Connexion

Fighting Pandas
GP: 54 | W: 32 | L: 16 | OTL: 6 | P: 70
GF: 232 | GA: 199 | PP%: 28.46% | PK%: 75.44%
DG: Hunter Jones | Morale : 62 | Moyenne d’équipe : 61
Prochains matchs #617 vs Lynx
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Centre de jeu
Fighting Pandas
32-16-6, 70pts
4
FINAL
8 Lynx
37-9-7, 81pts
Team Stats
W1SéquenceL1
17-8-3Fiche domicile22-4-2
15-8-3Fiche domicile15-5-5
7-3-0Derniers 10 matchs8-2-0
4.30Buts par match 4.75
3.69Buts contre par match 3.53
28.46%Pourcentage en avantage numérique20.45%
75.44%Pourcentage en désavantage numérique77.34%
Barracuda
26-24-5, 57pts
2
FINAL
3 Fighting Pandas
32-16-6, 70pts
Team Stats
W1SéquenceW1
14-11-3Fiche domicile17-8-3
12-13-2Fiche domicile15-8-3
4-4-2Derniers 10 matchs7-3-0
4.93Buts par match 4.30
5.13Buts contre par match 3.69
23.33%Pourcentage en avantage numérique28.46%
71.01%Pourcentage en désavantage numérique75.44%
Fighting Pandas
32-16-6, 70pts
Jour 117
Lynx
37-9-7, 81pts
Statistiques d’équipe
W1SéquenceL1
17-8-3Fiche domicile22-4-2
15-8-3Fiche visiteur15-5-5
7-3-010 derniers matchs8-2-0
4.30Buts par match 4.75
3.69Buts contre par match 4.75
28.46%Pourcentage en avantage numérique20.45%
75.44%Pourcentage en désavantage numérique77.34%
Broncos
26-28-1, 53pts
Jour 118
Fighting Pandas
32-16-6, 70pts
Statistiques d’équipe
W3SéquenceW1
14-12-1Fiche domicile17-8-3
12-16-0Fiche visiteur15-8-3
6-4-010 derniers matchs7-3-0
3.84Buts par match 4.30
4.53Buts contre par match 4.30
16.80%Pourcentage en avantage numérique28.46%
73.76%Pourcentage en désavantage numérique75.44%
Fighting Pandas
32-16-6, 70pts
Jour 120
Nordiks
28-26-2, 58pts
Statistiques d’équipe
W1SéquenceW1
17-8-3Fiche domicile14-11-2
15-8-3Fiche visiteur14-15-0
7-3-010 derniers matchs4-6-0
4.30Buts par match 5.55
3.69Buts contre par match 5.55
28.46%Pourcentage en avantage numérique23.53%
75.44%Pourcentage en désavantage numérique68.94%
Meneurs d'équipe
Alexander HoltzButs
Alexander Holtz
41
Passes
Ryan Johnson
57
Alexander HoltzPoints
Alexander Holtz
68
Alexander HoltzPlus/Moins
Alexander Holtz
27
Cayden PrimeauVictoires
Cayden Primeau
29
Cayden PrimeauPourcentage d’arrêts
Cayden Primeau
0.892

Statistiques d’équipe
Buts pour
232
4.30 GFG
Tirs pour
1845
34.17 Avg
Pourcentage en avantage numérique
28.5%
37 GF
Début de zone offensive
39.1%
Buts contre
199
3.69 GAA
Tirs contre
1869
34.61 Avg
Pourcentage en désavantage numérique
75.4%%
28 GA
Début de la zone défensive
40.3%
Informations de l'équipe

Directeur généralHunter Jones
EntraîneurPatrick Lalime
DivisionAtlantic
ConférenceEastern Conference
CapitaineConnor Brown
Assistant #1Alexander Holtz
Assistant #2Leo Carlsson


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro22
Équipe Mineure20
Limite contact 42 / 50
Espoirs23


