mike oxlong

mike oxlong — CS2 Stats

76561198079667708[U:1:119401980]Steam profile ↗✓ No bans

3,279Tracked matches43%Win rate2020Tracked since
4,279Hours in CS
CSDB Rating5.9 SolidPositional Player
Premier CS Rating13,121Blue band · top ~38.4% of ranked players (population est.)
FaceitLevel 3Top 90.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 1 Nov 2026 (2 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: 13,121 +1,388 30 Aug – 1 Nov · 29 days played
11,73316,078peak 16,07830 Aug1 Nov
16,487Peak Premier in tracked matches
26Days played since 2026-08-30

Premier CS Rating

  • 2,957 below peak (16,078)
  • -1,414 over 30 days · declining
  • Next: Purple band at 15,000 — 1,879 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Blue band first seen 2026-08-30
  • Light Blue band first seen 2026-08-30

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 3 among CSDB-tracked players (n=10,505), 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 3 medianLevel 4 medianvs Level 4
Headshot rate42.8%41.8%42.7%meets
Shot accuracy9.8%12.2%11.2%1.4% short
Kill/death ratio0.950.980.990.04 short
Match win rate44.2%43.3%43.9%meets

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

Widest gap: Shot accuracy. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGmike oxlongFACEITLevel 3STANDINGTop 90.6% of rankedPREMIER13,121 · Blue 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

Aim75
Positioning61
Utility55

0–100 skill scores via Leetify.

Recent form

COLD47–48–5Last 10047%Win rateLWLLLLLWLL

Last 10 vs previous 10: −10pp win rate · +0.03 avg rating · +0.5pp headshot accuracy · −38ms reaction

Win rate −10pp 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

  • 1–4 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 22%
  • Avg reaction 577ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 22%
  • Avg reaction 563ms

Last 20

  • 5–13–2 · 25% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 22%
  • Avg reaction 582ms

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 (+0.9 against its own average).

Aim7.5
Utility5.5
Positioning6.1
Opening Duels3.3
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

NiKo

Plays most like NiKo 92% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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. 65% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 65% on T to 40% on CT — first contacts on the defending side are being lost.

Reaction time. 576ms 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

Aim7.5
Positioning6.1
Utility5.5
Mechanics7.5
Opening Duels5.7
Win Impact2.6

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01
first ⅓ avg -0.00 → last ⅓ avg -0.02
Reaction time581ms−7ms
first ⅓ avg 588ms → last ⅓ avg 581ms
Headshot accuracy21.7%−2.9%
first ⅓ avg 24.6% → last ⅓ avg 21.7%

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 · 13–2 · nuke, 8 Oct →
56%Best headshot accuracy · 6–13 · dust2, 26 Sept →
469msFastest reaction time · 4–13 · anubis, 24 Oct →
13–2Biggest win · nuke, 8 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
2–13In matches decided by ≤2 rounds
15Overtime games

Map breakdown

nukeBest map · 65% over 20anubisWeakest map · 29% over 14
MapGradePlayedRecordWin rateAvg rating
dust2B2210–1245%0.00
nukeS2013–765%0.01
mirageC187–1139%-0.01
anubisD144–1029%-0.02
infernoA148–657%-0.00
ancientA85–363%0.01
cache—30–30%-0.02
office—10–10%-0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (29% over 14). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

176,293Lifetime kills
0.95K/D
9,648Matches
44.2%Match win rate · Top 50% of Level 3 players
42.8%Headshot % · Top 50% of Level 3 players
9.8%Shot accuracy
18,972MVPs
4,279Hours (in match)
2,887Bombs planted
1,123Bombs defused

Most-used weapons

AK-4740,492
AWP27,181
SSG 086,733
MAC-104,124
MP73,476

Lifetime map wins

53,096office
24,847dust2
4,010nuke
3,328inferno
598vertigo
166train
65cbble
53safehouse

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

Faceit stats

Combat

64Matches
48%Win rate
1.07Avg K/D
80.4ADR
45%Headshot %

Clutches & streaks

50%1v1 clutch win
21%1v2 clutch win
5Longest win streak

Recent Faceit resultsLLWLW

MapMatchesWin rateAvg K/DAvg kills
Dust2771%1.4715.3
Mirage450%0.8816.0
Inferno3100%1.969.7
Nuke367%1.1013.0
Train250%1.7216.0

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.

