abe!

abe! — CS2 Stats

76561198278569664[U:1:318303936]Steam profile ↗✓ No bans

1,116Tracked matches61%Win rate2020Tracked since
1,314Hours in CS5Hrs last 2 wks
CSDB Rating7.0 StrongPositional Player
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Sep 2026 (42 days ago). Ranks are recorded once per day this page is viewed.

+25Tracked matches · now 1,116
−16.0ppWin rate · 76.7% → 60.7%

Rating over time

40Days played since 2026-07-22

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Performance scores

Aim78
Positioning67
Utility51

0–100 skill scores via Leetify.

Recent form

STEADY60–35–5Last 10060%Win rateLWLWLWLWWW

Last 10 vs previous 10: 0pp win rate · +0.02 avg rating · +2.0pp headshot accuracy · −95ms 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 -0.00
  • Avg headshot accuracy 17%
  • Avg reaction 536ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 16%
  • Avg reaction 499ms

Last 20

  • 12–6–2 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 15%
  • Avg reaction 546ms

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 (+1 against its own average).

Aim7.8
Utility5.1
Positioning6.7
Opening Duels4.8
Clutch6.0

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

jL

Plays most like jL 95% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: 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

Strengths

T openings. 63% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 63% on T to 47% on CT — first contacts on the defending side are being lost.

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

Aim7.8
Positioning6.7
Utility5.1
Mechanics7.1
Opening Duels6.2
Win Impact8.6

Composite 7.0/10 (Strong), 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 rating0.00+0.00
first ⅓ avg -0.00 → last ⅓ avg 0.00
Reaction time539ms−54ms
first ⅓ avg 593ms → last ⅓ avg 539ms
Headshot accuracy14.9%−4.9%
first ⅓ avg 19.8% → last ⅓ avg 14.9%

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

0.17Best match rating · 13–5 · train, 15 Aug →
56%Best headshot accuracy · 13–3 · ancient, 8 Aug →
391msFastest reaction time · 13–7 · mirage, 23 Aug →
13–2Biggest win · vertigo, 18 Aug →

Across the last 100 tracked matches.

Highlights

9Longest win streak
7–2In matches decided by ≤2 rounds

Map breakdown

mirageBest map · 80% over 15dust2Weakest map · 29% over 17
MapGradePlayedRecordWin rateAvg rating
dust2D175–1229%-0.01
nukeB158–753%0.01
mirageS1512–380%0.00
ancientS129–375%0.00
infernoB105–550%0.01
trainA85–363%0.00
vertigoS75–271%0.02
cacheA74–357%0.00
anubisS64–267%0.03
overpass—22–0100%-0.01
office—11–0100%-0.00

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (29% over 17). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

25,916Lifetime kills
1.05K/D · Top 50% of tracked players
1,614Matches
51.2%Match win rate · Top 25% of tracked players
41.0%Headshot %
1.3%Shot accuracy
3,486MVPs
575Hours (in match)
1,572Bombs planted
259Bombs defused

Most-used weapons

Lifetime map wins

3,089dust2
1,604inferno
1,561nuke
1,345train
870vertigo
268office
40italy
3ar_baggage

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

Faceit stats

Combat

4Matches
100%Win rate
1.22Avg K/D
95.4ADR
46%Headshot %

Clutches & streaks

50%1v1 clutch win
50%1v2 clutch win
4Longest win streak

Recent Faceit resultsLWWWW

MapMatchesWin rateAvg K/DAvg kills
Mirage2100%1.3817.0
Dust21100%1.4227.0
Ancient1100%0.7112.0

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.

