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  Clan Information

Statistics Summary
Clan: TAMBOFF-WOLF
Home Page: tamboff-wolf.ru
Activity: 72.31%
Members: 29 active members (75 total)
Avg. Member Points: 11,717
Total Kills: 349,040
Total Deaths: 300,504
Avg. Kills: 12,036
Kills per Death: 1.16
Kills per Minute: 0.62
Total Connection Time: 390d 12:46:06h
Avg. Connection Time: 13d 11:11:56h
Favorite Server:* ~TAMBOFF-WOLF [NIGHT VIP] PUBLIC NOSTEAM~
Favorite Map:* de_dust2
Favorite Weapon:* Kalashnikov AK-47
Player Locations

  Members

Rank Name Rank Points Activity Time Kills Clan Kills % Deaths sort-descending.gif Kpd
1  Russian federationKAZANTIP elorank 13,115 50d 00:51:06h 42,157 12.08% 38,713 1.09
2  Russian federation⋙-☭3,14✖@ЉI4-►㋛™ elorank 33,434 46d 23:24:56h 69,135 19.81% 31,473 2.20
3  Russian federationdoc76 elorank 18,822 38d 01:47:03h 24,921 7.14% 24,192 1.03
4  Russian federationLoony elorank 9,640 30d 13:29:04h 20,090 5.76% 22,285 0.90
5  KazakhstanRastaman 10KZ elorank 9,158 22d 06:38:27h 16,151 4.63% 18,072 0.89
6  Russian federationубивашка 62 elorank 10,447 22d 05:26:20h 23,507 6.73% 15,929 1.48
7  Russian federationAnapskiy elorank 11,935 19d 05:13:30h 17,550 5.03% 15,207 1.15
8  Russian federation-=ΞDDDEMOΞ=- [77RUS] elorank 4,186 16d 07:37:33h 9,248 2.65% 14,654 0.63
9  Ukrainerimuru elorank 10,538 14d 04:56:12h 13,863 3.97% 13,411 1.03
10  Russian federationStanislav752 elorank 10,609 16d 07:31:00h 13,288 3.81% 12,958 1.03
11  Russian federationDiM4iK elorank 14,639 16d 11:27:36h 19,248 5.51% 12,180 1.58
12  Kazakhstan₭Ø฿Ɽ₳ 10₭Ⱬ elorank 5,483 13d 19:17:20h 4,999 1.43% 11,872 0.42
13  Russian federationSTRELOK elorank 14,649 15d 08:36:59h 11,558 3.31% 10,412 1.11
14  Russian federationBISON elorank 10,794 8d 22:58:50h 5,926 1.70% 8,847 0.67
15  Russian federationKenzO elorank 5,731 8d 18:32:44h 5,913 1.69% 7,910 0.75
16  Russian federation⇜Ṧ†êrvå⇝ elorank 9,398 6d 14:27:56h 4,767 1.37% 6,243 0.76
17  Israel«★»GℛΣﮒℍ₦iK«★» elorank 19,346 7d 17:10:25h 10,776 3.09% 5,572 1.93
18  Russian federationavpvovan elorank 9,968 5d 21:09:37h 4,479 1.28% 5,052 0.89
19  Russian federationубивашка 62 elorank 17,438 6d 03:37:34h 7,362 2.11% 4,973 1.48
20  Russian federationSlovoPetuxa!-Zerno na osvalte=) elorank 10,435 3d 15:33:00h 3,499 1.00% 3,659 0.96


Page: 1 2




  Player Actions *

Rank Action Achieved Points Bonus sort-ascending.gif
1 Drop the Bomb 12,382 times -24764
2 Kill a Hostage 18 times -270
3 Round MVP 16,405 times 0
4 Start Defusing the Bomb With a Defuse Kit 650 times 0
5 Start Defusing the Bomb Without a Defuse Kit 61 times 0
6 Touch a Hostage 4 times 0
7 Rescue a Hostage 1 times 5
8 Mega Kill (6 kills) 4 times 20
9 Rampage (5 kills) 44 times 176
10 Domination (4 kills) 426 times 1,278
11 Defuse the Bomb 480 times 4,800
12 Revenge 1,641 times 4,923
13 Triple Kill (3 kills) 2,486 times 4,972
14 Double Kill (2 kills) 10,455 times 10,455
15 Domination 3,198 times 15,990
16 Headshot 25,647 times 25,647
17 Pick up the Bomb 22,136 times 44,272
18 Plant the Bomb 4,459 times 44,590




