Connexion

Lynx
GP: 53 | W: 37 | L: 9 | OTL: 7 | P: 81
GF: 252 | GA: 187 | PP%: 20.45% | PK%: 77.34%
DG: Chris Ralph | Morale : 78 | Moyenne d’équipe : 59
Prochains matchs #617 vs Fighting Pandas
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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%
Lynx
37-9-7, 81pts
4
FINAL
5 Barracuda
26-24-5, 57pts
Team Stats
L1SéquenceW1
22-4-2Fiche domicile14-11-3
15-5-5Fiche domicile12-13-2
8-2-0Derniers 10 matchs4-4-2
4.75Buts par match 4.93
3.53Buts contre par match 5.13
20.45%Pourcentage en avantage numérique23.33%
77.34%Pourcentage en désavantage numérique71.01%
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%
Lynx
37-9-7, 81pts
Jour 118
Tomahawks
31-19-3, 65pts
Statistiques d’équipe
L1SéquenceW3
22-4-2Fiche domicile13-13-2
15-5-5Fiche visiteur18-6-1
8-2-010 derniers matchs7-3-0
4.75Buts par match 5.06
3.53Buts contre par match 5.06
20.45%Pourcentage en avantage numérique17.46%
77.34%Pourcentage en désavantage numérique78.29%
Lynx
37-9-7, 81pts
Jour 121
Lions
16-34-6, 38pts
Statistiques d’équipe
L1SéquenceOTL1
22-4-2Fiche domicile8-16-3
15-5-5Fiche visiteur8-18-3
8-2-010 derniers matchs3-5-2
4.75Buts par match 3.45
3.53Buts contre par match 3.45
20.45%Pourcentage en avantage numérique26.40%
77.34%Pourcentage en désavantage numérique78.76%
Meneurs d'équipe
Logan CooleyButs
Logan Cooley
41
Simon NemecPasses
Simon Nemec
49
Connor ZaryPoints
Connor Zary
84
Logan CooleyPlus/Moins
Logan Cooley
42
Jonas JohanssonVictoires
Jonas Johansson
36
Jonas JohanssonPourcentage d’arrêts
Jonas Johansson
0.897

Statistiques d’équipe
Buts pour
252
4.75 GFG
Tirs pour
1885
35.57 Avg
Pourcentage en avantage numérique
20.5%
27 GF
Début de zone offensive
41.5%
Buts contre
187
3.53 GAA
Tirs contre
1796
33.89 Avg
Pourcentage en désavantage numérique
77.3%%
29 GA
Début de la zone défensive
37.6%
Informations de l'équipe

Directeur généralChris Ralph
EntraîneurMats Sundin
DivisionAtlantic
ConférenceEastern Conference
CapitaineLogan Cooley
Assistant #1Simon Nemec
Assistant #2Connor Zary


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure19
Limite contact 46 / 50
Espoirs48


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
1Connor Zary (R) (A)XX99.00605683736477788158757364586164088670233500,000$
2Logan Cooley (R) (C)XXX100.00625589796278937857727462515560089670203500,000$
3Michael McLeodX100.00795688696876667789677071516869089670261500,000$
4Martin PospisilX100.00876552706271777657706464506365089650251500,000$
5Brett HowdenX100.00725784687272837462646271506668088650261500,000$
6Anthony BeauvillierX100.00665493726373757864685960506968089640272500,000$
7Trevor ZegrasXX100.006159726966786175547066596060630696302321,500,000$
8Mitchell ChaffeeX100.00805593676867587550596060506564083610271500,000$
9Adam RuzickaX100.00575788697866636962625258506565086600253500,000$
10Bo GroulxX100.00805875647170655861575066506163045590241500,000$
11Kirby DachXX100.00493590598050525450314948516070085500241500,000$
12Simon Nemec (R) (A)X100.00596377676976777250705472555761089650203500,000$
13Oliver KylingtonX100.00645881616569626850605770566970089620271500,000$
14Uvis BalinskisX100.00715884597064586350555366557171089610281500,000$
15Jack St. IvanyX100.00715792557149545750525068556669084580251500,000$
16Lane Hutson (R)X100.00503595585452565550605050575567044520203500,000$
17Yan KuznetsovX100.00503594587750515050495050555962060520221500,000$
Rayé
1Alex TurcotteX100.00525685646658546957565055506061036560233500,000$
2Shane WrightX100.00505089536855535871506350515563019540212500,000$
3Brian HalonenX100.00503589577450505050505050506262020510261500,000$
4Bradly Nadeau (R)X100.00503589575555545050505050505154020500193500,000$
5Victor SoderstromX100.00503594576550535050505050556062020520233500,000$
MOYENNE D’ÉQUIPE99.9562518564686463655659576053626506759
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
1Jonas Johansson98.0069737181746870717050507171081680291500,000$
2Devin Cooley100.0050636075575050505050506565089560271500,000$
Rayé
1Yaniv Perets100.0067606669506650505050506062024560241500,000$
2Jesper Wallstedt (R)100.0050615978525050505050505454036540223500,000$
3Matt Villalta100.0050615973505050505050506161024540251500,000$
MOYENNE D’ÉQUIPE99.605764637557575454545050626305158
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mats Sundin8595959060601SWE536500,000$


