Adirondack Phantoms

GP: 25 | W: 10 | L: 11 | OTL: 4 | P: 24
GF: 56 | GA: 65 | PP%: 21.95% | PK%: 80.90%
DG: Mathieu Veilleux | Morale : 39 | Moyenne d'Équipe : N/A
Prochain matchs #428 vs Oklahoma City Barons
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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 SPÂgeContratSalaire Moyen
1Benoit PouliotXX100.007545757377827775557273627688917040003411,000,000$
2Mike Winther (R)X100.00704078887178747875787766747172703400261875,000$
3Fredrik Karlstrom (R)XXX100.00633292817777777874787568736564704500221900,000$
4Michael ParksX100.008037767980818175627876697670707045002821,250,000$
5Vladimir SobotkaXX100.008345727773757478787675687796967045003321,250,000$
6Wojtek WolskiXX100.00694384728278787560757463779899704500342800,000$
7Zach HamillX100.00564688767573727476737467738688704500321800,000$
8Zach BudishXX100.00854575768477777566777670728381704500292750,000$
9Alexis Loiseau (R)X100.007438788176767680747978687470737025002621,600,000$
10Alexandre MalletXXX100.008038777577747375747575667070727035002821,250,000$
11Sebastian Repo (R)X100.00804375748578827670747571716665704500242800,000$
12Keegan Kolesar (R)X100.00895069718875777666727565706464704500232900,000$
13Alex PlanteX100.008248717094797372507361855787927045003111,700,000$
14Tyler Lewington (R)X100.008845717686818076507661826369707045002611,250,000$
15Taylor ChorneyX100.007545877376747176537859846695987045003311,900,000$
16Daniel Brickley (R)X100.008743747284787573507764836163657045002521,200,000$
17Greg PaterynX100.008746737382757374507762866285877045003011,950,000$
18Teemu EronenX100.007042818076787378507965826883847035003031,950,000$
19Randy GazzolaX100.007640817679797577607866806372747045002721,700,000$
20Markus Niemelainen (R)X100.00813876778076747250725781575757704500221750,000$
Rayé
1Nikita Popugaev (R)XX100.00733579768576727360717162705453703200221800,000$
2Chris Martenet (R)X100.00915269699075736650695882586664703500242600,000$
MOYENNE D'ÉQUIPE100.0078437776817775756275697369757670410
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
1Aaron Dell99.0085818485898989888988906869703500
2Jakub Kovar100.0086888586898687878887896463702500
Rayé
1Anthony Brodeur (R)100.0084808179838182818180805454703500
MOYENNE D'ÉQUIPE99.678583838387858685868586626270320
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Claude Noel90908585858570CAN651950,000$


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
1Alex PlanteAdirondack Phantoms (PHI)D2531417224036184511266.67%3548019.233583176000069100.00%000000.7100000210
2Daniel BrickleyAdirondack Phantoms (PHI)D2511415-61803131436232.33%4453221.300552459000175000.00%000000.5600000001
3Sebastian RepoAdirondack Phantoms (PHI)RW2596154200702062254114.52%550920.383471164000000046.34%12300000.5900000201
4Tyler LewingtonAdirondack Phantoms (PHI)D2521012-518037281652412.50%2045518.2400004000028100.00%000000.5300000011
5Greg PaterynAdirondack Phantoms (PHI)D2511112-43006734266313.85%5358923.561341363000052000.00%000000.4100000012
6Zach BudishAdirondack Phantoms (PHI)C/RW2575121160565856215312.50%448819.5512312710000222154.05%55500000.4903000302
7Fredrik KarlstromAdirondack Phantoms (PHI)C/LW/RW25831100043268185511.76%1158523.4332511690000870251.11%22500000.3803000110
8Michael ParksAdirondack Phantoms (PHI)RW255611-1312032266926457.25%355722.3235817640001510046.36%15100000.3900000001
9Taylor ChorneyAdirondack Phantoms (PHI)D2511011-26018383117323.23%3260424.171561472000075010.00%000000.3600000010
10Wojtek WolskiAdirondack Phantoms (PHI)LW/RW25538540192343133711.63%244217.69000228000080142.86%42000000.3600000211
11Randy GazzolaAdirondack Phantoms (PHI)D2517811201118111079.09%1933013.220000000000000.00%000000.4800000001