  Victims of Player-Player Actions *

Rank Action Times Victimized sort-descending.gif Points Bonus
1 Domination 2,630 times -13150
2 Revenge 1,872 times -5616




  Team Selection *

Rank Team Joined sort-descending.gif Percentage of Times %
1 Terrorist 3,031 times 27.96%
2 Counter-Terrorist 2,348 times 21.66%




  Weapon Usage *

Rank Weapon Points Modifier Kills sort-descending.gif Percentage of Kills % Headshots Percentage of Headshots % Hpk
1 Kalashnikov AK-47 1.00 18,151 5.20% 9,247 6.98% 0.51
2 Colt M4A1 Carbine 1.00 11,429 3.27% 5,204 3.93% 0.46
3 Desert Eagle .50AE 1.20 6,428 1.84% 3,586 2.71% 0.56
4 Steyr Scout 1.10 5,900 1.69% 3,709 2.80% 0.63
5 High Explosive Grenade 1.80 2,451 0.70% 0 0.00% 0.00
6 Arctic Warfare Magnum (Police) 1.00 2,332 0.67% 386 0.29% 0.17
7 M249 PARA Light Machine Gun 1.20 2,214 0.63% 1,062 0.80% 0.48
8 FN P90 1.20 1,616 0.46% 725 0.55% 0.45
9 Bundeswehr Advanced Combat Knife 2.00 1,615 0.46% 2 0.00% 0.00
10 Sig Sauer P-228 1.50 1,273 0.36% 541 0.41% 0.42
11 Sig Sauer SG-552 Commando 1.00 962 0.28% 428 0.32% 0.44
12 Benelli M3 Super 90 Combat 1.20 607 0.17% 264 0.20% 0.43
13 Dual Beretta 96G Elite 1.40 221 0.06% 102 0.08% 0.46
14 H&K USP .45 Tactical 1.40 131 0.04% 69 0.05% 0.53
15 Galil 1.10 117 0.03% 47 0.04% 0.40
16 H&K MP5-Navy 1.20 106 0.03% 46 0.03% 0.43
17 Ingram MAC-10 1.50 99 0.03% 45 0.03% 0.45
18 Glock 18 Select Fire 1.40 98 0.03% 45 0.03% 0.46
19 Steyr Aug 1.00 71 0.02% 35 0.03% 0.49
20 Benelli/H&K M4 Super 90 XM1014 1.10 66 0.02% 24 0.02% 0.36
21 FN Five-Seven 1.50 63 0.02% 32 0.02% 0.51
22 Steyr Tactical Machine Pistol 1.50 55 0.02% 27 0.02% 0.49
23 Fusil Automatique 1.00 44 0.01% 20 0.02% 0.45
24 H&K UMP45 1.20 34 0.01% 16 0.01% 0.47
25 H&K G3/SG1 Sniper Rifle 0.80 1 0.00% 0 0.00% 0.00




