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  Clan Information

Statistics Summary
Clan: TAMBOFF-WOLF
Home Page: tamboff-wolf.ru
Activity: 75.13%
Members: 29 active members (75 total)
Avg. Member Points: 11,665
Total Kills: 346,915
Total Deaths: 298,264
Avg. Kills: 11,963
Kills per Death: 1.16
Kills per Minute: 0.62
Total Connection Time: 388d 00:11:05h
Avg. Connection Time: 13d 09:06:35h
Favorite Server:* ~TAMBOFF-WOLF [NIGHT VIP] PUBLIC NOSTEAM~
Favorite Map:* de_dust2
Favorite Weapon:* Kalashnikov AK-47
Player Locations

  Members

Rank Name Rank Points sort-descending.gif Activity Time Kills Clan Kills % Deaths Kpd
1  Russian federation⋙-☭3,14✖@ЉI4-►㋛™ elorank 33,787 46d 21:12:43h 69,011 19.89% 31,407 2.20
2  Israel«★»GℛΣﮒℍ₦iK«★» elorank 19,346 7d 17:10:25h 10,776 3.11% 5,572 1.93
3  Russian federationdoc76 elorank 18,822 38d 01:42:25h 24,921 7.18% 24,192 1.03
4  Russian federationубивашка 62 elorank 17,763 5d 14:56:47h 6,740 1.94% 4,511 1.49
5  Russian federationSTRELOK elorank 14,649 15d 08:36:59h 11,558 3.33% 10,412 1.11
6  Russian federationDiM4iK elorank 14,639 16d 11:27:36h 19,248 5.55% 12,180 1.58
7  Russian federationOrel57RUSVOVAN elorank 13,050 5d 02:04:46h 4,277 1.23% 3,263 1.31
8  Russian federationKAZANTIP elorank 13,013 50d 00:05:11h 42,123 12.14% 38,689 1.09
9  Russian federationИлья190RUS elorank 12,673 3d 19:17:12h 3,977 1.15% 3,458 1.15
10  PolandПопугайчик Тоша elorank 12,655 2d 02:06:13h 3,109 0.90% 1,465 2.12
11  Russian federationAnapskiy elorank 11,935 19d 05:13:30h 17,550 5.06% 15,207 1.15
12  Russian federationStanislav752 elorank 10,885 15d 14:47:50h 12,949 3.73% 12,310 1.05
13  Ukrainerimuru elorank 10,538 14d 04:56:12h 13,863 4.00% 13,411 1.03
14  Germany«★»Andy«★» elorank 10,521 2d 20:55:52h 2,916 0.84% 2,272 1.28
15  Russian federationубивашка 62 elorank 10,447 22d 05:26:20h 23,507 6.78% 15,929 1.48
16  Russian federationSlovoPetuxa!-KashtanomPoOsvaltu elorank 10,147 3d 12:31:06h 3,352 0.97% 3,521 0.95
17  Russian federationBISON elorank 10,137 8d 12:53:36h 5,625 1.62% 8,468 0.66
18  Russian federationShalfeYka elorank 9,929 2d 00:54:08h 1,783 0.51% 1,789 1.00
19  Russian federationavpvovan elorank 9,833 5d 20:41:14h 4,453 1.28% 5,036 0.88
20  Russian federationLoony elorank 9,616 30d 09:51:43h 19,993 5.76% 22,172 0.90


Page: 1 2




  Player Actions *

Rank Action Achieved sort-descending.gif Points Bonus
1 Headshot 26,748 times 26,748
2 Pick up the Bomb 22,663 times 45,326
3 Round MVP 16,895 times 0
4 Drop the Bomb 12,556 times -25112
5 Double Kill (2 kills) 10,687 times 10,687
6 Plant the Bomb 4,726 times 47,260
7 Domination 3,308 times 16,540
8 Triple Kill (3 kills) 2,545 times 5,090
9 Revenge 1,656 times 4,968
10 Start Defusing the Bomb With a Defuse Kit 695 times 0
11 Defuse the Bomb 501 times 5,010
12 Domination (4 kills) 450 times 1,350
13 Start Defusing the Bomb Without a Defuse Kit 65 times 0
14 Rampage (5 kills) 48 times 192
15 Kill a Hostage 18 times -270
16 Touch a Hostage 4 times 0
17 Mega Kill (6 kills) 4 times 20
18 Rescue a Hostage 1 times 5