21.7%Headshot accuracy
30.9%Accuracy (enemy spotted)
34.7%Spray accuracy
83.8%Counter-strafing
8.4°Preaim
576msReaction time
65.3%T opening success
40.4%CT opening success
0.52Enemies flashed / flash
4.6%Flash assists
11.05HE damage / grenade
10.48Flashes / match

Recommended for you

Spend your practice time on Anubis

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

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust210–13-0.0324%1 Nov →
dust213–80.1123%1 Nov →
dust29–13-0.0023%1 Nov →
mirage6–13-0.0315%1 Nov →
cache4–13-0.0423%31 Oct →
anubis9–13-0.029%31 Oct →
dust213–16-0.0512%31 Oct →
nuke13–70.0128%31 Oct →
mirage6–130.0936%31 Oct →
office7–13-0.0429%31 Oct →
dust215–15-0.0130%31 Oct →
nuke13–8-0.0411%31 Oct →
mirage13–60.0115%31 Oct →
anubis9–13-0.0223%30 Oct →
nuke2–13-0.0713%30 Oct →
inferno9–13-0.0816%30 Oct →
anubis15–15-0.0222%30 Oct →
dust213–10-0.0239%29 Oct →
nuke0–13-0.0733%29 Oct →
anubis11–13-0.0217%29 Oct →
mirage13–4-0.0917%29 Oct →
inferno13–10-0.0024%25 Oct →
dust213–60.0521%25 Oct →
dust213–100.0223%25 Oct →
mirage4–13-0.0732%24 Oct →
nuke13–90.0719%24 Oct →
inferno13–50.046%24 Oct →
nuke8–13-0.0221%24 Oct →
nuke13–5-0.0711%24 Oct →
anubis4–13-0.0530%24 Oct →
anubis13–70.0017%24 Oct →
inferno3–13-0.0529%24 Oct →
inferno14–16-0.0023%23 Oct →
nuke13–90.0523%23 Oct →
inferno15–15-0.0525%22 Oct →
ancient7–130.0421%18 Oct →
inferno13–9-0.0217%18 Oct →
mirage13–110.0225%18 Oct →
mirage16–13-0.0239%17 Oct →
cache9–130.0123%17 Oct →
anubis7–130.0119%17 Oct →
inferno9–130.0221%17 Oct →
ancient13–80.0529%17 Oct →
dust213–70.0429%16 Oct →
dust211–130.0123%16 Oct →
nuke11–130.043%16 Oct →
mirage3–13-0.0335%15 Oct →
anubis8–13-0.0023%11 Oct →
dust23–130.0129%11 Oct →
inferno13–5-0.0426%11 Oct →
dust27–13-0.0522%11 Oct →
inferno13–70.0031%10 Oct →
mirage13–90.0420%10 Oct →
mirage13–40.0242%10 Oct →
dust215–15-0.0620%9 Oct →
nuke13–9-0.0215%9 Oct →
dust213–40.0636%9 Oct →
anubis13–9-0.0333%9 Oct →
mirage11–13-0.0122%9 Oct →
ancient8–13-0.0413%8 Oct →
dust210–13-0.0628%8 Oct →
dust213–100.0730%8 Oct →
nuke13–20.1324%8 Oct →
anubis13–7-0.0313%3 Oct →
anubis13–8-0.0116%3 Oct →
nuke13–8-0.0517%3 Oct →
nuke16–130.0340%3 Oct →
anubis13–16-0.0410%3 Oct →
nuke8–13-0.0120%2 Oct →
ancient13–7-0.0233%2 Oct →
ancient13–6-0.0023%2 Oct →
mirage10–13-0.0815%2 Oct →
dust215–150.0129%2 Oct →
mirage14–160.0117%2 Oct →
inferno13–50.0916%2 Oct →
nuke11–13-0.0633%1 Oct →
nuke13–6-0.0122%1 Oct →
dust216–13-0.0030%1 Oct →
mirage10–13-0.0352%27 Sept →
inferno14–160.0125%26 Sept →
dust213–4-0.0113%26 Sept →
dust26–13-0.0156%26 Sept →
mirage8–13-0.0248%25 Sept →
ancient8–13-0.0419%25 Sept →
inferno16–13-0.0423%24 Sept →
nuke13–40.1127%20 Sept →
nuke13–80.0430%20 Sept →
mirage14–160.0013%19 Sept →
mirage7–13-0.0212%19 Sept →
dust211–13-0.0330%19 Sept →
nuke13–50.1134%19 Sept →
mirage13–60.0415%19 Sept →
inferno13–60.0719%19 Sept →
anubis11–13-0.0022%19 Sept →
nuke11–13-0.0338%19 Sept →
ancient13–11-0.0421%19 Sept →
anubis11–13-0.0817%18 Sept →
ancient13–30.1130%18 Sept →
cache6–13-0.039%18 Sept →
dust213–5-0.0411%18 Sept →

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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