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Fighting Pandas
GP: 75 | W: 42 | L: 24 | OTL: 9 | P: 93
GF: 323 | GA: 265 | PP%: 26.75% | PK%: 79.29%
DG: Hunter Jones | Morale : 58 | Moyenne d’équipe : 60
Prochains matchs #825 vs Wombats

Centre de jeu
Lynx
37-34-1, 75pts
7
FINAL
6 Fighting Pandas
42-24-9, 93pts
Team Stats
W3SéquenceL2
18-18-1Fiche domicile20-11-6
19-16-0Fiche domicile22-13-3
4-6-0Derniers 10 matchs4-5-1
4.00Buts par match 4.31
4.13Buts contre par match 3.53
29.86%Pourcentage en avantage numérique26.75%
82.67%Pourcentage en désavantage numérique79.29%
Fighting Pandas
42-24-9, 93pts
4
FINAL
5 Marlies
53-19-3, 109pts
Team Stats
L2SéquenceW5
20-11-6Fiche domicile28-7-2
22-13-3Fiche domicile25-12-1
4-5-1Derniers 10 matchs9-1-0
4.31Buts par match 4.57
3.53Buts contre par match 3.23
26.75%Pourcentage en avantage numérique26.78%
79.29%Pourcentage en désavantage numérique76.84%
Wombats
41-21-9, 91pts
Jour 162
Fighting Pandas
42-24-9, 93pts
Statistiques d’équipe
W1SéquenceL2
19-15-3Fiche domicile20-11-6
22-6-6Fiche visiteur22-13-3
7-3-010 derniers matchs4-5-1
4.52Buts par match 4.31
3.92Buts contre par match 4.31
20.83%Pourcentage en avantage numérique26.75%
82.07%Pourcentage en désavantage numérique79.29%
Fighting Pandas
42-24-9, 93pts
Jour 164
Bruins
23-43-10, 56pts
Statistiques d’équipe
L2SéquenceL3
20-11-6Fiche domicile10-22-5
22-13-3Fiche visiteur13-21-5
4-5-110 derniers matchs3-6-1
4.31Buts par match 3.75
3.53Buts contre par match 3.75
26.75%Pourcentage en avantage numérique25.32%
79.29%Pourcentage en désavantage numérique72.22%
Fighting Pandas
42-24-9, 93pts
Jour 167
Marlies
53-19-3, 109pts
Statistiques d’équipe
L2SéquenceW5
20-11-6Fiche domicile28-7-2
22-13-3Fiche visiteur25-12-1
4-5-110 derniers matchs9-1-0
4.31Buts par match 4.57
3.53Buts contre par match 4.57
26.75%Pourcentage en avantage numérique26.78%
79.29%Pourcentage en désavantage numérique76.84%
Meneurs d'équipe
Connor BrownButs
Connor Brown
49
Sean DurziPasses
Sean Durzi
72
Mackie SamoskevichPoints
Mackie Samoskevich
93
Alec MartinezPlus/Moins
Alec Martinez
30
Jakub DobesVictoires
Jakub Dobes
41
Cayden PrimeauPourcentage d’arrêts
Cayden Primeau
0.89

Statistiques d’équipe
Buts pour
323
4.31 GFG
Tirs pour
2363
31.51 Avg
Pourcentage en avantage numérique
26.8%
42 GF
Début de zone offensive
38.7%
Buts contre
265
3.53 GAA
Tirs contre
2306
30.75 Avg
Pourcentage en désavantage numérique
79.3%%
35 GA
Début de la zone défensive
38.9%
Informations de l'équipe

Directeur généralHunter Jones
EntraîneurPatrick Lalime
DivisionAtlantic
ConférenceEastern Conference
CapitaineJeff Skinner
Assistant #1Ryker Evans
Assistant #2Keegan Kolesar


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro24
Équipe Mineure19
Limite contact 43 / 50
Espoirs28


