%-0.07
train—21–150%0.04

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

45,924Lifetime kills
0.82K/D
3,263Matches
42.6%Match win rate
44.9%Headshot % · Top 50% of Level 5 players
15.2%Shot accuracy · Top 50% of Level 5 players
5,629MVPs
1,097Hours (in match)
1,432Bombs planted
706Bombs defused

Most-used weapons

AK-4712,214
AWP5,464
SSG 081,367
MP91,200
Knife903

Lifetime map wins

3,372vertigo
3,043inferno
1,764nuke
1,092dust2
967train
271cbble
113office
106italy

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

Faceit stats

Combat

641Matches
50%Win rate
0.91Avg K/D
67.0ADR
41%Headshot %

Clutches & streaks

19%1v1 clutch win
0%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage5461%0.8513.1
Vertigo2030%0.8414.8
Ancient1346%0.8513.8
Anubis1267%0.7211.7
Inferno1136%0.7612.4
Nuke825%0.7112.1
Overpass560%0.7712.0
Dust2520%0.719.4

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.

28.5%Headshot accuracy
33.2%Accuracy (enemy spotted)
37.7%Spray accuracy
85.1%Counter-strafing
7.8°Preaim
661msReaction time
47.6%T opening success
47.1%CT opening success
0.40Enemies flashed / flash
2.3%Flash assists
3.55HE damage / grenade
7.38Flashes / 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. 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 0.3987 — below the 0.5 mark we flag

    Grenade Lineups →
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
nuke6–13-0.0526%26 Oct →
cache7–13-0.0818%26 Oct →
ancient4–13-0.0325%26 Oct →
inferno13–110.0213%26 Oct →
mirage11–13-0.0216%22 Oct →
cache13–11-0.0916%22 Oct →
inferno13–11-0.0240%21 Oct →
dust28–13-0.0258%21 Oct →
cache13–110.0122%20 Oct →
nuke13–11-0.0324%20 Oct →
dust213–80.0022%20 Oct →
nuke11–13-0.0315%15 Oct →
dust213–50.0515%15 Oct →
inferno7–13-0.0126%14 Oct →
mirage11–130.0213%14 Oct →
mirage13–2-0.0311%6 Aug →
cache2–13-0.1122%12 Jul →
inferno7–13-0.0835%12 Jul →
ancient6–13-0.0542%13 Jun →
nuke8–13-0.0339%13 Jun →
dust23–13-0.0757%8 Apr →
inferno5–130.0833%6 Apr →
mirage13–8-0.0230%6 Apr →
inferno15–15-0.0141%6 Apr →
mirage13–30.0433%5 Apr →
mirage10–13-0.0022%1 Apr →
anubis13–60.0040%1 Apr →
inferno13–30.1152%1 Apr →
overpass7–13-0.0123%30 Mar →
mirage13–110.1038%30 Mar →
inferno2–130.0156%28 Mar →
mirage11–130.0013%28 Mar →
nuke11–13-0.0222%27 Mar →
inferno13–50.0220%27 Mar →
mirage13–110.0123%23 Mar →
nuke9–130.1041%23 Mar →
mirage7–130.0441%18 Mar →
mirage13–100.0528%18 Mar →
inferno9–13-0.0228%11 Feb →
ancient13–16-0.0140%11 Feb →
mirage9–130.1337%11 Feb →
dust26–130.0825%11 Feb →
ancient5–13-0.0520%8 Feb →
anubis16–120.0923%3 Feb →
mirage13–40.0716%3 Feb →
ancient8–130.0526%3 Feb →
ancient10–13-0.0616%3 Feb →
anubis2–13-0.0120%1 Feb →
dust24–13-0.0510%1 Feb →
anubis13–5-0.0221%1 Feb →
mirage13–110.0624%30 Jan →
ancient6–130.0026%30 Jan →
nuke13–60.1446%30 Jan →
mirage13–11-0.0017%29 Jan →
mirage13–70.0029%29 Jan →
inferno13–80.1327%29 Jan →
mirage13–11-0.0411%29 Jan →
anubis11–130.1220%29 Jan →
overpass9–130.1628%28 Jan →
overpass13–90.0715%26 Jan →
ancient13–30.0617%26 Jan →
overpass13–11-0.0620%24 Jan →
mirage13–90.0930%24 Jan →
mirage3–13-0.0714%24 Jan →
ancient13–40.0723%24 Jan →
dust213–50.0728%24 Jan →
mirage13–70.1030%23 Jan →
anubis16–130.0832%23 Jan →
anubis16–14-0.0414%23 Jan →
anubis5–13-0.0021%23 Jan →
nuke13–11-0.0228%22 Jan →
overpass6–13-0.0244%22 Jan →
mirage13–5-0.0520%22 Jan →
anubis11–13-0.0317%22 Jan →
nuke11–13-0.0237%22 Jan →
mirage13–100.0020%22 Jan →
mirage13–110.0523%17 Jan →
ancient16–14-0.0021%17 Jan →
inferno13–70.0533%17 Jan →
nuke1–4-0.1033%16 Jan →
mirage7–13-0.0918%16 Jan →
mirage13–90.1123%16 Jan →
train13–50.0326%16 Jan →
ancient16–140.0520%15 Jan →
ancient13–70.0917%15 Jan →
overpass14–160.0521%11 Jan →
overpass13–70.0516%11 Jan →
dust213–30.0632%11 Jan →
train11–130.0527%11 Jan →
mirage11–130.0426%8 Jan →
inferno2–130.0530%8 Jan →
inferno8–130.0933%2 Jan →
overpass13–70.0138%2 Jan →
mirage16–140.0821%2 Jan →
mirage13–90.0420%30 Dec →
inferno15–150.0735%30 Dec →
mirage6–130.0323%29 Dec →
ancient13–80.1626%29 Dec →
overpass9–130.0324%29 Dec →
inferno13–50.0727%29 Dec →

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 →

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