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
1Leo Carlsson (R) (A)XXX100.00625785757082737655707063875157078660203500,000$
2Radek FaksaXXX100.0074578569777185727264568050737507566X0314500,000$
3Alexander Holtz (A)XX100.0062559272716991795064715851586108465X0233500,000$
4Keegan KolesarX100.00896884687768887350646063506767083640273500,000$
5Connor Brown (C)XX100.0059549467657282665062527050737308162X0313500,000$
6Cole KoepkeX100.00605090527350505650504949506666074520262500,000$
7Aku Raty (R)X100.0050358957595051565050505050586806951X0233500,000$
8Arshdeep BainsX100.00506064576552525050505050505859069510241500,000$
9Ruslan Iskhakov (R)X100.0050508957585052505050505050606905551X0243500,000$
10Georgii MerkulovX100.00503589576150515050505049505859042500242500,000$
11Luke SchennX100.0086748562806878645055507355807805566X03512,500,000$
12Bowen ByramX100.00726368656877877050656371566063055650231500,000$
13Declan Chisholm (R)X100.00585787727068617050656168566466087630253500,000$
14Ryan JohnsonX100.00545885637166646950645469556264083610232500,000$
15Samuel BolducX100.0073589062806260625054526555616305761X0243500,000$
16Simon Edvinsson (R)X100.00705886567755565950535465565963084580212500,000$
Rayé
1Michael McCarronXX100.00816878698472827673626571517171020670291500,000$
2Shane PintoX100.00695782747282667973746967516065020670242500,000$
3Ryker Evans (R)X100.0075607570687264685067546755606206063X0233500,000$
4Vincent Iorio (R)X100.00493594587350515050505049555761045520223500,000$
MOYENNE D’ÉQUIPE100.0065558564716467655459576254636606460
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
1Cayden Primeau100.0074717277736870736962716468027690251500,000$
2Devon Levi100.0072717171737170727057545761084670232500,000$
Rayé
MOYENNE D’ÉQUIPE100.007371727473707073706063616505668
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Patrick Lalime9090957070651CAN506500,000$


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
1Alexander HoltzFighting Pandas (OTT)LW/RW54412768274019962356217417.45%1189916.6621310290001136252.46%6100031.5112000685
2Ryan JohnsonFighting Pandas (OTT)D54957667100708111152858.11%92112120.7778154995000173310%000001.1801000735
3Declan ChisholmFighting Pandas (OTT)D5419446391606567146619113.01%88127023.528816621050111883050.00%600020.9901000654
4Keegan KolesarFighting Pandas (OTT)RW5423335627300176761886414812.23%1790116.6910110280001151056.41%7800011.2401000758
5Ryker EvansFighting Pandas (OTT)D4211314253151444874255614.86%7398423.4435836720000600357.14%700000.8501001465
6Connor BrownFighting Pandas (OTT)LW/RW5418183661353284160509911.25%1462811.6400001000022150.00%2600001.1501000353
7Simon EdvinssonFighting Pandas (OTT)D5482634536101124067244511.94%6583915.54123715000020100%000000.8111200114
8Leo CarlssonFighting Pandas (OTT)C/LW/RW679161220101635112120.00%414624.47011412000031162.22%4500012.1801000212
9Cole PerfettiOttawa SenatorsC/LW/RW1112416124082585254914.12%224422.2210111210000152045.56%9000121.3101000211
10Samuel BolducFighting Pandas (OTT)D2459144200831837172213.51%3347219.690221639000032100%000000.5901000311
11Vincent IorioFighting Pandas (OTT)D332121404010181741211.76%2251615.6601115000021000%000000.5401000100
12Cole KoepkeFighting Pandas (OTT)LW52391210025223210339.38%22775.33000010000110052.38%2100000.8701000010
13Radek FaksaFighting Pandas (OTT)C/LW/RW62796001714211199.52%210517.55000210000041059.29%14000001.7101000012
14Aku RatyFighting Pandas (OTT)RW7022-340019140%011115.9600002000000016.67%600000.3600000000
15Georgii MerkulovFighting Pandas (OTT)C71122000741025.00%013118.77011112000000042.36%14400000.3000000000
16Arshdeep BainsFighting Pandas (OTT)LW7000-200211140%0476.7900005000010040.00%100000000000000
Statistiques d’équipe totales ou en moyenne51916128945011817420773614122241985213.18%425869816.76232952209459011436321851.26%63400191.03214201423840
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
1Cayden PrimeauFighting Pandas (OTT)52291250.8923.6428344017215930020.80010520130
2Devon LeviFighting Pandas (OTT)103410.9123.3742700242740001.0004254000
Statistiques d’équipe totales ou en moyenne62321660.8953.613262401961867002145454130