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
1Connor ZaryLynx (QUE)C/LW533648843840591222436917914.81%15131724.866393512001111264155.43%113300001.2703000748
2Logan CooleyLynx (QUE)C/LW/RW534140814216055882676017915.36%9111220.993363012110111210243.88%9800031.4603000752
3Anthony BeauvillierLynx (QUE)LW53323870144027892135815715.02%11106220.0435822990002567255.68%8800011.3212000763
4Martin PospisilLynx (QUE)C5331346526500162812024113215.35%1392417.452793697000064257.55%60300011.4100000587
5Simon NemecLynx (QUE)D53104959372610716481285312.35%86119422.54448371100110100200%000000.9900110223
6Trevor ZegrasLynx (QUE)C/LW501539542319593521503811110.00%696119.2407718910001250056.91%18100001.1200100423
7Brett HowdenLynx (QUE)C4628235112100521341715213216.37%1582717.991123251012541258.71%99300101.2300000355
8Luke HughesQuebec NordiquesD28631371610034293982715.38%4268524.473361466000154200%000101.0800000030
9Michael McLeodLynx (QUE)C221318312380315880275416.25%340418.381348250113502165.52%55100001.5300000231
10Uvis BalinskisLynx (QUE)D53623295400973047153712.77%6597418.382351260000060100%000000.6000000120
11Oliver KylingtonLynx (QUE)D536222828260944158254610.34%93117322.131342497022197100%000100.4800000003
12Mitchell ChaffeeLynx (QUE)RW3312112312203236102256111.76%954416.4900000000081052.63%3800000.8500000220
13Adam RuzickaLynx (QUE)C5341620-32017597327555.48%659011.14011212000050055.49%63800000.6800000000
14Jack St. IvanyLynx (QUE)D53217191227582302118209.52%6484315.9200008000043110%000000.4500001102
15Bo GroulxLynx (QUE)C1525713201171922510.53%223115.4100000000001043.75%1600000.6100000001
16Yan KuznetsovLynx (QUE)D2913415809372414.29%2145615.750001100005000%000000.1800000001
17Alex TurcotteLynx (QUE)C28123-400111728283.57%32529.02000011013440056.07%10700000.2400000000
18Lane HutsonLynx (QUE)D250221000858040%1746818.75000349000014000%000000.0900000000
19Kirby DachLynx (QUE)C/RW53011-3009413270%24358.2100014000000062.96%2700000.0500000000
20Shane WrightLynx (QUE)C7000000000000%010.21000000000000100.00%10000000000000
Statistiques d’équipe totales ou en moyenne813246422668316254209549491822499129113.50%4821446217.7926436924699435815766371157.51%447400350.9218211414239
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
1Jonas JohanssonLynx (QUE)5336860.8973.45309412117817260400.3758530221
2Devin CooleyLynx (QUE)31110.9142.981210067000000053000
Statistiques d’équipe totales ou en moyenne5637970.8983.433215121184179604085353221


