Al The Alligator

Al The Alligator — CS2 Stats

DK76561198013922813[U:1:53657085]Steam profile ↗✓ No bans

665Tracked matches50%Win rate2020Tracked since
2,374Hours in CS3Hrs last 2 wks
CSDB Rating4.8 DevelopingAll-Rounder
Premier CS Rating21,018Top 50% of 210,584 CSDB-tracked playersPink band · top ~7.4% of ranked players (population est.)
CSDB Leaderboard#68967 of 257569 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 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: 21,018 +11,019 21 Nov – 23 Oct · 16 days played
9,99921,018peak 21,01821 Nov23 Oct
21,018Peak Premier in tracked matches
43Days played since 2023-11-21

Premier CS Rating

  • At peak — 21,018
  • Next: Red band at 25,000 — 3,982 to go
  • Reached: Pink band · 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 Pink band among CSDB-tracked players (n=38,294), 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 playerPink band medianRed band medianvs Red band
Headshot rate45.4%46.9%49.3%3.8% short
Shot accuracy18.3%13.0%13.4%above
Kill/death ratio1.241.081.12above
Match win rate42.5%46.7%48.5%6.0% short

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

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

Share this profile

CSDB.GGAl The AlligatorPREMIER21,018 · Pink 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

Aim41
Positioning56
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY52–46–2Last 10052%Win rateWLWWLLLLLW

Last 10 vs previous 10: −30pp win rate · +0.02 avg rating · +4.3pp headshot accuracy · +19ms reaction

Win rate down 30pp 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

  • 3–2 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 18%
  • Avg reaction 592ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 20%
  • Avg reaction 629ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 18%
  • Avg reaction 620ms

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-Rounder — No style dimension stands clear of the others in this profile.

Aim4.1
Utility4.6
Positioning5.6
Opening Duels4.5

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

m0NESY

Plays most like m0NESY 66% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower positioning profile; 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. 643ms 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

Aim4.1
Positioning5.6
Utility4.6
Mechanics4.5
Opening Duels5.0
Win Impact5.0

Composite 4.8/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00−0.00
first ⅓ avg 0.00 → last ⅓ avg 0.00
Reaction time635ms−69ms
first ⅓ avg 705ms → last ⅓ avg 635ms
Headshot accuracy16.6%+1.5%
first ⅓ avg 15.0% → last ⅓ avg 16.6%

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

0.25Best match rating · 9–13 · inferno, 30 Nov →
33%Best headshot accuracy · 13–0 · nuke, 31 Mar →
438msFastest reaction time · 11–13 · vertigo, 30 Jan →
13–0Biggest win · inferno, 18 Jan →

Across the last 100 tracked matches.

Highlights

7Longest win streak
11–12In matches decided by ≤2 rounds
13Overtime games

Map breakdown

anubisBest map · 67% over 9cacheWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
infernoB2714–1352%0.02
nukeS1711–665%0.02
ancientB157–847%0.00
overpassB105–550%0.01
anubisS96–367%-0.03
vertigoA85–363%0.01
cacheD61–517%0.01
mirage—42–250%0.00
dust2—31–233%-0.00
train—10–10%-0.07

Across the last 100 tracked matches.

Lifetime stats

89,428Lifetime kills
1.24K/D · Top 25% of Pink band
3,484Matches
42.5%Match win rate
45.4%Headshot %
18.3%Shot accuracy · Top 10% of Pink band
11,606MVPs
1,374Hours (in match)
5,410Bombs planted
1,268Bombs defused

Most-used weapons

AK-4715,617
AWP12,065
SG 5537,280
AUG2,581
FAMAS1,690
Tec-91,543

Lifetime map wins

7,543inferno
5,791nuke
5,588dust2
2,959vertigo
525train
470cbble
284lake
89militia

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.

16.2%Headshot accuracy
29.0%Accuracy (enemy spotted)
30.1%Spray accuracy
70.0%Counter-strafing
9.6°Preaim
643msReaction time
44.7%T opening success
55.0%CT opening success
0.65Enemies flashed / flash
4.3%Flash assists
12.16HE damage / grenade
2.95Flashes / 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

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 2.9475 — below the 4 mark we flag

    Grenade Lineups →
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.

