Comets

GP: 82 | W: 40 | L: 38 | OTL: 4 | P: 84
GF: 335 | GA: 351 | PP%: 24.29% | PK%: 74.22%
DG: Samuel Gendron-Mallet | Morale : 50 | Moyenne d'Équipe : 45
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Erik CondraXX100.00484382715958465035445766475547050550
2Reid BoucherXX100.00503593686562475639506252454640050550
3Iiro PakarinenXX100.00633590697355444735425272484137050550
4Dan O'Regan (R)X100.00463592715759424875524461453532050530
5Laurent DauphinXX100.00533581665655364648415060484036050510
6Zach SanfordXXX100.00483587717148384745435156443532050510
7Jason Dickinson (R)XX100.00554382647154394448434456484036050500
8Eric Robinson (R)X100.00453595606953353535353554483532050460
9Givani Smith (R)XX100.00454545457345454545454545453230050460
10Chris Calnan (R)X100.00394343436137373943393943413230050420
11Maxim Letunov (R)X100.00414545454439394145414145433230050420
12Daniel Zaar (R)X100.00333737374833333337333337353230050370
13Justin Holl (R)X100.00523595656855353535303966483532050520
14Ashton Sautner (R)X100.00543585636350353435353267483532050510
15Kyle CapobiancoX100.00513595636455353135303262483532050500
16Mitch Reinke (R)X100.00433595605550353135303252483532050460
17Ben Thomas (R)X100.00364040406135353640363640383230050400
18Daniel Walcott (R)X100.00333737374533333337333337353230050370
Rayé
1Kris VersteegXX100.00474384685370576663646756587065050620
2Stefan MatteauX100.00533595627649353750383555484238050480
3Christoph Bertschy (R)XXX100.00523555685749353735383556483936050470
4Brendan WoodsX100.00504366637445313235323263463532050460
5Sebastian Wannstrom (R)XXX100.00414545455639394145414145433230050430
6Ben Johnson (R)XX100.00394343435937373943393943413230050420
7Ben HanowskiXX100.00308436487329433135313146453734050400
8Artur Gavrus (R)XX100.00333737375133333337333337353230050370
9Cole Ully (R)XX100.00333737374633333337333337353230050370
10Gustav Possler (R)XX100.00333737375733333337333337353230050370
11Viktor LoovX100.00483593616941313135313071463532050510
12Dillon Fournier (R)X100.00414545455239394145414145433230050430
13Jack Glover (R)X100.00394343436237373943393943413230050420
14Dylan Labbe (R)X100.00364040405635353640363640383230050400
15Stephen Silas (R)X100.00364040405735353640363640383230050400
16Dmitry Sinitsyn (R)X100.00333737376633333337333337353230050390
MOYENNE D'ÉQUIPE100.0044406353614538394138405143363305046
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Ondrej Pavelec100.0044457980434646414686876053050540
2Kaapo Kahkonen (R)100.0038403878373636363636353230050410
Rayé
1Zachary Fucale (R)100.0043454366424141414141403230050430
2Matej Tomek (R)100.0042434266424141414141403230050430
3Brendan Burke (R)100.0035373564343333333333333230050370
MOYENNE D'ÉQUIPE100.004042477140393938394747383505044
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOS GP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Reid BoucherComets (Van)LW/RW82626212417180671123639321917.08%18167020.3821244596273112102587551.06%14100051.48350001198
2Laurent DauphinComets (Van)C/LW82396810720395772072537318115.42%22131716.0782533471960003874152.99%120400111.6203100766
3Iiro PakarinenComets (Van)LW/RW774452961148013917029610925314.86%39151419.671117288224600081893042.57%44400011.2714000557
4Erik CondraComets (Van)LW/RW8030538312220491422878721010.45%31124515.57512173812101181825144.14%22200021.3312000543
5Zach SanfordComets (Van)C/LW/RW71423577-160281252247214018.75%20123117.34121022452110006915150.93%129600021.25120002105
6Dan O'ReganComets (Van)C5217526966035123132249612.88%1699319.1081220331660002873261.96%112500001.3912000573
7Jason DickinsonComets (Van)C/LW7926335956715751131945313813.40%17113414.36123231220000473453.60%34700011.0411003412
8Justin HollComets (Van)D82123749-123807869109367811.01%125182222.2361218562510112215310.00%000000.5400000122
9Kyle CapobiancoComets (Van)D59112637-19480784266265316.67%91127121.557512351810003160110.00%000000.5800000131
10Brock NelsonVancouverC/LW13131730172094078235816.67%629923.0154925530001453165.51%43200012.0123000432