  Weapon Stats *

Rank Weapon Shots Hits Damage Headshots Kills sort-descending.gif Kills per Death Accuracy Damage per Hit Shots per Kill
1 Kalashnikov AK-47 571,642 65,049 2,546,035 9,239 18,140 8.9846 11.4% 39.1 31.5
2 Colt M4A1 Carbine 393,776 50,414 1,604,944 5,201 11,426 11.2794 12.8% 31.8 34.5
3 Desert Eagle .50AE 70,021 17,958 930,573 3,583 6,424 4.2515 25.6% 51.8 10.9
4 Steyr Scout 47,585 14,244 1,355,654 3,702 5,894 2.3718 29.9% 95.2 8.1
5 Arctic Warfare Magnum (Police) 9,708 3,363 450,007 386 2,331 4.9914 34.6% 133.8 4.2
6 M249 PARA Light Machine Gun 116,112 8,463 313,097 1,063 2,215 12.3743 7.3% 37.0 52.4
7 FN P90 79,157 9,128 214,549 725 1,616 10.4258 11.5% 23.5 49.0
8 Sig Sauer P-228 34,223 5,406 165,773 541 1,273 22.7321 15.8% 30.7 26.9
9 Sig Sauer SG-552 Commando 73,907 4,940 141,619 428 963 40.1250 6.7% 28.7 76.7
10 Benelli M3 Super 90 Combat 2,807 5,617 81,222 264 607 2.0166 200.1% 14.5 4.6
11 Bundeswehr Advanced Combat Knife 11,698 1,117 57,991 2 385 1.6739 9.5% 51.9 30.4
12 Dual Beretta 96G Elite 5,596 1,099 30,532 102 221 73.6667 19.6% 27.8 25.3
13 H&K USP .45 Tactical 5,114 920 18,918 68 130 10.0000 18.0% 20.6 39.3
14 Galil 3,354 489 16,087 47 117 58.5000 14.6% 32.9 28.7
15 H&K MP5-Navy 5,041 915 15,355 45 104 10.4000 18.2% 16.8 48.5
16 Ingram MAC-10 3,499 654 12,215 44 96 48.0000 18.7% 18.7 36.4
17 Glock 18 Select Fire 5,110 871 14,861 44 96 6.4000 17.0% 17.1 53.2
18 Steyr Aug 2,820 390 11,516 36 72 10.2857 13.8% 29.5 39.2
19 Benelli/H&K M4 Super 90 XM1014 1,248 807 9,511 24 66 13.2000 64.7% 11.8 18.9
20 FN Five-Seven 1,406 344 9,281 33 64 32.0000 24.5% 27.0 22.0
21 Steyr Tactical Machine Pistol 3,274 447 7,866 26 54 54.0000 13.7% 17.6 60.6
22 Fusil Automatique 1,188 194 6,207 19 42 42.0000 16.3% 32.0 28.3
23 H&K UMP45 2,080 269 5,346 16 33 16.5000 12.9% 19.9 63.0
24 Sig SG-550 Sniper 6 3 301 1 2 2.0000 50.0% 100.3 3.0
25 H&K G3/SG1 Sniper Rifle 13 2 137 0 1 1.0000 15.4% 68.5 13.0




  Weapon Targets *

Rank Weapon Hits Left Middle sort-descending.gif Right
1 Sig SG-550 Sniper 3 0.0% 100.0% 0.0%
2 Bundeswehr Advanced Combat Knife 51 23.5% 66.7% 9.8%
3 Steyr Scout 14,219 26.5% 64.8% 8.7%
4 Steyr Tactical Machine Pistol 447 25.1% 63.8% 11.2%
5 Fusil Automatique 194 23.2% 62.9% 13.9%
6 FN Five-Seven 344 23.3% 62.5% 14.2%
7 Glock 18 Select Fire 871 26.6% 62.0% 11.4%
8 H&K USP .45 Tactical 920 25.0% 61.8% 13.2%
9 Desert Eagle .50AE 17,958 26.3% 61.5% 12.2%
10 Dual Beretta 96G Elite 1,099 25.1% 61.2% 13.6%
11 Colt M4A1 Carbine 50,414 27.8% 59.2% 13.1%
12 Ingram MAC-10 654 26.8% 58.9% 14.4%
13 Kalashnikov AK-47 65,049 27.3% 58.7% 13.9%
14 Sig Sauer P-228 5,406 28.8% 57.6% 13.6%
15 Benelli M3 Super 90 Combat 5,617 29.7% 57.5% 12.7%
16 Arctic Warfare Magnum (Police) 3,363 32.6% 57.5% 9.9%
17 H&K MP5-Navy 915 28.3% 57.0% 14.6%
18 M249 PARA Light Machine Gun 8,463 28.6% 56.6% 14.8%
19 FN P90 9,128 27.9% 56.5% 15.7%
20 Steyr Aug 390 27.9% 56.4% 15.6%
21 Benelli/H&K M4 Super 90 XM1014 807 27.3% 56.0% 16.7%
22 Sig Sauer SG-552 Commando 4,940 29.0% 55.6% 15.3%
23 Galil 489 28.8% 55.6% 15.5%
24 H&K UMP45 269 26.4% 53.5% 20.1%
25 H&K G3/SG1 Sniper Rifle 2 100.0% 0.0% 0.0%


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 / 349040 * 100, 2) AS kpercent,
			ROUND(headshots / 132406 * 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