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
1Mackie Samoskevich (R)XX98.00765591766573837550707260545860080660232500,000$
2Connor BrownX100.00525494676574927250686976517474081660322500,000$
3Jeff Skinner (C)XX100.006556896971728374576673605179760806603312,000,000$
4Keegan Kolesar (A)X100.00857189687772927550686666506868079660282500,000$
5Radek FaksaX100.00785979657772826680655571617675079640323500,000$
6Cole KoepkeX100.00826292667469836850646365506766079640271500,000$
7Beck MalenstynX100.00836183637567865861605167506868079610282700,000$
8Alexander HoltzX100.00655690677269706150635359535960079590242500,000$
9Samuel Helenius (R)X100.00846990667563676064585559505959079590233750,000$
10Ivan Ivan (R)XX100.00545590656864625955575756505960054570232500,000$
11Ben JonesX100.00747499606661555250534959506463065550274500,000$
12Georgii MerkulovX100.00503983576150535050505050505860021510251500,000$
13Ryker Evans (A)X100.00785979687175877450705771566164080670242500,000$
14Alec MartinezX98.00635793647374677350656372568883079660382700,000$
15Sean DurziX99.006166776770756274506763735667690816502711,000,000$
16Kaedan KorczakX100.00725696627466646950655170656165060630242500,000$
17Declan ChisholmX100.00635692656871806850615467556565079630262500,000$
Rayé
1Arshdeep BainsX100.00645089576560535250505054506261020530252500,000$
2Matej BlümelX100.00515089577350515050505050506061020510254500,000$
3Samuel BolducX100.00503595588261585050504949556163019540252500,000$
4Ryan JohnsonX100.00504740577050545050505050556062020520241500,000$
MOYENNE D’ÉQUIPE99.7667578764716671635360576253656606360
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
1Jakub Dobes (R)97.0073687079756664686565876264029670243750,000$
2Cayden Primeau100.0050656176615453555050596161077570264500,000$
Rayé
1Devon Levi100.0050646071505050505050505656034530241500,000$
MOYENNE D’ÉQUIPE99.005866647562575658555565606004759
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Patrick Lalime9090957070651CAN515500,000$


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
1Mackie SamoskevichFighting Pandas (OTT)C/RW7540539327255921432857218114.04%21168122.424812171170002855146.85%152400101.11220007131
2Connor BrownFighting Pandas (OTT)RW754941902540111133206920815.31%27143119.0861016391170001491449.31%14400041.26240001025
3Sean DurziFighting Pandas (OTT)D7517728928321010577119408614.29%106177723.704162043121000012741100.00%100001.0001101534
4Jeff SkinnerFighting Pandas (OTT)LW/RW75483078176072872869620916.78%15173323.1184124313300041625157.69%13000020.90020001061
5Alec MartinezFighting Pandas (OTT)D71145973302605482114257012.28%90178825.194610351070001107200%000000.8200000145
6Keegan KolesarFighting Pandas (OTT)RW75333568172751401092146316215.42%15128717.1725715470000803148.64%25700001.0613001556
7Ryker EvansFighting Pandas (OTT)D758596721640213718234599.76%108182824.392810291140000111000%000000.7300000148
8Cole KoepkeFighting Pandas (OTT)LW7523416424415127801934512311.92%12145619.42437221170000334147.95%14600000.8800010323
9Radek FaksaFighting Pandas (OTT)C75193958131801231311663912911.45%13132817.722351353000094261.80%136400000.8702000136
10Alexander HoltzFighting Pandas (OTT)RW75103040201005157127431017.87%11138518.471789910001270048.15%13500000.5800000030
11Beck MalenstynFighting Pandas (OTT)LW751521361944013592114339613.16%35150320.05000030000294248.01%35200000.4800000123
12Declan ChisholmFighting Pandas (OTT)D7512223444001306066183118.18%102133417.80112925000043200%100000.5100000311
13Samuel HeleniusFighting Pandas (OTT)C75161834435598125117287813.68%10101413.5300001000015057.61%109700000.6700010004
14Leo CarlssonOttawa SenatorsC/RW20916251000286174235912.16%647523.790338380000300152.85%61500001.0501000321
15Kaedan KorczakFighting Pandas (OTT)D322171982005725246198.33%3364620.22112944000065100%000000.5911000102
16Ivan IvanFighting Pandas (OTT)C/LW533912-5003203815217.89%958911.1310111000020046.77%6200000.4100000000
17Samuel BolducFighting Pandas (OTT)D290772401945170%1847016.2300002000029000%000000.3000000010
18Ben JonesFighting Pandas (OTT)C29000-400010010%0642.22000020000100036.36%110000000000000
Statistiques d’équipe totales ou en moyenne113431856988726039630145813382344650164013.57%6312180019.224075115292114200091007401453.49%583900160.81616122515150
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
1Jakub DobesFighting Pandas (OTT)75412370.8843.5242054224721270500.6005750310
2Cayden PrimeauFighting Pandas (OTT)50100.8903.58201001210900000053010
Statistiques d’équipe totales ou en moyenne80412470.8843.53440742259223605057553320