11Eric RobinsonComets (Van)LW60101828-1755127590248811.11%1873212.210112180001552238.81%6700000.7600100111
12Tyler PitlickVancouverLW/RW121213251380151863234319.05%725421.2554918490002403041.35%10400011.9601000214
13Mitch ReinkeComets (Van)D827182510200423853113213.21%102167420.42369182240110207000.00%000000.3000000111
14Ashton SautnerComets (Van)D5232124-738084505618345.36%78112621.6611112241490001115000.00%000000.4300000001
15Givani SmithComets (Van)LW/RW797162315010131228430718.33%15126416.01066112000000170044.94%8900000.3601002110
16Maxim LetunovComets (Van)C8281321-323810671158122639.88%1086810.59000380001420043.64%82500000.4800001000
17Chris CalnanComets (Van)RW8281018-2440723758184713.79%695211.620117300000360052.24%6700000.3800000001
18Christoph BertschyComets (Van)C/LW/RW3041418-630056345915386.78%647415.81123892000001128.00%2500000.7600000100
19Jack GloverComets (Van)D8041317-116801362524132016.67%70136617.080224107000097100.00%000000.2500000100
20Daniel WalcottComets (Van)D82189-1379510115193105.26%54132216.13000063000092000.00%000000.1400010000
21Stefan MatteauComets (Van)LW213690606304611336.52%627212.980111140002280058.62%2900000.6600000000
22Artur GavrusComets (Van)C/LW46246-234031251851311.11%54249.2200015000010039.22%25500000.2800000000
23Ben ThomasComets (Van)D2504432204958110.00%1941116.47000028000018000.00%000000.1900000000
24Cole UllyComets (Van)LW/RW32112-2080131216166.25%23089.6500005000000023.81%2100000.1300000000
25Daniel ZaarComets (Van)RW82022-42140487378220.00%47178.75000011000030037.50%4000000.0600000000
Stats d'équipe Total ou en Moyenne1524366596962-9072850149816512714799194713.49%7872467316.19941572515772834145502125442051.55%6733001140.781024216525447
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Kaapo KahkonenComets (Van)67263230.8634.5635270026819610510.733156517101
2Ondrej PavelecComets (Van)1713310.8963.2396700525020000.6673170000
Stats d'équipe Total ou en Moyenne84393540.8704.2744950032024630510.722188217101


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Artur GavrusComets (Van)C/LW231994-01-03Yes175 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Ashton SautnerComets (Van)D231994-05-27Yes195 Lbs6 ft1YesNoNo6Avec RestrictionPro & Farm1,000,000$100,000$0$NoLien
Ben HanowskiComets (Van)LW/RW261990-10-18No210 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm1,000,000$100,000$0$NoLien
Ben JohnsonComets (Van)C/LW231994-06-07Yes188 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm625,000$62,500$0$NoLien
Ben ThomasComets (Van)D211996-05-28Yes190 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Brendan BurkeComets (Van)G211996-05-11Yes176 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Brendan WoodsComets (Van)LW251992-06-11No210 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm900,000$90,000$0$NoLien
Chris CalnanComets (Van)RW231994-05-05Yes187 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Christoph BertschyComets (Van)C/LW/RW231994-04-05Yes185 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm693,000$69,300$0$NoLien
Cole UllyComets (Van)LW/RW221995-02-20Yes164 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm620,000$62,000$0$NoLien
Dan O'ReganComets (Van)C231994-01-30Yes185 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Daniel WalcottComets (Van)D231994-02-19Yes161 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Daniel ZaarComets (Van)RW231994-04-24Yes167 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Dillon FournierComets (Van)D231994-06-15Yes173 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm718,000$71,800$0$NoLien
Dmitry SinitsynComets (Van)D231994-06-17Yes200 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Dylan LabbeComets (Van)D221995-01-09Yes180 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm667,000$66,700$0$NoLien
Eric RobinsonComets (Van)LW221995-06-14Yes200 Lbs6 ft2YesNoNo6Avec RestrictionPro & Farm1,000,000$100,000$0$NoLien
Erik CondraComets (Van)LW/RW311986-08-06No188 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm1,900,000$190,000$0$NoLien