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
Adam RuzickaLynx (QUE)C251999-05-11SVKNo215 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Alex TurcotteLynx (QUE)C232001-02-26USANo185 Lbs5 ft11NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Anthony BeauvillierLynx (QUE)LW271997-06-08CANNo180 Lbs5 ft11NoNoTrade2024-08-22NoNo2FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
Bo GroulxLynx (QUE)C242000-02-06CANNo198 Lbs6 ft2NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Bradly NadeauLynx (QUE)LW192005-05-05CANYes161 Lbs5 ft10NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Brett HowdenLynx (QUE)C261998-03-29CANNo200 Lbs6 ft2NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Brian HalonenLynx (QUE)LW261999-01-11USANo207 Lbs6 ft0NoNoTrade2024-10-07NoNo12024-10-07FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Connor ZaryLynx (QUE)C/LW232001-09-25CANYes178 Lbs6 ft0NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Devin CooleyLynx (QUE)G271997-05-25USANo192 Lbs6 ft5NoNoFree AgentNoNo12024-09-03FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Jack St. IvanyLynx (QUE)D251999-07-22USANo198 Lbs6 ft3NoNoTrade2024-10-07NoNo12024-10-07FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Jesper WallstedtLynx (QUE)G222002-11-14SWEYes214 Lbs6 ft3NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Jonas JohanssonLynx (QUE)G291995-09-19SWENo219 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Kirby DachLynx (QUE)C/RW242001-01-21CANNo217 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Lane HutsonLynx (QUE)D202004-02-14USAYes158 Lbs5 ft9NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Logan CooleyLynx (QUE)C/LW/RW202004-05-04USAYes174 Lbs5 ft10NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Martin PospisilLynx (QUE)C251999-11-19SVKNo173 Lbs6 ft2NoNoFree AgentNoNo12024-09-03FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Matt VillaltaLynx (QUE)G251999-06-03CANNo190 Lbs6 ft3NoNoFree AgentNoNo12024-09-09FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Michael McLeodLynx (QUE)C261998-02-03CANNo190 Lbs6 ft2NoNoN/ANoNo12024-08-19FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Mitchell ChaffeeLynx (QUE)RW271998-01-26USANo192 Lbs6 ft1NoNoAssign ManuallyNoNo12024-08-09FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Oliver KylingtonLynx (QUE)D271997-05-19SWENo183 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Shane WrightLynx (QUE)C212004-01-05CANNo192 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
Simon NemecLynx (QUE)D202004-02-15SVKYes190 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Trevor ZegrasLynx (QUE)C/LW232001-03-20USANo185 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm1,500,000$150,000$51,429$No1,500,000$--------1,500,000$--------No--------Lien NHL
Uvis BalinskisLynx (QUE)D281996-08-01LVANo196 Lbs6 ft0NoNoFree AgentNoNo12024-10-07FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Victor SoderstromLynx (QUE)D232001-02-26SWENo184 Lbs5 ft11NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Yan KuznetsovLynx (QUE)D222002-03-09RUSNo209 Lbs6 ft4NoNoFree AgentNoNo12024-09-11FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Yaniv PeretsLynx (QUE)G242000-03-04CANNo181 Lbs6 ft1NoNoFree AgentNoNo12024-09-09FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2724.11191 Lbs6 ft11.78537,037$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Connor ZaryMichael McLeodLogan Cooley33014
2Anthony BeauvillierBrett HowdenMitchell Chaffee30023
3Trevor ZegrasMartin PospisilBo Groulx25113
4Connor ZaryAdam RuzickaKirby Dach12032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Oliver KylingtonSimon Nemec40122
2Lane HutsonUvis Balinskis30122
3Yan KuznetsovJack St. Ivany20122
4Simon NemecOliver Kylington10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Martin PospisilConnor ZaryLogan Cooley60005
2Anthony BeauvillierMichael McLeodBrett Howden40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon NemecLane Hutson60014
2Uvis BalinskisOliver Kylington40014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Michael McLeodConnor Zary60041
2Brett HowdenAnthony Beauvillier40041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon NemecJack St. Ivany60140
2Uvis BalinskisOliver Kylington40140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Michael McLeod60140Simon NemecJack St. Ivany60140
2Brett Howden40140Uvis BalinskisOliver Kylington40140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Connor ZaryLogan Cooley60023
2Michael McLeodAnthony Beauvillier40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon NemecLane Hutson60032
2Uvis BalinskisOliver Kylington40032
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anthony BeauvillierConnor ZaryLogan CooleyOliver KylingtonSimon Nemec
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Connor ZaryMichael McLeodLogan CooleyOliver KylingtonSimon Nemec
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Adam Ruzicka, Bo Groulx, Mitchell ChaffeeMartin Pospisil, Adam RuzickaMitchell Chaffee
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Oliver Kylington, Uvis Balinskis, Jack St. IvanyOliver KylingtonOliver Kylington, Uvis Balinskis
Tirs de pénalité
Logan Cooley, Connor Zary, Anthony Beauvillier, Martin Pospisil, Brett Howden
Gardien
#1 : Jonas Johansson, #2 : Devin Cooley
Lignes d’attaque personnalisées en prolongation
Logan Cooley, Connor Zary, Anthony Beauvillier, Martin Pospisil, Brett Howden, Trevor Zegras, Trevor Zegras, Mitchell Chaffee, Adam Ruzicka, Bo Groulx, Kirby Dach
Lignes de défense personnalisées en prolongation
Simon Nemec, Oliver Kylington, Uvis Balinskis, Jack St. Ivany, Lane Hutson


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
1Aces11000000615000000000001100000061521.0006111700908174850566647639412274222150.00%20100.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
2Admirals2200000011832200000011830000000000041.0001120310090817485656664763941942114405120.00%70100.00%11098186558.87%968169257.21%54993958.47%147410861098336645343
3Americiens4200010121192220000001174200001011012-260.75021365700908174816656664763941175582410814428.57%12375.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
4Barons10001000101100010001010000000000021.0001230190817482756664763941208611400.00%20100.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
5Barracuda402011002224-21010000056-1301011001718-130.3752240620090817481455666476394116142206510330.00%10460.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
6Broncos11000000514110000005140000000000021.00059140090817482756664763941216624000%30100.00%11098186558.87%968169257.21%54993958.47%147410861098336645343
7Bruins430010002181333000000175121000100043181.000214061009081748138566647639411213327706116.67%11190.91%01098186558.87%968169257.21%54993958.47%147410861098336645343
8Butter Knives640000023024632000001131033200000117143100.8333055850090817482375666476394124758221201715.88%10460.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
9Canucks22000000954110000005231100000043141.0009172600908174870566647639413715833500.00%4250.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
10Fighting Pandas41201000171432110000011832010100066040.500173148009081748119566647639411425030758337.50%15380.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
11Firebirds33000000191091100000065122000000135861.000193554009081748129566647639411213410617228.57%5180.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
12Griffins11000000532000000000001100000053221.0005813009081748305666476394133146183133.33%30100.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
13Ice Bats2010100010100100010006511010000045-120.5001019290090817481045666476394189311041300.00%5180.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
14Marlies412010001011-1210010006422020000047-340.50010142400908174892566647639419931217410220.00%5180.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
15Nordiks5210020023230311001001113-2210001001210260.6002341640090817482065666476394119057319616318.75%13376.92%11098186558.87%968169257.21%54993958.47%147410861098336645343
16Punishers210010001284100010006511100000063341.00012223400908174856566647639414381734200.00%6183.33%01098186558.87%968169257.21%54993958.47%147410861098336645343
17Roadrunners22000000945220000009450000000000041.00091827009081748685666476394149184388225.00%2150.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
18Wombats43100000181352110000078-122000000115660.7501831490090817481325666476394111540207512325.00%10460.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
19Wranglers11000000312000000000001100000031221.0003580090817483356664763941175624000%30100.00%01098186558.87%968169257.21%54993958.47%147410861098336645343
Total5330907403252187652818404101130913925125033021229626810.764252454706019081748188556664763941179653628610291322720.45%1282977.34%31098186558.87%968169257.21%54993958.47%147410861098336645343
_Since Last GM Reset5330907403252187652818404101130913925125033021229626810.764252454706019081748188556664763941179653628610291322720.45%1282977.34%31098186558.87%968169257.21%54993958.47%147410861098336645343
_Vs Conference3422503103161112492016201001966036146302102655213540.7941612894500090817481164566647639411184349178685871921.84%801877.50%21098186558.87%968169257.21%54993958.47%147410861098336645343
_Vs Division22114031039976231291010015834241023021024142-1320.7279917627500908174875256664763941784230124447551120.00%531277.36%01098186558.87%968169257.21%54993958.47%147410861098336645343

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5381L125245470618851796536286102901
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
533097403252187
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
28184410113091
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
25125330212296
Derniers 10 matchs
WLOTWOTL SOWSOL
820000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1322720.45%1282977.34%3
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
566647639419081748
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
1098186558.87%968169257.21%54993958.47%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
147410861098336645343


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
14Lynx1Marlies3LSommaire du match
29Lynx6Americiens7LXXSommaire du match
421Nordiks7Lynx4LSommaire du match
735Fighting Pandas4Lynx3LSommaire du match
949Lynx4Bruins3WXSommaire du match
1057Bruins1Lynx6WSommaire du match
1373Marlies2Lynx3WXSommaire du match
1584Lynx7Barracuda6WXSommaire du match
1691Lynx3Fighting Pandas4LSommaire du match
19103Barracuda6Lynx5LSommaire du match
20112Lynx5Butter Knives6LXXSommaire du match
21121Lynx4Americiens5LXSommaire du match
22129Butter Knives3Lynx5WSommaire du match
26145Americiens1Lynx4WSommaire du match
27154Lynx7Nordiks4WSommaire du match
31169Butter Knives5Lynx4LXXSommaire du match
34179Lynx6Barracuda7LXSommaire du match
35190Punishers5Lynx6WXSommaire du match
40206Lynx5Griffins3WSommaire du match
42216Bruins1Lynx6WSommaire du match
45232Butter Knives2Lynx4WSommaire du match
48245Lynx5Firebirds2WSommaire du match
49254Bruins3Lynx5WSommaire du match
51268Admirals6Lynx8WSommaire du match
54279Lynx5Nordiks6LXSommaire du match
55290Admirals2Lynx3WSommaire du match
57303Lynx3Fighting Pandas2WXSommaire du match
60314Wombats5Lynx2LSommaire du match
62324Lynx7Butter Knives5WSommaire du match
64333Nordiks4Lynx3LXSommaire du match
68354Lynx6Aces1WSommaire du match
69359Wombats3Lynx5WSommaire du match
73377Roadrunners2Lynx6WSommaire du match
74387Lynx5Butter Knives3WSommaire du match
77398Canucks2Lynx5WSommaire du match
79409Lynx4Ice Bats5LSommaire du match
81417Lynx4Canucks3WSommaire du match
82425Firebirds5Lynx6WSommaire du match
86442Ice Bats5Lynx6WXSommaire du match
88453Lynx8Firebirds3WSommaire du match
89464Marlies2Lynx3WSommaire du match
92478Lynx6Punishers3WSommaire du match
93486Barons0Lynx1WXSommaire du match
95494Lynx3Marlies4LSommaire du match
96505Lynx5Wombats3WSommaire du match
98511Broncos1Lynx5WSommaire du match
101529Lynx3Wranglers1WSommaire du match
102535Americiens6Lynx7WSommaire du match
106554Nordiks2Lynx4WSommaire du match
109571Lynx6Wombats2WSommaire du match
110576Roadrunners2Lynx3WSommaire du match
113594Fighting Pandas4Lynx8WSommaire du match
115603Lynx4Barracuda5LSommaire du match
117617Fighting Pandas-Lynx-
118620Lynx-Tomahawks-
121638Lynx-Lions-
122640Wranglers-Lynx-
126662Aces-Lynx-
129677Lynx-Bruins-
130684Lions-Lynx-
135705Tomahawks-Lynx-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
137712Lynx-Fighting Pandas-
140727Punishers-Lynx-
141736Lynx-Punishers-
143747Barracuda-Lynx-
147765Lynx-Bruins-
148771Broncos-Lynx-
153793Barracuda-Lynx-
155802Lynx-Americiens-
157815Americiens-Lynx-
158819Lynx-Barons-
160831Lynx-Marlies-
161837Firebirds-Lynx-
162844Lynx-Roadrunners-
165859Marlies-Lynx-
166862Lynx-Admirals-
167868Lynx-Broncos-
168872Lynx-Americiens-
170882Griffins-Lynx-
171884Lynx-Admirals-
172889Lynx-Roadrunners-
173892Lynx-Broncos-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
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
1,309,733$ 1,450,000$ 1,450,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,450,000$ 981,134$ 27 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 60 11,143$ 668,580$




Lynx 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

Lynx 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

Lynx 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

Lynx 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

Lynx 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