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Comets
GP: 12 | W: 2 | L: 9 | OTL: 1 | P: 5
GF: 26 | GA: 42 | PP%: 23.91% | PK%: 76.56%
DG: Mathieu Sicard | Morale : 70 | Moyenne d’équipe : 65
Prochains matchs #201 vs Monsters

Centre de jeu
Rockets
8-3-2, 18pts
4
2 Comets
2-9-1, 5pts
Team Stats
W2SéquenceL2
4-2-0Fiche domicile1-5-0
4-1-2Fiche domicile1-4-1
6-2-2Derniers 10 matchs1-8-1
3.38Buts par match 2.17
3.00Buts contre par match 3.50
23.53%Pourcentage en avantage numérique23.91%
72.92%Pourcentage en désavantage numérique76.56%
Comets
2-9-1, 5pts
2
3 Rockets
8-3-2, 18pts
Team Stats
L2SéquenceW2
1-5-0Fiche domicile4-2-0
1-4-1Fiche domicile4-1-2
1-8-1Derniers 10 matchs6-2-2
2.17Buts par match 3.38
3.50Buts contre par match 3.00
23.91%Pourcentage en avantage numérique23.53%
76.56%Pourcentage en désavantage numérique72.92%
Comets
2-9-1, 5pts
Jour 29
Monsters
2-9-1, 5pts
Statistiques d’équipe
L2SéquenceL3
1-5-0Fiche domicile1-4-1
1-4-1Fiche visiteur1-5-0
1-8-110 derniers matchs2-7-1
2.17Buts par match 2.33
3.50Buts contre par match 2.33
23.91%Pourcentage en avantage numérique16.67%
76.56%Pourcentage en désavantage numérique84.48%
Senators
8-3-1, 17pts
Jour 31
Comets
2-9-1, 5pts
Statistiques d’équipe
W1SéquenceL2
4-1-1Fiche domicile1-5-0
4-2-0Fiche visiteur1-4-1
7-2-110 derniers matchs1-8-1
3.00Buts par match 2.17
2.75Buts contre par match 2.17
20.93%Pourcentage en avantage numérique23.91%
84.00%Pourcentage en désavantage numérique76.56%
Comets
2-9-1, 5pts
Jour 33
Americans
1-9-2, 4pts
Statistiques d’équipe
L2SéquenceL2
1-5-0Fiche domicile0-5-1
1-4-1Fiche visiteur1-4-1
1-8-110 derniers matchs0-8-2
2.17Buts par match 2.33
3.50Buts contre par match 2.33
23.91%Pourcentage en avantage numérique17.39%
76.56%Pourcentage en désavantage numérique80.36%
Meneurs d'équipe
Buts
Ian Moore
5
Passes
Ryan Bottrill
8
Points
Ian Moore
11
Plus/Moins
Sam Stange
1
Victoires
Nikita Tolopilo
2
Pourcentage d’arrêts
Henrik Tikkanen
0.889

Statistiques d’équipe
Buts pour
26
2.17 GFG
Tirs pour
301
25.08 Avg
Pourcentage en avantage numérique
23.9%
11 GF
Début de zone offensive
40.2%
Buts contre
42
3.50 GAA
Tirs contre
350
29.17 Avg
Pourcentage en désavantage numérique
76.6%%
15 GA
Début de la zone défensive
42.2%
Informations de l'équipe

Directeur généralMathieu Sicard
EntraîneurJohn Tortorella
DivisionNorth
ConférenceConference Est
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,968
Billets de saison300