Givani SmithComets (Van)LW/RW191998-02-27Yes209 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm742,500$74,250$0$NoLien
Gustav PosslerComets (Van)LW/RW221994-11-11Yes183 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Iiro PakarinenComets (Van)LW/RW261991-08-25No212 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm792,000$79,200$0$NoLien
Jack GloverComets (Van)D211996-05-17Yes190 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Jason DickinsonComets (Van)C/LW221995-07-04Yes205 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Justin HollComets (Van)D251992-01-30Yes205 Lbs6 ft3YesNoNo6Avec RestrictionPro & Farm1,400,000$140,000$0$NoLien
Kaapo KahkonenComets (Van)G211996-08-16Yes209 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Kris VersteegComets (Van)LW/RW311986-05-13No176 Lbs5 ft11NoNoNo4Sans RestrictionPro & Farm3,100,000$3,100,000$0$NoLien
Kyle CapobiancoComets (Van)D201997-08-13No196 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Laurent DauphinComets (Van)C/LW221995-03-27No180 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm718,000$71,800$0$NoLien
Matej TomekComets (Van)G201997-05-24Yes180 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Maxim LetunovComets (Van)C211996-02-20Yes155 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm825,000$82,500$0$NoLien
Mitch ReinkeComets (Van)D211996-02-04Yes181 Lbs5 ft11YesNoNo6Contrat d'EntréePro & Farm1,200,000$120,000$0$NoLien
Ondrej PavelecComets (Van)G301987-08-31No212 Lbs6 ft3NoNoNo3Sans RestrictionPro & Farm2,800,000$280,000$0$NoLien
Reid BoucherComets (Van)LW/RW241993-09-08No195 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm800,000$80,000$0$NoLien
Sebastian WannstromComets (Van)C/LW/RW261991-03-03Yes180 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm825,000$82,500$0$NoLien
Stefan MatteauComets (Van)LW231994-02-23No220 Lbs6 ft2NoNoNo5Avec RestrictionPro & Farm600,000$60,000$0$NoLien
Stephen SilasComets (Van)D251992-06-26Yes183 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Viktor LoovComets (Van)D241992-11-16No212 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm693,000$69,300$0$NoLien
Zach SanfordComets (Van)C/LW/RW221994-11-09No203 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Zachary FucaleComets (Van)G221995-03-28Yes181 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm743,000$74,300$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3923.26190 Lbs6 ft12.69885,551$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Iiro PakarinenDan O'ReganErik Condra40122
2Reid BoucherZach SanfordGivani Smith30122
3Jason DickinsonLaurent DauphinChris Calnan20122
4Eric RobinsonMaxim LetunovDaniel Zaar10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Justin HollAshton Sautner40122
2Kyle CapobiancoMitch Reinke30122
3Ben ThomasDaniel Walcott20122
4Justin HollAshton Sautner10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Iiro PakarinenDan O'ReganErik Condra60122
2Reid BoucherZach SanfordGivani Smith40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Justin HollAshton Sautner60122
2Kyle CapobiancoMitch Reinke40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Iiro PakarinenErik Condra60122
2Reid BoucherDan O'Regan40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Justin HollAshton Sautner60122
2Kyle CapobiancoMitch Reinke40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Iiro Pakarinen60122Justin HollAshton Sautner60122
2Erik Condra40122Kyle CapobiancoMitch Reinke40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Iiro PakarinenErik Condra60122
2Reid BoucherDan O'Regan40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Justin HollAshton Sautner60122
2Kyle CapobiancoMitch Reinke40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Iiro PakarinenDan O'ReganErik CondraJustin HollAshton Sautner
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Iiro PakarinenDan O'ReganErik CondraJustin HollAshton Sautner