  Victims of Player-Player Actions *

Rank Action Times Victimized Points Bonus sort-descending.gif
1 Revenge 1,941 times -5823
2 Domination 2,661 times -13305




  Team Selection *

Rank Team Joined sort-ascending.gif Percentage of Times %
1 Counter-Terrorist 2,406 times 21.51%
2 Terrorist 3,128 times 27.96%




  Weapon Usage *

Rank Weapon Points Modifier Kills sort-ascending.gif Percentage of Kills % Headshots Percentage of Headshots % Hpk
1 H&K G3/SG1 Sniper Rifle 0.80 1 0.00% 0 0.00% 0.00
2 H&K UMP45 1.20 34 0.01% 16 0.01% 0.47
3 Fusil Automatique 1.00 48 0.01% 23 0.02% 0.48
4 FN Five-Seven 1.50 59 0.02% 28 0.02% 0.47
5 Steyr Tactical Machine Pistol 1.50 59 0.02% 30 0.02% 0.51
6 Benelli/H&K M4 Super 90 XM1014 1.10 75 0.02% 28 0.02% 0.37
7 Steyr Aug 1.00 80 0.02% 39 0.03% 0.49
8 Glock 18 Select Fire 1.40 105 0.03% 51 0.04% 0.49
9 H&K MP5-Navy 1.20 105 0.03% 46 0.04% 0.44
10 Ingram MAC-10 1.50 119 0.03% 59 0.04% 0.50
11 Galil 1.10 120 0.03% 50 0.04% 0.42
12 H&K USP .45 Tactical 1.40 134 0.04% 67 0.05% 0.50
13 Dual Beretta 96G Elite 1.40 224 0.06% 102 0.08% 0.46
14 Benelli M3 Super 90 Combat 1.20 638 0.18% 268 0.20% 0.42
15 Sig Sauer SG-552 Commando 1.00 965 0.28% 428 0.33% 0.44
16 Sig Sauer P-228 1.50 1,250 0.36% 529 0.40% 0.42
17 FN P90 1.20 1,554 0.45% 689 0.52% 0.44
18 Bundeswehr Advanced Combat Knife 2.00 1,653 0.48% 2 0.00% 0.00
19 M249 PARA Light Machine Gun 1.20 2,176 0.63% 1,062 0.81% 0.49
20 Arctic Warfare Magnum (Police) 1.00 2,400 0.69% 397 0.30% 0.17
21 High Explosive Grenade 1.80 2,493 0.72% 0 0.00% 0.00
22 Steyr Scout 1.10 5,905 1.70% 3,710 2.82% 0.63
23 Desert Eagle .50AE 1.20 6,456 1.86% 3,603 2.74% 0.56
24 Colt M4A1 Carbine 1.00 11,680 3.37% 5,272 4.01% 0.45
25 Kalashnikov AK-47 1.00 19,161 5.52% 9,714 7.39% 0.51