Informations de la formation

Équipe Pro29
Équipe Mineure20
Limite Contrat49 / 99
Espoirs41


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 SPÂgeContratSalaire
1Ty Glover0XX98.0078749263789061736269586853586943706602621,520,000$
2Cole Koepke0XX99.0090886163759093596159596761737351706502831,481,000$
3Sam Stange0X99.0059357164606470684667766370585778706402511,055,000$
4Matej Blumel0XX100.0084769262766873644862646761595962706402641,275,000$
5Ryan Bottrill0XXX99.005732736759687367457659695857587470640241900,000$
6Vincent Arseneau0XX100.00995341558265735648565967618681457063N03421,055,000$
7Josiah Slavin0X100.0056289967756782547353547661778050706302711,309,000$
8Braeden Bowman0XX100.008580917079646759495657665764636570620232900,000$
9Blake Biondi0XX100.005940686260606068557370586956577770620241900,000$
10Dino Kambeitz0XX100.0085838061786779596559596160696749706202621,272,000$
11Ethan Cardwell0XX100.007571816574697260496061606162616870610241900,000$
12Owen Michaels0XXX100.005830715956677162466767636457597670610241615,000$
13Nic Hague0X99.0084778160827884653070606852798263706902711,975,000$
14Ian Moore0X99.006735747269869061456757765670677470690241900,000$
15Cole Hutson (R)0X99.005630777560788369457662746264678270680203900,000$
16Wyatt Aamodt0X100.0085836862756171613067596961737146706502811,100,000$
17Jeremy Hanzel (R)0X100.006035736360737865457654695656597370640232900,000$
18Luca Marrelli (R)0X100.005832736259667261457255695458597670620213835,000$
Rayé
1Ilya Protas (R)0XX100.006240656763687270617673597258598270660203900,000$
2Ondrej Becher0XXX100.007770966973626758695356645561616570610222895,000$
3Thomas Freel0X100.00583273616067736060695569525758707061N0252650,000$
4Sasha Teleguine (R)0XXX100.00603270626267736050665566555558697060N0243650,000$
5Mattys Sicardsson0XXX100.006055706682667055575555616056568470590223956,000$
6Kirill Kudryavtsev0X100.007772896374848262255752695561626670660222900,000$
7Brandon Scanlin0X100.0086857763806987522553516754696863706502721,373,000$
8Corson Ceulemans0X100.007368966576577347255149675361606170610231900,000$
MOYENNE D’ÉQUIPE99.69715577647070756148645967596464667064
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 SPÂgeContratSalaire
1Nikita Tolopilo099.007385819480777978777776667455707802632,515,000$
2Henrik Tikkanen099.007270709571727271697068686469707202611,427,500$
Rayé
1Jaxson Stauber0100.007372728272727271727067706469707102711,427,500$
MOYENNE D’ÉQUIPE99.3373767490747474737372706867647074
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Tortorella6796959999991USA682500,000$


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’équipePOSGP 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
1Ian MooreComets (NJD)D125611-11201918276818.52%1629824.893361641000051100%000000.7400000004
2Ryan BottrillComets (NJD)C/LW/RW12189100422278193.70%122518.780449360000300036.26%17100000.8000000000
3Ty GloverComets (NJD)C/LW12448-32092039102410.26%228023.3923515380002650046.45%39400000.5700000000
4Sam StangeComets (NJD)RW12527180793851913.16%019115.992131135000090036.36%2200000.7300000011
5Nic HagueComets (NJD)D1216702604014177125.88%1729024.171231341000143000%000000.4800000010
6Cole HutsonComets (NJD)D12145-520117205135.00%1425521.321341333000048000%000000.3900000000
7Cole KoepkeComets (NJD)LW/RW120550220679186120%324520.440115380000360048.28%2900000.4100000000
8Matej BlumelComets (NJD)LW/RW122350100189237158.70%118415.351231035000000045.45%1100000.5400000000
9Vincent ArseneauComets (NJD)LW/RW12123-814028481512.50%413811.5500001000060045.45%1100000.4300000000
10Wyatt AamodtComets (NJD)D12123-5160421283712.50%1623219.40123431000038000%000000.2600000000
11Braeden BowmanComets (NJD)LW/RW12112-44010494311.11%21008.370000100001000%100000.4000000000
12Blake BiondiComets (NJD)C/RW12202-800091641012.50%113611.3400000000071047.06%5100000.2900000000
13Jeremy HanzelComets (NJD)D12022-610015141020%1618115.090000200006000%000000.2200000000
14Dino KambeitzComets (NJD)C/RW12022-6801378330%115412.900111100000110051.18%17000000.2600000000
15Ilya ProtasComets (NJD)C/LW8011-220111188150%318022.540003270001390021.43%1400000.1100000000
16Ethan CardwellComets (NJD)C/RW110110001100100.00%01212.5500000000000047.06%1700001.5900000000
17Luca MarrelliComets (NJD)D12011-6401282120%518415.3400001000023000%000000.1100000000
18Josiah SlavinComets (NJD)LW12011-300078350%1887.3600002000000042.86%700000.2300000000
19Sasha TeleguineComets (NJD)C/LW/RW11101-3003693111.11%2766.9800000000000140.91%6600000.2600000000
20Owen MichaelsComets (NJD)C/LW/RW4000-100024130%0297.4100000000000048.00%250000000000000
Statistiques d’équipe totales ou en moyenne216265076-581400289203301851788.64%105348716.1411223310037900044192144.59%98900000.4400000025
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
1Nikita TolopiloComets (NJD)112810.8853.35662013732100200111100
2Henrik TikkanenComets (NJD)10100.8893.00600032700000111000
Statistiques d’équipe totales ou en moyenne122910.8853.32722014034800201212100