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Laurent Dauphin, Jason Dickinson, Eric RobinsonLaurent Dauphin, Jason DickinsonEric Robinson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ben Thomas, Daniel Walcott, Kyle CapobiancoBen ThomasDaniel Walcott, Kyle Capobianco
Tirs de Pénalité
Iiro Pakarinen, Erik Condra, Reid Boucher, Dan O'Regan, Zach Sanford
Gardien
#1 : Ondrej Pavelec, #2 : Kaapo Kahkonen


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Admirals4110110015150210001006602010100099050.6251527420013310986111228517798084713840188119842.11%9277.78%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
2Baby Hawks32000100141311000010056-12200000097250.833142236001331098611978517798084710431264813323.08%13469.23%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
3Bears2110000079-21010000025-31100000054120.500714210013310986115185177980847772516347114.29%8362.50%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
4Bruins22000000844110000005321100000031241.0008142200133109861163851779808474713103711327.27%50100.00%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
5Cabaret Lady Mary Ann2110000010100110000006421010000046-220.5001017270013310986117885177980847732428528337.50%12375.00%11229239351.36%1174235849.79%759149850.67%1838122720206411096532
6Caroline220000001468110000006241100000084441.00014253900133109861183851779808476219182517423.53%9366.67%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
7Chiefs30200010713-61010000027-52010001056-120.33371017001331098611678517798084784312452800.00%12283.33%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
8Chill311001001013-31000010045-12110000068-230.50010152500133109861165851779808478328205812325.00%10190.00%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
9Cougars21100000913-4110000007521010000028-620.5009182700133109861157851779808471033229277114.29%11463.64%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
10Crunch211000009901010000046-21100000053220.500917260013310986114685177980847601619448225.00%80100.00%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
11Heat5120101027261311010001815320100010911-260.60027437000133109861117785177980847149406010032825.00%17758.82%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
12Jayhawks404000001020-1020200000510-520200000510-500.0001017270013310986117885177980847152445585700.00%24866.67%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
13Las Vegas4300001016124220000009722100001075281.0001627430013310986111298517798084710526266221733.33%12191.67%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
14Manchots22000000963110000005321100000043141.00091423001331098611398517798084734325458225.00%9188.89%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
15Marlies201000101011-1100000105411010000057-220.50010172700133109861168851779808479016183511436.36%9277.78%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
16Minnesota31200000151502110000012931010000036-320.333152742001331098611108851779808477828325316637.50%16662.50%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
17Monarchs413000002019121100000149520200000610-420.2502035550013310986111608517798084717044386616212.50%18666.67%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
18Monsters20200000411-71010000017-61010000034-100.000471100133109861140851779808478437183713323.08%9366.67%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
19Monsters31200000815-71010000018-72110000077020.333816240013310986117885177980847913228459222.22%14564.29%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
20Oceanics31200000810-2211000006601010000024-220.33381422001331098611608517798084712139165310330.00%8187.50%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
21Oil Kings43100000211382110000088022000000135860.7502131520013310986111268517798084710726267215320.00%11463.64%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
22Phantoms2020000048-41010000023-11010000025-300.00045900133109861152851779808475419203310110.00%10190.00%11229239351.36%1174235849.79%759149850.67%1838122720206411096532