12Vladimir SobotkaAdirondack Phantoms (PHI)C/LW25437010046155419427.41%251920.7722415720001852052.73%5500000.2701000010
13Zach HamillAdirondack Phantoms (PHI)C253366003223512218.57%434713.9000001000040047.06%1700000.3500000000
14Alexandre MalletAdirondack Phantoms (PHI)C/LW/RW16134-820814138157.69%118511.591236240000121056.52%2300000.4300000000
15Mike WintherAdirondack Phantoms (PHI)C20213-90010203511185.71%124012.030001100001142046.48%25600000.2501000000
16Benoit PouliotAdirondack Phantoms (PHI)LW/RW14202-2005161131218.18%120214.47000160000131142.47%18600000.2000000100
17Keegan KolesarAdirondack Phantoms (PHI)RW25112-41202910234114.35%22369.4400000000000046.15%1300000.1700000000
18Teemu EronenAdirondack Phantoms (PHI)D19011100133000.00%4201.060001000003000.00%000000.9900000000
19Nick SuzukiPhiladelphia FlyersC/RW3011000556040.00%03913.0900000000000033.33%300000.5100000000
20Markus NiemelainenAdirondack Phantoms (PHI)D25000000001000.00%130.130000000000000.00%000000.0000000000
21Nikita PopugaevAdirondack Phantoms (PHI)LW/RW12000000000000.00%040.410000000000000.00%000000.0000000000
22Chris MartenetAdirondack Phantoms (PHI)D19000000000000.00%020.130000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne47856102158-3318404884316512154978.60%244737815.44183553159691000460610648.20%202700000.430800011710
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
1Aaron DellAdirondack Phantoms (PHI)25101140.9122.52145260616970110.5008250121
2Anthony BrodeurAdirondack Phantoms (PHI)20001.0000.0063000150000.0000019000
Stats d'équipe Total ou en Moyenne27101140.9142.42151560617120110.50082519121


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 Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Aaron DellAdirondack Phantoms (PHI)G311988-01-22 13:08:31No205 Lbs6 ft0NoNoNo2Pro & Farm750,000$522,606$750,000$522,606$0$0$No750,000$
Alex PlanteAdirondack Phantoms (PHI)D311988-01-22 06:29:38No230 Lbs6 ft4NoNoNo1Pro & Farm1,700,000$1,184,574$1,700,000$1,184,574$0$0$No
Alexandre MalletAdirondack Phantoms (PHI)C/LW/RW281991-01-22 04:34:51No195 Lbs6 ft1NoNoNo2Pro & Farm1,250,000$871,010$1,250,000$871,010$0$0$No1,250,000$
Alexis LoiseauAdirondack Phantoms (PHI)C261993-01-22 16:01:11Yes179 Lbs6 ft1NoNoNo2Pro & Farm1,600,000$1,114,893$1,600,000$1,114,893$0$0$No1,600,000$
Anthony BrodeurAdirondack Phantoms (PHI)G251994-01-22 07:21:10Yes194 Lbs5 ft10NoNoNo1Pro & Farm650,000$452,925$650,000$452,925$0$0$No
Benoit PouliotAdirondack Phantoms (PHI)LW/RW341985-01-22 12:29:38No199 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$696,808$1,000,000$696,808$0$0$No
Chris MartenetAdirondack Phantoms (PHI)D241995-01-22 01:57:24Yes216 Lbs6 ft7NoNoNo2Pro & Farm600,000$418,085$600,000$418,085$0$0$No600,000$
Daniel BrickleyAdirondack Phantoms (PHI)D251994-01-22 11:12:14Yes205 Lbs6 ft3NoNoNo2Pro & Farm1,200,000$836,170$1,200,000$836,170$0$0$No1,200,000$
Fredrik KarlstromAdirondack Phantoms (PHI)C/LW/RW221997-01-22 03:40:25Yes185 Lbs6 ft2NoNoNo1Pro & Farm900,000$627,127$900,000$627,127$0$0$No
Greg PaterynAdirondack Phantoms (PHI)D301989-01-22 09:14:31No214 Lbs6 ft3NoNoNo1Pro & Farm1,950,000$1,358,776$1,950,000$1,358,776$0$0$No
Jakub KovarAdirondack Phantoms (PHI)G321987-01-22 02:33:31No201 Lbs6 ft1NoNoNo2Pro & Farm1,200,000$836,170$1,200,000$836,170$0$0$No1,200,000$
Keegan KolesarAdirondack Phantoms (PHI)RW231996-01-22 03:29:26Yes227 Lbs6 ft2NoNoNo2Pro & Farm900,000$627,127$900,000$627,127$0$0$No900,000$
Markus NiemelainenAdirondack Phantoms (PHI)D221997-01-22 06:53:24Yes190 Lbs6 ft6NoNoNo1Pro & Farm750,000$522,606$750,000$522,606$0$0$No
Michael ParksAdirondack Phantoms (PHI)RW281991-01-22 10:15:43No196 Lbs6 ft0NoNoNo2Pro & Farm1,250,000$871,010$1,250,000$871,010$0$0$No1,250,000$