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Blake BiondiComets (NJD)C/RW242002-04-24USANo198 Lbs6 ft1NoNoFree AgentNoNo12026-06-01FalseFalsePro & Farm900,000$0$0$No---------------------------
Braeden BowmanComets (NJD)LW/RW232003-06-26CANNo103 Lbs4 ft0NoNoFree AgentNoNo22025-05-22FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Brandon ScanlinComets (NJD)D271999-06-02CANNo214 Lbs6 ft4NoNoTrade2024-08-07NoNo22025-05-25FalseFalsePro & Farm1,373,000$0$0$No1,373,000$--------1,373,000$--------No--------
Cole HutsonComets (NJD)D202006-06-28USAYes172 Lbs5 ft11NoNoFree AgentNoNo32026-06-01FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Cole KoepkeComets (NJD)LW/RW281998-05-17USANo204 Lbs6 ft1NoNoN/ANoNo32026-05-31FalseFalsePro & Farm1,481,000$0$0$No1,481,000$1,481,000$-------1,481,000$1,481,000$-------NoNo-------
Corson CeulemansComets (NJD)D232003-05-05CANNo203 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm900,000$0$0$No---------------------------
Dino KambeitzComets (NJD)C/RW262000-01-25USANo214 Lbs6 ft2NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,272,000$0$0$No1,272,000$--------1,272,000$--------No--------
Ethan CardwellComets (NJD)C/RW242002-08-30CANNo197 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm900,000$0$0$No---------------------------
Henrik TikkanenComets (NJD)G262000-09-28FINNo100 Lbs4 ft0NoNoFree AgentNoNo12026-06-01FalseFalsePro & Farm1,427,500$0$0$No---------------------------
Ian MooreComets (NJD)D242002-01-04USANo205 Lbs6 ft3NoNoProspectNoNo12026-09-12FalseFalsePro & Farm900,000$0$0$No---------------------------
Ilya ProtasComets (NJD)C/LW202006-07-18BLRYes225 Lbs6 ft5NoNoFree AgentNoNo32026-06-01FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Jaxson StauberComets (NJD)G271999-04-27USANo174 Lbs6 ft3NoNoFree AgentNoNo12026-06-01FalseFalsePro & Farm1,427,500$0$0$No---------------------------
Jeremy HanzelComets (NJD)D232003-02-27CANYes201 Lbs6 ft1NoNoFree AgentNoNo22026-06-01FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Josiah SlavinComets (NJD)LW271998-12-31USANo197 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,309,000$0$0$No---------------------------
Kirill KudryavtsevComets (NJD)D222004-02-05RUSNo205 Lbs5 ft11NoNoFree AgentNoNo22025-05-22FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Luca MarrelliComets (NJD)D212005-10-04CANYes185 Lbs6 ft2NoNoFree AgentNoNo32026-06-01FalseFalsePro & Farm835,000$0$0$No835,000$835,000$-------835,000$835,000$-------NoNo-------
Matej BlumelComets (NJD)LW/RW262000-05-31CZENo203 Lbs6 ft0NoNoFree AgentNoNo42025-06-03FalseFalsePro & Farm1,275,000$0$0$No1,275,000$1,275,000$1,275,000$------1,275,000$1,275,000$1,275,000$------NoNoNo------
Mattys SicardssonComets (NJD)C/LW/RW222004-07-17SWENo227 Lbs6 ft5NoNoN/ANoNo32026-05-31FalseFalsePro & Farm956,000$0$0$No956,000$956,000$-------956,000$956,000$-------NoNo-------
Nic HagueComets (NJD)D271998-12-05CANNo231 Lbs6 ft6NoNoN/ANoNo1FalseFalsePro & Farm1,975,000$0$0$No---------------------------
Nikita TolopiloComets (NJD)G262000-04-06RUSNo234 Lbs6 ft6NoNoFree Agent2024-12-15NoNo32026-05-31FalseFalsePro & Farm2,515,000$0$0$No2,515,000$2,515,000$-------2,515,000$2,515,000$-------NoNo-------
Ondrej BecherComets (NJD)C/LW/RW222004-02-22CZENo188 Lbs6 ft1NoNoFree AgentNoNo22025-05-22FalseFalsePro & Farm895,000$0$0$No895,000$--------895,000$--------No--------
Owen MichaelsComets (NJD)C/LW/RW242002-05-01USANo179 Lbs6 ft0NoNoFree AgentNoNo12026-06-24FalseFalsePro & Farm615,000$0$0$No---------------------------
Ryan BottrillComets (NJD)C/LW/RW242002-02-04USANo185 Lbs6 ft1NoNoFree AgentNoNo12026-07-04FalseFalsePro & Farm900,000$0$0$No---------------------------
Sam StangeComets (NJD)RW252001-04-20USANo201 Lbs6 ft1NoNoFree AgentNoNo12026-06-01FalseFalsePro & Farm1,055,000$0$0$No---------------------------
Sasha TeleguineComets (NJD)C/LW/RW242002-09-17USAYes194 Lbs5 ft10YesNoFree AgentNoNo32026-09-12FalseFalsePro & Farm650,000$0$0$No650,000$650,000$-------650,000$650,000$-------YesYes-------
Thomas FreelComets (NJD)C252001-06-26GBRNo190 Lbs6 ft0YesNoFree AgentNoNo22026-09-12FalseFalsePro & Farm650,000$0$0$No650,000$--------650,000$--------Yes--------
Ty GloverComets (NJD)C/LW262000-10-01GBRNo209 Lbs6 ft3NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,520,000$0$0$No1,520,000$--------1,520,000$--------No--------
Vincent ArseneauComets (NJD)LW/RW341992-03-26CANNo237 Lbs6 ft2YesNoFree AgentNoNo22026-09-02FalseFalsePro & Farm1,055,000$0$0$No1,055,000$--------1,055,000$--------Yes--------
Wyatt AamodtComets (NJD)D281997-11-22USANo206 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,100,000$0$0$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2924.76196 Lbs6 ft01.901,116,759$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matej BlumelTy GloverRyan Bottrill40122
2Cole KoepkeEthan CardwellSam Stange30122
3Vincent ArseneauBlake BiondiBraeden Bowman20122
4Josiah SlavinOwen MichaelsDino Kambeitz10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nic HagueIan Moore40122
2Cole HutsonJeremy Hanzel30122
3Wyatt AamodtLuca Marrelli20122
4Nic HagueIan Moore10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cole KoepkeTy GloverRyan Bottrill60122
2Matej BlumelDino KambeitzSam Stange40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nic HagueIan Moore60122
2Cole HutsonWyatt Aamodt40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Ty GloverCole Koepke60122
2Ryan BottrillSam Stange40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nic HagueIan Moore60122
2Cole HutsonWyatt Aamodt40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Ty Glover60122Nic HagueIan Moore60122
2Cole Koepke40122Cole HutsonWyatt Aamodt40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ty GloverCole Koepke60122
2Ryan BottrillSam Stange40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nic HagueIan Moore60122
2Cole HutsonWyatt Aamodt40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cole KoepkeTy GloverRyan BottrillNic HagueIan Moore
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cole KoepkeTy GloverRyan BottrillNic HagueIan Moore
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Vincent Arseneau, Josiah Slavin, Blake BiondiVincent Arseneau, Josiah SlavinBlake Biondi
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jeremy Hanzel, Luca Marrelli, Cole HutsonJeremy HanzelLuca Marrelli, Cole Hutson
Tirs de pénalité
Ty Glover, Cole Koepke, Ryan Bottrill, Sam Stange, Matej Blumel
Gardien
#1 : Henrik Tikkanen, #2 : Nikita Tolopilo