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
Aku RatyFighting Pandas (OTT)RW232001-07-05FINYes170 Lbs6 ft0NoYesN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Alexander HoltzFighting Pandas (OTT)LW/RW232002-01-23SWENo195 Lbs6 ft0NoYesN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Arshdeep BainsFighting Pandas (OTT)LW242001-01-09CANNo184 Lbs6 ft0NoNoFree AgentNoNo12024-09-09FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Bowen ByramFighting Pandas (OTT)D232001-06-13CANNo190 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Cayden PrimeauFighting Pandas (OTT)G251999-08-11USANo207 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Cole KoepkeFighting Pandas (OTT)LW261998-05-17USANo203 Lbs6 ft1NoNoFree AgentNoNo22024-10-11FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------
Connor BrownFighting Pandas (OTT)LW/RW311994-01-14CANNo184 Lbs6 ft0NoYesN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Declan ChisholmFighting Pandas (OTT)D252000-01-12CANYes190 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Devon LeviFighting Pandas (OTT)G232001-12-27CANNo192 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
Georgii MerkulovFighting Pandas (OTT)C242000-10-10RUSNo176 Lbs5 ft11NoNoFree AgentNoNo22024-09-09FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------
Keegan KolesarFighting Pandas (OTT)RW271997-04-08CANNo216 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Leo CarlssonFighting Pandas (OTT)C/LW/RW202004-12-26SWEYes194 Lbs6 ft3NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Luke SchennFighting Pandas (OTT)D351989-11-02CANNo225 Lbs6 ft2NoYesN/ANoNo1FalseFalsePro & Farm2,500,000$250,000$85,714$No---------------------------Lien NHL
Michael McCarronFighting Pandas (OTT)C/RW291995-03-07USANo232 Lbs6 ft6NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Radek FaksaFighting Pandas (OTT)C/LW/RW311994-01-09CZENo215 Lbs6 ft3NoYesN/ANoNo42024-08-19FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien NHL
Ruslan IskhakovFighting Pandas (OTT)C242000-07-22RUSYes170 Lbs5 ft8NoYesN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Ryan JohnsonFighting Pandas (OTT)D232001-07-24USANo195 Lbs6 ft1NoNoFree AgentNoNo22024-09-09FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------
Ryker EvansFighting Pandas (OTT)D232001-12-13CANYes189 Lbs5 ft11NoYesN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Samuel BolducFighting Pandas (OTT)D242000-12-09CANNo220 Lbs6 ft4NoYesN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Shane PintoFighting Pandas (OTT)C242000-11-12USANo201 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
Simon EdvinssonFighting Pandas (OTT)D212003-02-05SWEYes209 Lbs6 ft6NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
Vincent IorioFighting Pandas (OTT)D222002-11-14CANYes200 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2225.00198 Lbs6 ft22.32590,909$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
140122
2Alexander HoltzKeegan Kolesar30122
3Connor Brown20122
4Cole Koepke10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Declan Chisholm40122
2Ryan Johnson30122
3Simon Edvinsson20122
4Declan Chisholm10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
160122
2Alexander HoltzKeegan Kolesar40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Declan Chisholm60122
2Ryan Johnson40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
160122
2Alexander Holtz40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Declan Chisholm60122
2Ryan Johnson40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160122Declan Chisholm60122
240122Ryan Johnson40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
160122
2Alexander Holtz40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Declan Chisholm60122
2Ryan Johnson40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Declan Chisholm
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Declan Chisholm
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Connor Brown, Cole Koepke, Connor BrownCole Koepke
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Simon Edvinsson, , Simon Edvinsson,
Tirs de pénalité
, , , Alexander Holtz, Keegan Kolesar
Gardien
#1 : Cayden Primeau, #2 : Devon Levi
Lignes d’attaque personnalisées en prolongation
, , , Alexander Holtz, Keegan Kolesar, Connor Brown, Connor Brown, Cole Koepke, , ,
Lignes de défense personnalisées en prolongation
, Declan Chisholm, , Ryan Johnson, Simon Edvinsson