Mike WintherAdirondack Phantoms (PHI)C261993-01-22 07:52:34Yes170 Lbs5 ft11NoNoNo1Pro & Farm875,000$609,707$875,000$609,707$0$0$No
Nikita PopugaevAdirondack Phantoms (PHI)LW/RW221997-01-22 07:00:26Yes216 Lbs6 ft6NoNoNo1Pro & Farm800,000$557,446$800,000$557,446$0$0$No
Randy GazzolaAdirondack Phantoms (PHI)D271992-01-22 18:09:29No201 Lbs6 ft3NoNoNo2Pro & Farm1,700,000$1,184,574$1,700,000$1,184,574$0$0$No1,700,000$
Sebastian RepoAdirondack Phantoms (PHI)RW241995-01-22 03:08:53Yes212 Lbs6 ft3NoNoNo2Pro & Farm800,000$557,446$800,000$557,446$0$0$No800,000$
Taylor ChorneyAdirondack Phantoms (PHI)D331986-01-22 18:29:38No193 Lbs6 ft0NoNoNo1Pro & Farm1,900,000$1,323,936$1,900,000$1,323,936$0$0$No
Teemu EronenAdirondack Phantoms (PHI)D301989-01-22 20:03:05No180 Lbs5 ft10NoNoNo3Pro & Farm1,950,000$1,358,776$1,950,000$1,358,776$0$0$No1,950,000$1,950,000$
Tyler LewingtonAdirondack Phantoms (PHI)D261993-01-22 04:11:09Yes194 Lbs6 ft1NoNoNo1Pro & Farm1,250,000$871,010$1,250,000$871,010$0$0$No
Vladimir SobotkaAdirondack Phantoms (PHI)C/LW331986-01-22 18:29:38No183 Lbs5 ft10NoNoNo2Pro & Farm1,250,000$871,010$1,250,000$871,010$0$0$No1,250,000$
Wojtek WolskiAdirondack Phantoms (PHI)LW/RW341985-01-22 12:29:38No215 Lbs6 ft3NoNoNo2Pro & Farm800,000$557,446$800,000$557,446$0$0$No800,000$
Zach BudishAdirondack Phantoms (PHI)C/RW291990-01-22 06:02:20No214 Lbs6 ft3NoNoNo2Pro & Farm750,000$522,606$750,000$522,606$0$0$No750,000$
Zach HamillAdirondack Phantoms (PHI)C321987-01-22 00:29:38No180 Lbs5 ft11NoNoNo1Pro & Farm800,000$557,446$800,000$557,446$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2527.88200 Lbs6 ft21.601,143,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Fredrik KarlstromZach BudishVladimir Sobotka25122
2Keegan KolesarBenoit PouliotMichael Parks25122
3Sebastian RepoWojtek WolskiZach Hamill25122
4Fredrik KarlstromMichael ParksSebastian Repo25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alex PlanteTaylor Chorney25122
2Greg PaterynRandy Gazzola25122
3Tyler LewingtonDaniel Brickley25122
4Greg PaterynTaylor Chorney25122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Fredrik KarlstromZach BudishVladimir Sobotka60122
2Wojtek WolskiSebastian RepoMichael Parks40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alex PlanteTaylor Chorney60122
2Greg PaterynDaniel Brickley40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Fredrik KarlstromVladimir Sobotka60122
2Zach BudishMichael Parks40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Daniel BrickleyTaylor Chorney60122
2Greg PaterynAlex Plante40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Michael Parks60122Daniel BrickleyTaylor Chorney60122
2Fredrik Karlstrom40122Greg PaterynAlex Plante40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Fredrik KarlstromZach Budish60122
2Vladimir SobotkaMichael Parks40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alex PlanteTaylor Chorney60122
2Greg PaterynTyler Lewington40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Fredrik KarlstromZach BudishVladimir SobotkaAlex PlanteTaylor Chorney
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Fredrik KarlstromZach BudishVladimir SobotkaAlex PlanteTaylor Chorney
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Parks, Fredrik Karlstrom, Zach BudishMichael Parks, Fredrik KarlstromMichael Parks
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Taylor Chorney, Greg Pateryn, Daniel BrickleyTaylor ChorneyTaylor Chorney, Daniel Brickley
Tirs de Pénalité
Fredrik Karlstrom, Zach Budish, Vladimir Sobotka, Michael Parks, Wojtek Wolski
Gardien
#1 : Aaron Dell, #2 : Jakub Kovar
Lignes d'Attaque Perso. en Prol.