23Rocket20200000711-41010000025-31010000056-100.0007132010133109861152851779808475315183610330.00%8275.00%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
24Senators22000000752110000003211100000043141.00071017001331098611578517798084752118257114.29%4175.00%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
25Sharks413000001920-121100000119220200000811-320.2501931500013310986111578517798084721151349614428.57%17476.47%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
26Sound Tigers21000001871110000005321000000134-130.750812200013310986114785177980847612216325120.00%8275.00%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
27Spiders20101000880100010005411010000034-120.50081422001331098611578517798084774181440300.00%6266.67%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
28Stars321000001495211000009721100000052340.6671423370013310986119985177980847701823501218.33%9188.89%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
29Thunder20200000310-71010000038-51010000002-200.0003470013310986115185177980847761516328112.50%8187.50%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
Total82333803341335351-1641181702310178180-241152101031157171-14840.512335563898101331098611246685177980847273778672015073508524.29%3228374.22%21229239351.36%1174235849.79%759149850.67%1838122720206411096532
31Wolf Pack2200000014104110000007431100000076141.000142438001331098611102851779808477423215213538.46%8362.50%01229239351.36%1174235849.79%759149850.67%1838122720206411096532
_Since Last GM Reset82333803341335351-1641181702310178180-241152101031157171-14840.512335563898101331098611246685177980847273778672015073508524.29%3228374.22%21229239351.36%1174235849.79%759149850.67%1838122720206411096532
_Vs Conference42181901130181185-421910011009499-521990003087861450.53618130648710133109861112758517798084712913824127511834323.50%1765071.59%11229239351.36%1174235849.79%759149850.67%1838122720206411096532
_Vs Division2146000007688-121014000003948-91132000003740-380.1907612720300133109861157485177980847631207169359801822.50%822075.61%01229239351.36%1174235849.79%759149850.67%1838122720206411096532

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8284L233556389824662737786720150710
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8233383341335351
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4118172310178180
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4115211031157171
Derniers 10 Matchs
WLOTWOTL SOWSOL
630100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3508524.29%3228374.22%2
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
851779808471331098611
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
1229239351.36%1174235849.79%759149850.67%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1838122720206411096532


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2018-10-033Heat4Comets5WXSommaire du Match
4 - 2018-10-0628Comets4Heat7LSommaire du Match
7 - 2018-10-0937Comets8Caroline4WSommaire du Match
9 - 2018-10-1153Comets0Thunder2LSommaire du Match
11 - 2018-10-1364Comets4Cabaret Lady Mary Ann6LSommaire du Match
14 - 2018-10-1681Comets4Manchots3WSommaire du Match
16 - 2018-10-1894Comets2Oceanics4LSommaire du Match
18 - 2018-10-20111Bruins3Comets5WSommaire du Match
20 - 2018-10-22121Bears5Comets2LSommaire du Match
22 - 2018-10-24133Comets4Las Vegas3WXXSommaire du Match
23 - 2018-10-25143Comets1Jayhawks5LSommaire du Match
25 - 2018-10-27158Manchots3Comets5WSommaire du Match
27 - 2018-10-29166Minnesota4Comets8WSommaire du Match
29 - 2018-10-31178Baby Hawks6Comets5LXSommaire du Match
31 - 2018-11-02193Monsters8Comets1LSommaire du Match
35 - 2018-11-06219Comets2Cougars8LSommaire du Match
37 - 2018-11-08227Comets3Bruins1WSommaire du Match
39 - 2018-11-10242Comets5Crunch3WSommaire du Match
41 - 2018-11-12260Comets7Wolf Pack6WSommaire du Match
42 - 2018-11-13266Comets3Sound Tigers4LXXSommaire du Match
44 - 2018-11-15282Comets3Minnesota6LSommaire du Match
46 - 2018-11-17295Rocket5Comets2LSommaire du Match
48 - 2018-11-19316Oceanics2Comets3WSommaire du Match
50 - 2018-11-21329Comets3Admirals4LSommaire du Match