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
1Aces11000000211110000002110000000000021.00024600757578522575629631242072174250.00%10100.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
2Americiens5220100022193220000001156302010001114-360.60022406200757578519657562963124211553011510110.00%13284.62%0831176447.11%848181946.62%46393449.57%139810201204356666343
3Barons321000001192110000004312110000076140.66711213200757578510157562963124702412635240.00%6266.67%0831176447.11%848181946.62%46393449.57%139810201204356666343
4Barracuda3210000013112220000009541010000046-240.667132235107575785121575629631241053115616233.33%30100.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
5Broncos3210000015871010000023-122000000135840.6671528430075757858457562963124792012494250.00%5180.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
6Bruins211000004401010000023-11100000021120.5004711007575785525756296312448134445120.00%2150.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
7Butter Knives63300000282533210000016124312000001213-160.50028497710757578522257562963124267803415917635.29%17476.47%2831176447.11%848181946.62%46393449.57%139810201204356666343
8Canucks1000010034-1000000000001000010034-110.5003690075757852657562963124237414200.00%20100.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
9Firebirds32100000171252110000011741100000065140.667173249007575785126575629631241272919819111.11%7271.43%0831176447.11%848181946.62%46393449.57%139810201204356666343
10Griffins311001001516-111000000523201001001014-430.5001528430075757851245756296312413641148110330.00%6350.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
11Ice Bats210001001091110000005321000010056-130.750101828007575785695756296312490261254300.00%60100.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
12Lynx421001001417-32100010066021100000811-350.6251426400075757851425756296312411931166915320.00%8362.50%0831176447.11%848181946.62%46393449.57%139810201204356666343
13Marlies6410100024177321000001192320010001385100.83324467000757578515857562963124168462211918738.89%11281.82%0831176447.11%848181946.62%46393449.57%139810201204356666343
14Nordiks1000000167-11000000167-10000000000010.50061117007575785405756296312442237262150.00%4250.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
15Punishers1010000046-21010000046-20000000000000.00048120075757852857562963124274419000%220.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
16Roadrunners6400011027189420001101813522000000954110.9172746730075757851815756296312418851351207114.29%14378.57%0831176447.11%848181946.62%46393449.57%139810201204356666343
17Tomahawks1010000046-21010000046-20000000000000.000481200757578542575629631244119620400.00%30100.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
18Wombats11000000413000000000001100000041321.0004610007575785305756296312426104144250.00%2150.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
19Wranglers201010009901010000034-11000100065120.50091726007575785815756296312482234535360.00%20100.00%0831176447.11%848181946.62%46393449.57%139810201204356666343
Total54281603511232199332816800211119952426128033001131049700.648232423655207575785184557562963124186954025611781303728.46%1142875.44%2831176447.11%848181946.62%46393449.57%139810201204356666343
_Since Last GM Reset54281603511232199332816800211119952426128033001131049700.648232423655207575785184557562963124186954025611781303728.46%1142875.44%2831176447.11%848181946.62%46393449.57%139810201204356666343
_Vs Conference362110022101551213418105002107758191811502000786315500.6941552804351075757851191575629631241233335176770892426.97%791975.95%2831176447.11%848181946.62%46393449.57%139810201204356666343
_Vs Division23128021009282101173001004635111255020004647-1290.6309216826010757578577057562963124813225106506651827.69%511276.47%2831176447.11%848181946.62%46393449.57%139810201204356666343

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5470W123242365518451869540256117820
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5428163511232199
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
28168021111995
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
261283300113104
Derniers 10 matchs
WLOTWOTL SOWSOL
730000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1303728.46%1142875.44%2
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
575629631247575785
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
831176447.11%848181946.62%46393449.57%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
139810201204356666343