Zach Budish, Benoit Pouliot, Wojtek Wolski, Michael Parks, Zach Hamill, Vladimir Sobotka, Vladimir Sobotka, Keegan Kolesar, Fredrik Karlstrom, Sebastian Repo, Alexis Loiseau
Lignes de Défense Perso. en Prol.
Tyler Lewington, Taylor Chorney, Greg Pateryn, Alex Plante, Daniel Brickley


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
1Albany Devils512000021016-641100002812-41010000024-240.40010172700281414014122221121214124453611421314.29%17194.12%038781147.72%41483949.34%17636148.75%593406599187322161
2Bridgeport Sound Tigers1010000002-2000000000001010000002-200.000000002814140222222112121431111018200.00%50100.00%038781147.72%41483949.34%17636148.75%593406599187322161
3CCCP Red Army1010000034-1000000000001010000034-100.0003690028141402722221121214327419200.00%20100.00%038781147.72%41483949.34%17636148.75%593406599187322161
4Charlotte Checkers1010000013-2000000000001010000013-200.000123102814140252222112121432162202150.00%110.00%038781147.72%41483949.34%17636148.75%593406599187322161
5Chicago Wolves11000000321000000000001100000032121.000358002814140222222112121442188223133.33%4175.00%038781147.72%41483949.34%17636148.75%593406599187322161
6Connecticut Whale11000000514000000000001100000051421.0005914002814140222222112121424104155240.00%20100.00%038781147.72%41483949.34%17636148.75%593406599187322161
7Gatineau Olympiques22000000725110000003121100000041341.000714210028141404322221121214632020435240.00%100100.00%038781147.72%41483949.34%17636148.75%593406599187322161
8Lake Erie Monsters1010000023-11010000023-10000000000000.000246002814140292222112121428810199222.22%5260.00%038781147.72%41483949.34%17636148.75%593406599187322161
9Manitoba Moose22000000642220000006420000000000041.000611170028141405022221121214481516425240.00%8362.50%038781147.72%41483949.34%17636148.75%593406599187322161
10Mercer Island Hafgufa11000000321110000003210000000000021.0003690028141402022221121214309141722100.00%7185.71%038781147.72%41483949.34%17636148.75%593406599187322161
11Norfolk Admirals1010000014-3000000000001010000014-300.000112002814140382222112121424929200.00%10100.00%038781147.72%41483949.34%17636148.75%593406599187322161
12Peoria Rivermen2020000026-4000000000002020000026-400.0002460028141405822221121214681116424125.00%8275.00%038781147.72%41483949.34%17636148.75%593406599187322161
13Providence Bruins1000010023-1000000000001000010023-110.50023500281414025222211212143611818500.00%220.00%038781147.72%41483949.34%17636148.75%593406599187322161
14San Antonio Rampage21100000550211000005500000000000020.5005914002814140392222112121456182031400.00%9277.78%038781147.72%41483949.34%17636148.75%593406599187322161
Total251011001035665-91364000033033-31247001002632-6240.4805610215810281414065122221121214713244190488821821.95%891780.90%038781147.72%41483949.34%17636148.75%593406599187322161
15Trois-Rivières Draveurs1010000024-21010000024-20000000000000.00024600281414035222211212142914624300.00%2150.00%038781147.72%41483949.34%17636148.75%593406599187322161
16Wilkes-Barre/Scranton Penguins210000014401000000112-11100000032130.75047110028141405522221121214462214358225.00%6183.33%038781147.72%41483949.34%17636148.75%593406599187322161
_Since Last GM Reset251011001035665-91364000033033-31247001002632-6240.4805610215810281414065122221121214713244190488821821.95%891780.90%038781147.72%41483949.34%17636148.75%593406599187322161