  Weapon Stats *

Rank Weapon Shots sort-ascending.gif Hits Damage Headshots Kills Kills per Death Accuracy Damage per Hit Shots per Kill
1 Sig SG-550 Sniper 6 3 301 1 2 2.0000 50.0% 100.3 3.0
2 H&K G3/SG1 Sniper Rifle 30 10 1,742 6 7 7.0000 33.3% 174.2 4.3
3 Fusil Automatique 1,191 214 6,712 22 46 46.0000 18.0% 31.4 25.9
4 Benelli/H&K M4 Super 90 XM1014 1,346 924 10,916 28 75 15.0000 68.6% 11.8 17.9
5 FN Five-Seven 1,360 334 8,810 29 60 30.0000 24.6% 26.4 22.7
6 H&K UMP45 2,080 269 5,346 16 33 16.5000 12.9% 19.9 63.0
7 Benelli M3 Super 90 Combat 2,875 5,800 83,874 268 638 2.1267 201.7% 14.5 4.5
8 Steyr Aug 3,010 428 12,647 40 81 11.5714 14.2% 29.5 37.2
9 Galil 3,410 500 16,691 50 120 60.0000 14.7% 33.4 28.4
10 Steyr Tactical Machine Pistol 4,010 502 8,977 29 58 58.0000 12.5% 17.9 69.1
11 H&K MP5-Navy 4,960 905 15,133 45 103 11.4444 18.2% 16.7 48.2
12 Ingram MAC-10 5,038 844 15,369 58 116 29.0000 16.8% 18.2 43.4
13 H&K USP .45 Tactical 5,130 930 19,158 66 133 10.2308 18.1% 20.6 38.6
14 Glock 18 Select Fire 5,194 901 15,897 50 103 6.8667 17.3% 17.6 50.4
15 Dual Beretta 96G Elite 5,633 1,119 30,927 102 224 74.6667 19.9% 27.6 25.1
16 Arctic Warfare Magnum (Police) 10,029 3,468 466,604 404 2,408 5.0695 34.6% 134.5 4.2
17 Bundeswehr Advanced Combat Knife 12,054 1,158 60,557 2 403 1.7446 9.6% 52.3 29.9
18 Sig Sauer P-228 33,771 5,229 160,866 529 1,250 23.1481 15.5% 30.8 27.0
19 Steyr Scout 47,373 14,232 1,359,572 3,703 5,899 2.3921 30.0% 95.5 8.0
20 Desert Eagle .50AE 70,262 18,132 944,032 3,637 6,496 4.3597 25.8% 52.1 10.8
21 Sig Sauer SG-552 Commando 74,133 4,978 143,947 441 981 37.7308 6.7% 28.9 75.6
22 FN P90 76,882 8,789 205,959 689 1,554 10.1569 11.4% 23.4 49.5
23 M249 PARA Light Machine Gun 113,208 8,393 315,999 1,114 2,234 13.2189 7.4% 37.7 50.7
24 Colt M4A1 Carbine 413,764 51,643 1,639,485 5,269 11,677 10.9438 12.5% 31.7 35.4
25 Kalashnikov AK-47 583,274 69,495 2,748,632 10,142 19,690 9.3406 11.9% 39.6 29.6




  Weapon Targets *

Rank Weapon Hits sort-ascending.gif Left Middle Right
1 Sig SG-550 Sniper 3 0.0% 100.0% 0.0%
2 H&K G3/SG1 Sniper Rifle 10 20.0% 80.0% 0.0%
3 Bundeswehr Advanced Combat Knife 53 24.5% 67.9% 7.5%
4 Fusil Automatique 214 22.0% 63.6% 14.5%
5 H&K UMP45 269 26.4% 53.5% 20.1%
6 FN Five-Seven 334 23.7% 62.0% 14.4%
7 Steyr Aug 428 27.8% 57.2% 15.0%
8 Galil 500 28.8% 55.6% 15.6%
9 Steyr Tactical Machine Pistol 502 25.7% 63.1% 11.2%
10 Ingram MAC-10 844 26.4% 58.4% 15.2%
11 Glock 18 Select Fire 901 26.5% 62.2% 11.3%
12 H&K MP5-Navy 905 28.4% 56.8% 14.8%
13 Benelli/H&K M4 Super 90 XM1014 924 26.6% 56.9% 16.5%
14 H&K USP .45 Tactical 930 25.1% 62.7% 12.3%
15 Dual Beretta 96G Elite 1,119 24.9% 61.6% 13.5%
16 Arctic Warfare Magnum (Police) 3,468 32.6% 57.6% 9.8%
17 Sig Sauer SG-552 Commando 4,978 28.7% 56.0% 15.3%
18 Sig Sauer P-228 5,229 28.6% 57.7% 13.7%
19 Benelli M3 Super 90 Combat 5,800 29.7% 57.3% 13.0%
20 M249 PARA Light Machine Gun 8,393 28.3% 57.3% 14.5%
21 FN P90 8,789 28.0% 56.4% 15.6%
22 Steyr Scout 14,207 26.4% 64.9% 8.7%
23 Desert Eagle .50AE 18,132 26.1% 61.7% 12.2%
24 Colt M4A1 Carbine 51,643 27.8% 59.2% 13.0%
25 Kalashnikov AK-47 69,495 27.1% 59.1% 13.8%


Targets
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ERROR
Database Error

Server Address: localhost
Server Username: hlstatsxce

Error Diagnostic:
Bad query.

Server Error: (1052) Column 'map' in order clause is ambiguous

Last SQL Query:
		SELECT *, 
			IFNULL(kills/deaths, '-') AS kpd,
			IFNULL(headshots / kills, '-') AS hpk,
			ROUND(kills / 346915 * 100, 2) AS kpercent,
			ROUND(headshots / 131390 * 100, 2) AS hpercent
		FROM
			tmp_clan_kills, tmp_clan_deaths
		WHERE
			tmp_clan_kills.map = tmp_clan_deaths.map
		ORDER BY
			map desc,
			kills desc