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
inferno13–90.0717%23 Oct →
ancient5–13-0.0015%23 Oct →
anubis13–3-0.0311%23 Oct →
inferno13–30.0324%23 Oct →
dust25–13-0.0024%23 Oct →
cache6–130.0230%23 Sept →
nuke11–130.1032%22 Sept →
cache5–130.0225%18 Sept →
cache10–130.0115%9 Sept →
inferno13–2-0.018%9 Sept →
ancient3–13-0.0619%24 Aug →
cache16–140.0132%24 Aug →
ancient13–90.0720%24 Aug →
ancient13–100.0614%17 Aug →
nuke13–40.0117%17 Aug →
inferno13–50.034%11 Aug →
nuke13–9-0.0510%11 Aug →
anubis13–11-0.0319%10 Aug →
cache14–16-0.0018%9 Jul →
ancient14–16-0.064%1 Jun →
dust28–13-0.0216%1 Jun →
inferno8–13-0.0511%1 Jun →
ancient8–13-0.1017%1 Jun →
anubis13–100.016%24 May →
nuke7–13-0.0610%19 May →
overpass7–130.0413%13 May →
cache5–13-0.0016%13 May →
anubis13–11-0.076%11 May →
overpass13–70.0213%11 May →
ancient13–70.0217%11 May →
inferno13–7-0.0218%11 May →
inferno13–10-0.0619%23 Apr →
nuke13–10.1426%20 Apr →
inferno13–16-0.0319%7 Apr →
inferno6–130.0216%30 Dec →
nuke13–9-0.0719%30 Dec →
ancient11–13-0.0315%29 Sept →
overpass10–130.018%29 Sept →
nuke13–60.049%29 Sept →
inferno13–60.0726%29 Sept →
train10–13-0.0712%29 Sept →
mirage13–70.0725%15 Sept →
ancient9–130.0017%16 May →
dust216–140.0111%16 May →
ancient13–50.0027%15 Apr →
inferno13–10.1115%18 Jan →
nuke13–80.0322%18 Jan →
inferno16–140.0814%18 Jan →
ancient8–130.0514%18 Jan →
inferno13–00.0822%18 Jan →
inferno10–130.0313%18 Jan →
inferno12–120.0319%25 Nov →
nuke8–130.0828%25 Nov →
inferno13–60.0623%25 Oct →
inferno12–12-0.0210%25 Oct →
nuke13–00.0933%31 Mar →
overpass13–60.0219%31 Mar →
ancient13–90.0416%31 Mar →
mirage7–13-0.0827%31 Mar →
inferno8–130.0721%7 Mar →
vertigo11–130.0120%30 Jan →
vertigo13–50.0821%30 Jan →
overpass9–13-0.0520%30 Jan →
inferno6–130.0115%30 Dec →
overpass10–13-0.0117%30 Dec →
nuke13–100.0318%30 Dec →
nuke14–160.0511%23 Dec →
inferno11–130.016%23 Dec →
overpass13–40.0121%23 Dec →
inferno14–16-0.0416%19 Dec →
anubis5–13-0.119%19 Dec →
anubis11–130.0115%15 Dec →
inferno16–120.0815%15 Dec →
vertigo14–16-0.0311%15 Dec →
mirage3–13-0.0722%9 Dec →
overpass13–110.0719%9 Dec →
vertigo11–13-0.0311%6 Dec →
inferno3–13-0.0514%6 Dec →
vertigo13–8-0.044%6 Dec →
overpass12–16-0.0313%4 Dec →
vertigo13–9-0.025%4 Dec →
vertigo13–80.0818%4 Dec →
ancient14–160.0314%3 Dec →
nuke13–100.0317%3 Dec →
inferno7–13-0.0611%3 Dec →
nuke13–100.0417%3 Dec →
anubis4–13-0.0314%1 Dec →
mirage13–90.0813%1 Dec →
nuke9–13-0.0114%1 Dec →
vertigo13–100.0521%1 Dec →
inferno9–130.2524%30 Nov →
anubis13–11-0.0811%29 Nov →
inferno13–110.0316%27 Nov →
ancient13–40.0117%27 Nov →
nuke6–13-0.0825%27 Nov →
nuke13–60.0028%27 Nov →
overpass16–140.0315%26 Nov →
anubis13–110.0314%26 Nov →
ancient13–80.029%26 Nov →
inferno13–11-0.0614%21 Nov →

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 →

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