_Vs Conference1868001033950-111043000032227-5825001001723-6160.444396910810281414047922221121214482178122345591016.95%551180.00%038781147.72%41483949.34%17636148.75%593406599187322161
_Vs Division1133000032330-751100003914-5622000001416-290.409234164102814140292222211212142891117022140820.00%33390.91%038781147.72%41483949.34%17636148.75%593406599187322161

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2524W35610215865171324419048810
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
25101101035665
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
136400033033
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
124701002632
Derniers 10 Matchs
WLOTWOTL SOWSOL
630001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
821821.95%891780.90%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
222211212142814140
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
38781147.72%41483949.34%17636148.75%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
593406599187322161


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
3 - 2020-10-3017Albany Devils2Adirondack Phantoms1LXXSommaire du Match
5 - 2020-11-0134Adirondack Phantoms5Connecticut Whale1WSommaire du Match
6 - 2020-11-0247Adirondack Phantoms1Charlotte Checkers3LSommaire du Match
8 - 2020-11-0458Albany Devils4Adirondack Phantoms3LXXSommaire du Match
10 - 2020-11-0678Albany Devils4Adirondack Phantoms1LSommaire du Match
12 - 2020-11-0893Adirondack Phantoms0Bridgeport Sound Tigers2LSommaire du Match
15 - 2020-11-11115San Antonio Rampage1Adirondack Phantoms3WSommaire du Match
17 - 2020-11-13126Adirondack Phantoms2Albany Devils4LSommaire du Match
19 - 2020-11-15147Manitoba Moose2Adirondack Phantoms3WSommaire du Match
20 - 2020-11-16151Adirondack Phantoms3CCCP Red Army4LSommaire du Match
23 - 2020-11-19174Trois-Rivières Draveurs4Adirondack Phantoms2LSommaire du Match
25 - 2020-11-21187Adirondack Phantoms1Norfolk Admirals4LSommaire du Match
29 - 2020-11-25211Albany Devils2Adirondack Phantoms3WSommaire du Match
31 - 2020-11-27228Adirondack Phantoms2Providence Bruins3LXSommaire du Match
32 - 2020-11-28233Adirondack Phantoms1Peoria Rivermen3LSommaire du Match
34 - 2020-11-30253Wilkes-Barre/Scranton Penguins2Adirondack Phantoms1LXXSommaire du Match
37 - 2020-12-03271Adirondack Phantoms3Wilkes-Barre/Scranton Penguins2WSommaire du Match
39 - 2020-12-05285Lake Erie Monsters3Adirondack Phantoms2LSommaire du Match
41 - 2020-12-07303Adirondack Phantoms3Chicago Wolves2WSommaire du Match
43 - 2020-12-09317San Antonio Rampage4Adirondack Phantoms2LSommaire du Match
46 - 2020-12-12340Manitoba Moose2Adirondack Phantoms3WSommaire du Match
50 - 2020-12-16368Adirondack Phantoms1Peoria Rivermen3LSommaire du Match
52 - 2020-12-18377Mercer Island Hafgufa2Adirondack Phantoms3WSommaire du Match
54 - 2020-12-20396Adirondack Phantoms4Gatineau Olympiques1WSommaire du Match
56 - 2020-12-22409Gatineau Olympiques1Adirondack Phantoms3WSommaire du Match
59 - 2020-12-25428Adirondack Phantoms-Oklahoma City Barons-
60 - 2020-12-26442Manitoba Moose-Adirondack Phantoms-
65 - 2020-12-31471Roberval Dwarfs-Adirondack Phantoms-
67 - 2021-01-02487Adirondack Phantoms-Charlotte Checkers-
69 - 2021-01-04502Roberval Dwarfs-Adirondack Phantoms-
71 - 2021-01-06518Adirondack Phantoms-Providence Bruins-
73 - 2021-01-08534Laval Chiefs-Adirondack Phantoms-
75 - 2021-01-10546Adirondack Phantoms-Houston Aeros-