52 - 2018-11-23346Comets5Sharks6LSommaire du Match
53 - 2018-11-24357Comets4Monarchs6LSommaire du Match
56 - 2018-11-27376Monarchs7Comets5LSommaire du Match
58 - 2018-11-29389Las Vegas4Comets5WSommaire du Match
60 - 2018-12-01396Stars5Comets3LSommaire du Match
63 - 2018-12-04423Minnesota5Comets4LSommaire du Match
65 - 2018-12-06437Chill5Comets4LXSommaire du Match
68 - 2018-12-09454Comets3Chiefs2WXXSommaire du Match
70 - 2018-12-11469Comets3Monsters4LSommaire du Match
72 - 2018-12-13483Comets5Chill4WSommaire du Match
74 - 2018-12-15504Phantoms3Comets2LSommaire du Match
75 - 2018-12-16511Oil Kings5Comets4LSommaire du Match
77 - 2018-12-18526Thunder8Comets3LSommaire du Match
79 - 2018-12-20539Chiefs7Comets2LSommaire du Match
81 - 2018-12-22557Oceanics4Comets3LSommaire du Match
86 - 2018-12-27576Comets7Oil Kings3WSommaire du Match
88 - 2018-12-29597Comets5Heat4WXXSommaire du Match
90 - 2018-12-31600Comets3Spiders4LSommaire du Match
92 - 2019-01-02615Comets4Senators3WSommaire du Match
93 - 2019-01-03626Comets5Rocket6LSommaire du Match
95 - 2019-01-05639Comets5Marlies7LSommaire du Match
100 - 2019-01-10680Jayhawks5Comets4LSommaire du Match
103 - 2019-01-13702Cabaret Lady Mary Ann4Comets6WSommaire du Match
106 - 2019-01-16724Oil Kings3Comets4WSommaire du Match
108 - 2019-01-18739Crunch6Comets4LSommaire du Match
110 - 2019-01-20753Cougars5Comets7WSommaire du Match
113 - 2019-01-23770Caroline2Comets6WSommaire du Match
123 - 2019-02-02800Comets4Monsters5LSommaire du Match
125 - 2019-02-04807Comets2Phantoms5LSommaire du Match
126 - 2019-02-05814Comets5Bears4WSommaire du Match
128 - 2019-02-07834Comets5Baby Hawks4WSommaire du Match
130 - 2019-02-09850Heat7Comets6LSommaire du Match
132 - 2019-02-11862Sharks6Comets5LSommaire du Match
134 - 2019-02-13876Comets6Admirals5WXSommaire du Match
135 - 2019-02-14886Comets2Monarchs4LSommaire du Match
137 - 2019-02-16902Comets3Sharks5LSommaire du Match
142 - 2019-02-21939Jayhawks5Comets1LSommaire du Match
144 - 2019-02-23954Sound Tigers3Comets5WSommaire du Match
146 - 2019-02-25967Admirals3Comets4WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
148 - 2019-02-27982Comets3Monsters2WSommaire du Match
149 - 2019-02-28988Comets4Jayhawks5LSommaire du Match
152 - 2019-03-031011Comets3Las Vegas2WSommaire du Match
155 - 2019-03-061030Marlies4Comets5WXXSommaire du Match
156 - 2019-03-071040Comets6Oil Kings2WSommaire du Match
158 - 2019-03-091059Las Vegas3Comets4WSommaire du Match
162 - 2019-03-131082Wolf Pack4Comets7WSommaire du Match
164 - 2019-03-151098Spiders4Comets5WXSommaire du Match
166 - 2019-03-171114Comets5Stars2WSommaire du Match
167 - 2019-03-181119Comets4Baby Hawks3WSommaire du Match
169 - 2019-03-201134Senators2Comets3WSommaire du Match
172 - 2019-03-231161Heat4Comets7WSommaire du Match
173 - 2019-03-241168Monsters7Comets1LSommaire du Match
175 - 2019-03-261183Admirals3Comets2LXSommaire du Match
177 - 2019-03-281195Monarchs2Comets9WSommaire du Match
179 - 2019-03-301212Stars2Comets6WSommaire du Match
182 - 2019-04-021237Sharks3Comets6WSommaire du Match
184 - 2019-04-041249Comets1Chill4LSommaire du Match
186 - 2019-04-061258Comets2Chiefs4LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3010
Assistance61,52330,623
Assistance PCT75.03%74.69%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2247 - 74.92% 52,486$2,151,920$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,121,464$ 6,243,650$ 6,243,650$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
33,389$ 3,121,464$ 39 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 33,389$ 0$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
201882333803341335351-1641181702310178180-241152101031157171-1484335563898101331098611246685177980847273778672015073508524.29%3228374.22%21229239351.36%1174235849.79%759149850.67%1838122720206411096532
Total Saison Régulière82333803341335351-1641181702310178180-241152101031157171-1484335563898101331098611246685177980847273778672015073508524.29%3228374.22%21229239351.36%1174235849.79%759149850.67%1838122720206411096532