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 Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer 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
Alec MartinezFighting Pandas (OTT)D381987-07-26USANo210 Lbs6 ft1NoNoTrade2025-03-05NoNo22024-08-21FalseFalsePro & Farm700,000$70,000$8,167$No700,000$--------700,000$--------No--------Lien / Lien NHL
Alexander HoltzFighting Pandas (OTT)RW242002-01-23SWENo198 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Arshdeep BainsFighting Pandas (OTT)LW252001-01-09CANNo184 Lbs6 ft0NoNoFree AgentNoNo22025-07-23FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Beck MalenstynFighting Pandas (OTT)LW281998-02-04CANNo209 Lbs6 ft3NoNoAssign ManuallyNoNo22024-08-21FalseFalsePro & Farm700,000$70,000$8,167$No700,000$--------700,000$--------No--------Lien / Lien NHL
Ben JonesFighting Pandas (OTT)C271999-02-26CANNo187 Lbs6 ft0NoNoFree AgentNoNo42025-07-25FalseFalsePro & Farm500,000$50,000$5,833$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Cayden PrimeauFighting Pandas (OTT)G261999-08-11USANo205 Lbs6 ft3NoNoFree AgentNoNo42025-07-25FalseFalsePro & Farm500,000$50,000$5,833$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Cole KoepkeFighting Pandas (OTT)LW271998-05-17USANo207 Lbs6 ft1NoNoFree AgentNoNo12024-10-11FalseFalsePro & Farm500,000$50,000$5,833$No---------------------------Lien / Lien NHL
Connor BrownFighting Pandas (OTT)RW321994-01-14CANNo184 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Declan ChisholmFighting Pandas (OTT)D262000-01-12CANNo190 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Devon LeviFighting Pandas (OTT)G242001-12-27CANNo192 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$5,833$No---------------------------Lien / Lien NHL
Georgii MerkulovFighting Pandas (OTT)C252000-10-10RUSNo176 Lbs5 ft11NoNoFree AgentNoNo12024-09-09FalseFalsePro & Farm500,000$50,000$5,833$No---------------------------Lien / Lien NHL
Ivan IvanFighting Pandas (OTT)C/LW232002-08-20CZEYes190 Lbs6 ft0NoNoFree AgentNoNo22025-08-09FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Jakub DobesFighting Pandas (OTT)G242001-05-27CZEYes215 Lbs6 ft4NoNoFree AgentNoNo32025-08-07FalseFalsePro & Farm750,000$75,000$8,750$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien / Lien NHL
Jeff SkinnerFighting Pandas (OTT)LW/RW331992-05-16CANNo200 Lbs5 ft11NoNoTrade2024-08-25NoNo1FalseFalsePro & Farm2,000,000$200,000$23,333$No---------------------------Lien / Lien NHL
Kaedan KorczakFighting Pandas (OTT)D242002-01-18CANNo202 Lbs6 ft3NoNoTrade2025-08-04NoNo2FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Keegan KolesarFighting Pandas (OTT)RW281997-04-08CANNo216 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Mackie SamoskevichFighting Pandas (OTT)C/RW232002-11-15USAYes180 Lbs5 ft11NoNoTrade2025-08-04NoNo22024-08-10FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Matej BlümelFighting Pandas (OTT)RW252000-05-31CZENo205 Lbs6 ft0NoNoFree AgentNoNo42025-07-25FalseFalsePro & Farm500,000$50,000$5,833$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien
Radek FaksaFighting Pandas (OTT)C321994-01-09CZENo215 Lbs6 ft3NoNoN/ANoNo32024-08-19FalseFalsePro & Farm500,000$50,000$5,833$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Ryan JohnsonFighting Pandas (OTT)D242001-07-24USANo195 Lbs6 ft1NoNoFree AgentNoNo12024-09-09FalseFalsePro & Farm500,000$50,000$5,833$No---------------------------Lien / Lien NHL
Ryker EvansFighting Pandas (OTT)D242001-12-13CANNo195 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Samuel BolducFighting Pandas (OTT)D252000-12-09CANNo224 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$5,833$No500,000$--------500,000$--------No--------Lien / Lien NHL
Samuel HeleniusFighting Pandas (OTT)C232002-11-26USAYes201 Lbs6 ft6NoNoFree AgentNoNo32025-08-10FalseFalsePro & Farm750,000$75,000$8,750$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien / Lien NHL
Sean DurziFighting Pandas (OTT)D271998-10-21CANNo196 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm1,000,000$100,000$11,667$No---------------------------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2426.54199 Lbs6 ft12.13620,833$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jeff SkinnerAlexander Holtz40122
2Cole KoepkeMackie SamoskevichConnor Brown30122
3Beck MalenstynRadek FaksaKeegan Kolesar20122
4Ivan IvanSamuel HeleniusMackie Samoskevich10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alec MartinezRyker Evans40122
2Sean Durzi30122
3Declan ChisholmAlec Martinez20122
4Ryker EvansSean Durzi10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jeff SkinnerAlexander Holtz60122
2Cole KoepkeMackie SamoskevichConnor Brown40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alec MartinezRyker Evans60122
2Sean Durzi40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jeff Skinner60122
2Mackie SamoskevichCole Koepke40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alec MartinezRyker Evans60122
2Sean Durzi40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160122Alec MartinezRyker Evans60122
2Mackie Samoskevich40122Sean Durzi40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jeff Skinner60122
2Mackie SamoskevichCole Koepke40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alec MartinezRyker Evans60122
2Sean Durzi40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jeff SkinnerAlexander HoltzAlec MartinezRyker Evans
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jeff SkinnerConnor BrownAlec MartinezRyker Evans
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Mackie Samoskevich, Radek Faksa, Cole KoepkeMackie Samoskevich, Radek FaksaMackie Samoskevich
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Sean Durzi, , Declan ChisholmSean DurziSean Durzi,
Tirs de pénalité
, Connor Brown, Keegan Kolesar, Jeff Skinner, Mackie Samoskevich
Gardien
#1 : Jakub Dobes, #2 : Cayden Primeau