78 - 2021-01-13565Adirondack Phantoms-Manitoba Moose-
79 - 2021-01-14574Bridgeport Sound Tigers-Adirondack Phantoms-
82 - 2021-01-17602Trois-Rivières Draveurs-Adirondack Phantoms-
84 - 2021-01-19612Adirondack Phantoms-San Antonio Rampage-
86 - 2021-01-21624Adirondack Phantoms-Norfolk Admirals-
88 - 2021-01-23638Adirondack Phantoms-Chicoutimi Saguenéens-
89 - 2021-01-24646Springfield Falcons-Adirondack Phantoms-
92 - 2021-01-27670Adirondack Phantoms-Milwaukee Admirals-
93 - 2021-01-28679Albany Devils-Adirondack Phantoms-
97 - 2021-02-01707CCCP Red Army-Adirondack Phantoms-
99 - 2021-02-03720Adirondack Phantoms-Wilkes-Barre/Scranton Penguins-
101 - 2021-02-05738Binghamton Senators-Adirondack Phantoms-
103 - 2021-02-07761Adirondack Phantoms-Henderson Silver Knights-
104 - 2021-02-08770Connecticut Whale-Adirondack Phantoms-
107 - 2021-02-11783Adirondack Phantoms-Roberval Dwarfs-
109 - 2021-02-13803Charlotte Checkers-Adirondack Phantoms-
111 - 2021-02-15813Adirondack Phantoms-Albany Devils-
114 - 2021-02-18835Adirondack Phantoms-CCCP Red Army-
115 - 2021-02-19843Wilkes-Barre/Scranton Penguins-Adirondack Phantoms-
120 - 2021-02-24873Norfolk Admirals-Adirondack Phantoms-
122 - 2021-02-26887Adirondack Phantoms-Bridgeport Sound Tigers-
124 - 2021-02-28902Adirondack Phantoms-CCCP Red Army-
125 - 2021-03-01911Norfolk Admirals-Adirondack Phantoms-
128 - 2021-03-04935Adirondack Phantoms-Connecticut Whale-
129 - 2021-03-05944Joliette Sportif-Adirondack Phantoms-
132 - 2021-03-08966Adirondack Phantoms-Trois-Rivières Draveurs-
133 - 2021-03-09975Rockford IceHogs-Adirondack Phantoms-
137 - 2021-03-131004Grand Rapids Griffins-Adirondack Phantoms-
138 - 2021-03-141011Adirondack Phantoms-The Nuuk Vikings-
141 - 2021-03-171034Bridgeport Sound Tigers-Adirondack Phantoms-
145 - 2021-03-211062Adirondack Phantoms-Rochester Americans-
146 - 2021-03-221069Providence Bruins-Adirondack Phantoms-
149 - 2021-03-251087Adirondack Phantoms-Grand Rapids Griffins-
151 - 2021-03-271103Rochester Americans-Adirondack Phantoms-
153 - 2021-03-291116Adirondack Phantoms-Albany Devils-
155 - 2021-03-311132Adirondack Phantoms-Rochester Americans-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
157 - 2021-04-021141Adirondack Phantoms-Connecticut Whale-
158 - 2021-04-031150Las Vegas Gamblers-Adirondack Phantoms-
161 - 2021-04-061173Connecticut Whale-Adirondack Phantoms-
163 - 2021-04-081185Adirondack Phantoms-Bridgeport Sound Tigers-
166 - 2021-04-111204Rouyn-Noranda Huskies-Adirondack Phantoms-
169 - 2021-04-141223Adirondack Phantoms-Grand Rapids Griffins-
171 - 2021-04-161240Adirondack Phantoms-Binghamton Senators-
172 - 2021-04-171249Chicoutimi Saguenéens-Adirondack Phantoms-
177 - 2021-04-221269Rouyn-Noranda Huskies-Adirondack Phantoms-
184 - 2021-04-291302Chicoutimi Saguenéens-Adirondack Phantoms-
185 - 2021-04-301308Adirondack Phantoms-Binghamton Senators-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets10060
Assistance19,38712,155
Assistance PCT74.57%93.50%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
27 2426 - 80.88% 191,115$2,484,500$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,099,220$ 2,857,500$ 2,857,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
15,199$ 808,495$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
5,160,115$ 131 20,253$ 2,653,143$




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