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
12Fighting Pandas6Roadrunners3WSommaire du match
213Roadrunners4Fighting Pandas5WXXSommaire du match
528Fighting Pandas2Bruins1WSommaire du match
735Fighting Pandas4Lynx3WSommaire du match
843Americiens3Fighting Pandas5WSommaire du match
1059Americiens2Fighting Pandas6WSommaire du match
1269Fighting Pandas5Marlies3WSommaire du match
1480Bruins3Fighting Pandas2LSommaire du match
1691Lynx3Fighting Pandas4WSommaire du match
1797Fighting Pandas5Americiens7LSommaire du match
21118Butter Knives3Fighting Pandas1LSommaire du match
24134Roadrunners2Fighting Pandas4WSommaire du match
25143Fighting Pandas4Butter Knives5LSommaire du match
27151Fighting Pandas3Roadrunners2WSommaire du match
29160Fighting Pandas4Wombats1WSommaire du match
32172Marlies1Fighting Pandas3WSommaire du match
34180Fighting Pandas3Marlies2WXSommaire du match
36191Firebirds6Fighting Pandas4LSommaire du match
39204Nordiks7Fighting Pandas6LXXSommaire du match
41215Fighting Pandas6Firebirds5WSommaire du match
44226Wranglers4Fighting Pandas3LSommaire du match
47238Fighting Pandas3Canucks4LXSommaire du match
49250Broncos3Fighting Pandas2LSommaire du match
51265Fighting Pandas4Barracuda6LSommaire du match
53273Punishers6Fighting Pandas4LSommaire du match
54284Fighting Pandas4Americiens3WXSommaire du match
56294Fighting Pandas3Griffins6LSommaire du match
57303Lynx3Fighting Pandas2LXSommaire du match
60316Marlies6Fighting Pandas5LSommaire du match
63327Fighting Pandas6Broncos4WSommaire du match
65339Butter Knives3Fighting Pandas6WSommaire du match
66348Fighting Pandas2Americiens4LSommaire du match
70361Griffins2Fighting Pandas5WSommaire du match
73378Barons3Fighting Pandas4WSommaire du match
77397Fighting Pandas6Wranglers5WXSommaire du match
78403Aces1Fighting Pandas2WSommaire du match
81420Barracuda3Fighting Pandas6WSommaire du match
84434Fighting Pandas7Griffins8LXSommaire du match
86441Roadrunners4Fighting Pandas3LXSommaire du match
88452Fighting Pandas5Ice Bats6LXSommaire du match
89463Roadrunners3Fighting Pandas6WSommaire du match
91476Fighting Pandas3Butter Knives2WSommaire du match
93485Ice Bats3Fighting Pandas5WSommaire du match
95493Fighting Pandas4Barons5LSommaire du match
96506Butter Knives6Fighting Pandas9WSommaire du match
99515Fighting Pandas5Marlies3WSommaire du match
101530Tomahawks6Fighting Pandas4LSommaire du match
102537Fighting Pandas7Broncos1WSommaire du match
105551Marlies2Fighting Pandas3WSommaire du match
107559Fighting Pandas3Barons1WSommaire du match
108568Fighting Pandas5Butter Knives6LSommaire du match
110579Firebirds1Fighting Pandas7WSommaire du match
113594Fighting Pandas4Lynx8LSommaire du match
114600Barracuda2Fighting Pandas3WSommaire du match
117617Fighting Pandas-Lynx-
118621Broncos-Fighting Pandas-
120635Fighting Pandas-Nordiks-
122643Wombats-Fighting Pandas-
124653Fighting Pandas-Punishers-
127664Canucks-Fighting Pandas-
129674Fighting Pandas-Firebirds-
130683Fighting Pandas-Tomahawks-
132694Lions-Fighting Pandas-
135706Fighting Pandas-Aces-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
137712Lynx-Fighting Pandas-
138721Fighting Pandas-Wombats-
141735Wombats-Fighting Pandas-
143742Fighting Pandas-Admirals-
145755Fighting Pandas-Admirals-
146760Ice Bats-Fighting Pandas-
150780Bruins-Fighting Pandas-
153792Fighting Pandas-Wombats-
155800Bruins-Fighting Pandas-
158818Admirals-Fighting Pandas-
160827Fighting Pandas-Roadrunners-
162842Americiens-Fighting Pandas-
165860Americiens-Fighting Pandas-
167867Fighting Pandas-Lions-
168871Fighting Pandas-Roadrunners-
169875Fighting Pandas-Bruins-
172888Admirals-Fighting Pandas-
173897Fighting Pandas-Bruins-



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
13 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,322,285$ 1,300,000$ 1,300,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,300,000$ 993,727$ 22 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 60 10,286$ 617,160$




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