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
TotalDomicileVisiteur
# 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
1Aces3110010089-1211000006601000010023-130.50081523001181039978576978779033551585810330.00%4175.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
2Admirals4220000013112211000005502110000086240.5001323360011810399711076978779033862216616116.67%70100.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
3Americiens623001002530-53210000013121302001001218-650.4172545700011810399722476978779033251992013116637.50%10640.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
4Barons30100200812-41000010034-12010010058-320.333811190011810399791769787790335820856300.00%40100.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
5Barracuda210001009811000010067-11100000031230.7509172600118103997547697877903347168498337.50%4175.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
6Broncos632000102416811000000615522000101815380.667244064001181039971427697877903315542241174250.00%12375.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
7Bruins531010002017333000000137620101000710-380.800203454011181039971517697877903315430569614321.43%16287.50%01261235353.59%1245236352.69%741135854.57%197214211609499960507
8Butter Knives64200000282263210000016115321000001211180.667284876001181039972287697877903322873341179111.11%17382.35%01261235353.59%1245236352.69%741135854.57%197214211609499960507
9Canucks22000000963110000004311100000053241.000916250011810399755769787790334998224125.00%4250.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
10Firebirds3200010018992100010011741100000072550.83318345200118103997108769787790331022520698337.50%10190.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
11Griffins220000001156110000007251100000043141.000112132001181039975876978779033792313373133.33%4175.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
12Ice Bats1100000010280000000000011000000102821.0001018280011810399741769787790333057114250.00%110.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
13Lions220000001376110000006331100000074341.000132336001181039978276978779033701819495120.00%7271.43%01261235353.59%1245236352.69%741135854.57%197214211609499960507
14Lynx651000003321123210000020137330000001385100.833336396001181039971987697877903315241201037114.29%8275.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
15Marlies614000102025-541300000813-5201000101212040.3332037570111810399714876978779033171404010615640.00%18477.78%01261235353.59%1245236352.69%741135854.57%197214211609499960507
16Nordiks3110000118171201000011214-21100000063330.50018314900118103997131769787790331454119778450.00%60100.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
17Quacken21100000743110000006151010000013-220.500712190011810399747769787790334178446233.33%30100.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
18Roadrunners623000011317-43110000178-13120000069-350.417132235001181039971727697877903316742421211100.00%20575.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
19Tomahawks20100100711-41000010034-11010000047-310.2507101700118103997827697877903379208446116.67%40100.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
20Wombats33000000188101100000053222000000135861.000183351001181039978276978779033104261061800.00%40100.00%01261235353.59%1245236352.69%741135854.57%197214211609499960507
21Wranglers2110000011831010000036-31100000082620.500111930001181039977476978779033832812462150.00%6183.33%01261235353.59%1245236352.69%741135854.57%197214211609499960507
Total753924017223232655837201100402160130303819130132016313528930.62032357289502118103997236376978779033230664240014751574226.75%1693579.29%01261235353.59%1245236352.69%741135854.57%197214211609499960507
_Since Last GM Reset753924017223232655837201100402160130303819130132016313528930.62032357289502118103997236376978779033230664240014751574226.75%1693579.29%01261235353.59%1245236352.69%741135854.57%197214211609499960507
_Vs Conference512718012212121763625158001011048024261210011201089612630.618212379591021181039971563769787790331570440282982982323.47%1222678.69%01261235353.59%1245236352.69%741135854.57%197214211609499960507
_Vs Division291511011101261151116106000007056141355011105659-3350.6031262273530211810399794976978779033956283170553611727.87%691775.36%01261235353.59%1245236352.69%741135854.57%197214211609499960507

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7593L232357289523632306642400147502
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7539241722323265
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3720110402160130
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3819131320163135
Derniers 10 matchs
WLOTWOTL SOWSOL
450100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1574226.75%1693579.29%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
76978779033118103997
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
1261235353.59%1245236352.69%741135854.57%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
197214211609499960507


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
27Marlies6Fighting Pandas1LSommaire du match
623Fighting Pandas3Americiens4LSommaire du match
834Americiens3Fighting Pandas5WSommaire du match
938Fighting Pandas2Broncos1WSommaire du match
1254Bruins4Fighting Pandas5WSommaire du match
1361Fighting Pandas3Broncos6LSommaire du match
1674Butter Knives2Fighting Pandas7WSommaire du match
1884Fighting Pandas5Bruins4WXSommaire du match
2098Lynx3Fighting Pandas7WSommaire du match
21105Fighting Pandas0Roadrunners3LSommaire du match
25119Roadrunners1Fighting Pandas3WSommaire du match
26125Fighting Pandas2Lynx1WSommaire du match
29138Fighting Pandas3Broncos5LSommaire du match
31147Marlies3Fighting Pandas0LSommaire du match
32154Fighting Pandas8Marlies7WXXSommaire du match
35169Firebirds2Fighting Pandas7WSommaire du match
39184Tomahawks4Fighting Pandas3LXSommaire du match
41193Fighting Pandas3Barracuda1WSommaire du match
43201Fighting Pandas3Butter Knives5LSommaire du match
45212Nordiks7Fighting Pandas6LXXSommaire du match
48226Fighting Pandas7Broncos1WSommaire du match
49234Nordiks7Fighting Pandas6LSommaire du match
51249Barracuda7Fighting Pandas6LXSommaire du match
53260Fighting Pandas7Lions4WSommaire du match
55271Fighting Pandas8Wranglers2WSommaire du match
56278Admirals4Fighting Pandas3LSommaire du match
59293Firebirds5Fighting Pandas4LXSommaire du match
61305Fighting Pandas2Roadrunners4LSommaire du match
63315Wranglers6Fighting Pandas3LSommaire du match
66325Fighting Pandas4Griffins3WSommaire du match
68337Lions3Fighting Pandas6WSommaire du match
70348Fighting Pandas2Aces3LXSommaire du match
72358Fighting Pandas7Wombats1WSommaire du match
74365Marlies4Fighting Pandas3LSommaire du match
76380Barons4Fighting Pandas3LXSommaire du match
78388Fighting Pandas10Ice Bats2WSommaire du match
80401Griffins2Fighting Pandas7WSommaire du match
82412Fighting Pandas4Roadrunners2WSommaire du match
84424Canucks3Fighting Pandas4WSommaire du match
85431Fighting Pandas1Quacken3LSommaire du match
88442Fighting Pandas5Butter Knives3WSommaire du match
90451Butter Knives3Fighting Pandas4WSommaire du match
92461Fighting Pandas3Barons5LSommaire du match
95471Roadrunners3Fighting Pandas2LXXSommaire du match
97482Fighting Pandas6Nordiks3WSommaire du match
99492Fighting Pandas6Admirals3WSommaire du match
100501Bruins0Fighting Pandas3WSommaire du match
102512Fighting Pandas5Lynx3WSommaire du match
104523Butter Knives6Fighting Pandas5LSommaire du match
107535Fighting Pandas2Admirals3LSommaire du match
108544Roadrunners4Fighting Pandas2LSommaire du match
110555Fighting Pandas6Wombats4WSommaire du match
112567Broncos1Fighting Pandas6WSommaire du match
114577Fighting Pandas3Broncos2WXXSommaire du match
116589Bruins3Fighting Pandas5WSommaire du match
119598Fighting Pandas4Butter Knives3WSommaire du match
120608Americiens3Fighting Pandas5WSommaire du match
122621Fighting Pandas6Lynx4WSommaire du match
124632Lynx3Fighting Pandas7WSommaire du match
126643Fighting Pandas6Americiens7LXSommaire du match
128652Marlies0Fighting Pandas4WSommaire du match
130657Fighting Pandas5Canucks3WSommaire du match
132673Quacken1Fighting Pandas6WSommaire du match
133677Fighting Pandas4Tomahawks7LSommaire du match
135686Fighting Pandas3Americiens7LSommaire du match
136692Fighting Pandas2Barons3LXSommaire du match
138703Americiens6Fighting Pandas3LSommaire du match
141719Fighting Pandas7Firebirds2WSommaire du match
143725Wombats3Fighting Pandas5WSommaire du match
146743Aces3Fighting Pandas0LSommaire du match
147748Fighting Pandas2Bruins6LSommaire du match
150765Admirals1Fighting Pandas2WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
154785Aces3Fighting Pandas6WSommaire du match
158804Lynx7Fighting Pandas6LSommaire du match
159809Fighting Pandas4Marlies5LSommaire du match
162825Wombats-Fighting Pandas-
164834Fighting Pandas-Bruins-
167846Fighting Pandas-Marlies-
168854Fighting Pandas-Firebirds-
169858Ice Bats-Fighting Pandas-
173875Broncos-Fighting Pandas-
177892Ice Bats-Fighting Pandas-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4020
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
4 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,774,538$ 1,490,000$ 1,490,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,490,000$ 1,332,878$ 24 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 21 11,056$ 232,176$




Fighting Pandas 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

Fighting Pandas 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

Fighting Pandas 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

Fighting Pandas 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

Fighting Pandas 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