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
TotalDomicile Visiteur
# 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 RI
1Americans2110000067-11010000013-21100000054120.500612180061010054958711815916305710330.00%15473.33%017739644.70%18741644.95%7717344.51%2791842879115678
2Crunch2020000049-51010000025-31010000024-200.00047110061010055958711816516204511218.18%90100.00%017739644.70%18741644.95%7717344.51%2791842879115678
3Griffins2020000058-31010000034-11010000024-200.0005914106101004795871181672328525240.00%12283.33%017739644.70%18741644.95%7717344.51%2791842879115678
4Marlies2020000018-71010000013-21010000005-500.000123006101004495871181541724487114.29%9366.67%017739644.70%18741644.95%7717344.51%2791842879115678
5Monsters11000000404110000004040000000000021.00048120161010022958711812511818300.00%40100.00%017739644.70%18741644.95%7717344.51%2791842879115678
6Rockets2020000047-31010000024-21010000023-100.0004812106101006095871181491016388337.50%8450.00%017739644.70%18741644.95%7717344.51%2791842879115678
7Senators1000010023-1000000000001000010023-110.50024600610100199587118131121431200.00%7271.43%017739644.70%18741644.95%7717344.51%2791842879115678
Total1229001002642-16615000001319-6614001001323-1050.2082650762161010030195871181350105140289461123.91%641576.56%017739644.70%18741644.95%7717344.51%2791842879115678
_Since Last GM Reset1229001002642-16615000001319-6614001001323-1050.2082650762161010030195871181350105140289461123.91%641576.56%017739644.70%18741644.95%7717344.51%2791842879115678
_Vs Conference1229001002642-16615000001319-6614001001323-1050.2082650762161010030195871181350105140289461123.91%641576.56%017739644.70%18741644.95%7717344.51%2791842879115678