15.3%Headshot accuracy
35.6%Accuracy (enemy spotted)
40.9%Spray accuracy
81.9%Counter-strafing
9.1°Preaim
535msReaction time
63.3%T opening success
46.6%CT opening success
0.66Enemies flashed / flash
7.9%Flash assists
5.78HE damage / grenade
5.77Flashes / match

Recommended for you

Spend your practice time on Dust 2

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 17 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke3–13-0.0719%24 Oct →
vertigo13–10-0.0113%24 Oct →
dust25–130.0018%24 Oct →
dust213–60.0414%24 Oct →
cache8–130.0220%24 Oct →
train13–7-0.0415%19 Oct →
dust23–130.036%18 Oct →
cache9–30.0125%12 Oct →
dust213–70.0818%12 Oct →
mirage13–100.0516%10 Oct →
inferno12–12-0.0217%8 Oct →
ancient13–110.0014%8 Oct →
vertigo10–13-0.0222%6 Oct →
cache12–120.0115%6 Oct →
mirage13–8-0.0613%6 Oct →
mirage4–13-0.0713%5 Oct →
vertigo12–20.0716%5 Oct →
nuke13–6-0.018%5 Oct →
ancient13–5-0.0114%30 Sept →
nuke13–90.0513%29 Sept →
dust28–13-0.0113%29 Sept →
overpass13–30.0013%24 Sept →
anubis11–130.0315%24 Sept →
train5–13-0.0517%13 Sept →
dust27–13-0.0523%13 Sept →
ancient10–130.019%10 Sept →
mirage13–8-0.0021%10 Sept →
dust213–9-0.0219%10 Sept →
anubis13–110.0212%7 Sept →
dust213–110.0211%7 Sept →
mirage13–90.072%7 Sept →
train1–13-0.0413%3 Sept →
nuke10–2-0.0216%3 Sept →
cache13–90.029%1 Sept →
dust26–13-0.0126%1 Sept →
inferno13–80.1117%1 Sept →
mirage13–4-0.016%29 Aug →
mirage3–13-0.0112%28 Aug →
anubis13–110.0114%28 Aug →
inferno13–80.0416%28 Aug →
mirage13–11-0.0511%25 Aug →
train13–110.0113%25 Aug →
inferno13–80.0717%24 Aug →
nuke13–70.0123%24 Aug →
ancient13–80.0012%24 Aug →
nuke8–10.0311%23 Aug →
mirage13–7-0.0018%23 Aug →
inferno11–130.0220%23 Aug →
nuke10–130.0513%23 Aug →
dust213–4-0.0222%22 Aug →
cache6–13-0.0122%22 Aug →
ancient13–9-0.0412%22 Aug →
nuke13–10-0.0010%22 Aug →
mirage13–70.0415%21 Aug →
nuke13–8-0.0215%21 Aug →
ancient7–13-0.0419%21 Aug →
cache13–11-0.0214%19 Aug →
dust28–130.0524%19 Aug →
inferno4–13-0.0422%18 Aug →
train13–7-0.0411%18 Aug →
vertigo13–20.0915%18 Aug →
cache13–90.0110%17 Aug →
nuke12–120.0414%17 Aug →
nuke13–20.1214%15 Aug →
ancient13–100.0220%15 Aug →
train13–50.1724%15 Aug →
dust23–130.0518%15 Aug →
office13–8-0.0015%14 Aug →
mirage13–8-0.016%14 Aug →
dust27–13-0.0330%14 Aug →
inferno13–70.0216%13 Aug →
nuke12–120.009%13 Aug →
ancient13–7-0.0028%11 Aug →
mirage1–13-0.0219%11 Aug →
dust23–13-0.0811%11 Aug →
dust27–13-0.0313%9 Aug →
mirage13–20.1121%9 Aug →
ancient6–13-0.0616%9 Aug →
vertigo13–100.0422%8 Aug →
anubis9–130.0435%8 Aug →
ancient13–30.0856%8 Aug →
nuke8–130.0112%8 Aug →
dust21–13-0.0717%8 Aug →
train6–130.0129%8 Aug →
nuke12–120.0128%7 Aug →
inferno8–13-0.0423%7 Aug →
overpass13–10-0.0119%6 Aug →
anubis13–100.0213%6 Aug →
nuke5–13-0.0316%1 Aug →
train13–50.0125%31 Jul →
ancient13–20.0612%31 Jul →
vertigo13–4-0.049%31 Jul →
vertigo10–130.0115%30 Jul →
inferno13–7-0.0320%30 Jul →
mirage13–80.0413%26 Jul →
mirage13–8-0.0311%24 Jul →
ancient13–8-0.017%24 Jul →
dust23–13-0.0636%24 Jul →
inferno5–13-0.0128%24 Jul →
anubis13–70.0322%22 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 →

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