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
125L226507630135010514028921
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
122901002642
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
61500001319
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
61401001323
Derniers 10 matchs
WLOTWOTL SOWSOL
180100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
461123.91%641576.56%0
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
95871181610100
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
17739644.70%18741644.95%7717344.51%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2791842879115678


Derniers matchs 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
210Comets5Americans4WSommaire du match
326Americans3Comets1LSommaire du match
647Marlies3Comets1LSommaire du match
966Griffins4Comets3LSommaire du match
1180Comets2Griffins4LSommaire du match
1498Monsters0Comets4WSommaire du match
16114Comets2Crunch4LSommaire du match
17119Comets0Marlies5LSommaire du match
21143Crunch5Comets2LSommaire du match
22153Comets2Senators3LXSommaire du match
25168Rockets4Comets2LSommaire du match
27188Comets2Rockets3LSommaire du match
29201Comets-Monsters-
31214Senators-Comets-
33232Comets-Americans-
35246Canucks-Comets-
39261Comets-Gulls-
41278Wranglers-Comets-
43295Comets-Monsters-
45306Gulls-Comets-
48329Barracuda-Comets-
52357Wild-Comets-
54372Comets-Barracuda-
56381Comets-Rockets-
60399Bears-Comets-
62416Comets-Senators-
63429Hammers-Comets-
66449Comets-Griffins-
68462Condors-Comets-
70477Comets-Wolf Pack-
72490Silver Knight-Comets-
74505Comets-Moose-
77519Comets-Wolves-
79530Stars-Comets-
81549Comets-Checkers-
83563Wolves-Comets-
85582Comets-Reign-
87596Checkers-Comets-
89614Comets-Silver Knight-
91626Admirals-Comets-
93639Comets-Bears-
96657Wolf Pack-Comets-
98675Comets-Crunch-
100685Comets-Condors-
101698Penguins-Comets-
104721Reign-Comets-
106735Comets-Wranglers-
108746Comets-Eagles-
110760Rockets-Comets-
112775Comets-Canucks-
116792Eagles-Comets-
119817Comets-Phantoms-
121825Senators-Comets-
123844Comets-Firebird-
124853Comets-Stars-
126867IceHogs-Comets-
128889Thunderbirds-Comets-
131908Comets-Hammers-
132920Phantoms-Comets-
137946Comets-Thunderbirds-
138951Firebird-Comets-
141969Comets-Bruins-
142980Bruins-Comets-
1471012Roadrunners-Comets-
1481020Comets-Wild-
1511038Marlies-Comets-
1521049Comets-Marlies-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1541057Comets-Admirals-
1571075Comets-IceHogs-
1581083Griffins-Comets-
1631111Monsters-Comets-
1671138Comets-Penguins-
1691147Americans-Comets-
1731171Crunch-Comets-
1781193Moose-Comets-
1821203Comets-Roadrunners-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance11,8086,000
Assistance PCT98.40%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
32 2968 - 98.93% 169,205$1,015,227$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,017,332$ 6,477,200$ 6,477,200$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 944,351$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,414,544$ 158 37,715$ 5,958,970$




Comets Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Comets Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Comets Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Comets Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Comets Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA