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Syracuse
GP: 33 | W: 12 | L: 16 | OTL: 5 | P: 29
GF: 84 | GA: 109 | PP%: 16.33% | PK%: 83.65%
DG: William Mercier | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #443 vs Charlotte

Centre de jeu
San Jose
18-13-4, 40pts
4
FINAL
2 Syracuse
12-16-5, 29pts
Team Stats
L2SéquenceL2
9-7-2Fiche domicile5-11-2
9-6-2Fiche domicile7-5-3
6-4-0Derniers 10 matchs5-3-2
3.37Buts par match 2.55
3.43Buts contre par match 3.30
21.01%Pourcentage en avantage numérique16.33%
77.17%Pourcentage en désavantage numérique83.65%
Coachella Valley
20-12-4, 44pts
7
FINAL
3 Syracuse
12-16-5, 29pts
Team Stats
W1SéquenceL2
13-4-0Fiche domicile5-11-2
7-8-4Fiche domicile7-5-3
6-3-1Derniers 10 matchs5-3-2
3.19Buts par match 2.55
2.58Buts contre par match 3.30
13.55%Pourcentage en avantage numérique16.33%
80.92%Pourcentage en désavantage numérique83.65%
Syracuse
12-16-5, 29pts
Jour 85
Charlotte
25-6-5, 55pts
Statistiques d’équipe
L2SéquenceW5
5-11-2Fiche domicile13-2-2
7-5-3Fiche visiteur12-4-3
5-3-210 derniers matchs8-1-1
2.55Buts par match 3.81
3.30Buts contre par match 3.81
16.33%Pourcentage en avantage numérique15.07%
83.65%Pourcentage en désavantage numérique83.65%
Syracuse
12-16-5, 29pts
Jour 86
Abbotsford
8-23-3, 19pts
Statistiques d’équipe
L2SéquenceL2
5-11-2Fiche domicile4-13-1
7-5-3Fiche visiteur4-10-2
5-3-210 derniers matchs1-9-0
2.55Buts par match 2.59
3.30Buts contre par match 2.59
16.33%Pourcentage en avantage numérique16.45%
83.65%Pourcentage en désavantage numérique80.00%
Hartford
19-14-3, 41pts
Jour 88
Syracuse
12-16-5, 29pts
Statistiques d’équipe
W1SéquenceL2
9-7-1Fiche domicile5-11-2
10-7-2Fiche visiteur7-5-3
2-7-110 derniers matchs5-3-2
3.36Buts par match 2.55
3.47Buts contre par match 2.55
23.03%Pourcentage en avantage numérique16.33%
76.76%Pourcentage en désavantage numérique83.65%
Meneurs d'équipe
Buts
Landon Slaggert
11
Passes
Landon Slaggert
18
Points
Landon Slaggert
29
Plus/Moins
Rocco Grimaldi
-1
Victoires
Devan Dubnyk
6
Pourcentage d’arrêts
Devan Dubnyk
0.941

Statistiques d’équipe
Buts pour
84
2.55 GFG
Tirs pour
1167
35.36 Avg
Pourcentage en avantage numérique
16.3%
24 GF
Début de zone offensive
40.7%
Buts contre
109
3.30 GAA
Tirs contre
1247
37.79 Avg
Pourcentage en désavantage numérique
83.7%%
17 GA
Début de la zone défensive
42.7%
Informations de l'équipe

Directeur généralWilliam Mercier
EntraîneurRob Murray
DivisionNord
ConférenceConference est
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,238
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure20
Limite contact 41 / 50
Espoirs37


Historique d'équipe

Saison actuelle12-16-5 (29PTS)
Historique54-50-14 (0.458%)
Apparitions en séries éliminatoires 2
Historique en séries éliminatoires (W-L)10 - 10 (0.500%)
Coupe Stanley0


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
1Jori LehteraXXX96.00622991528368876580616762797771185000361500,000$
2Anders LeeX100.00732985679076926568646659757592245000331800,000$
3Carl HagelinXX100.00654284696978846754686763777963255000351800,000$
4Rocco GrimaldiXX97.00682093736875816670656761826452425000311500,000$
5Damien Giroux (R)X100.00413098757781996470646664754440575000241500,000$
6Trevor LewisXXX100.00612792567363906786676766676661175000371500,000$
7David DesharnaisXX100.00552295606372926485656561868468265000371500,000$
8Trevor MooreXX100.00672389787679946370636564756153505000291800,000$
9Justin BaileyXX100.00623190808978796876666865695550375000291800,000$
10Pontus AbergXX100.00602797788371857073696758836157415000301700,000$
11Ben Jones (R)XX100.00754585727970996370646464704949555000251500,000$
12Landon Slaggert (R)XX96.00713082857979996670676768703838695000223500,000$
13Nikita NesterovX100.00712966797086874853484982705941415000301800,000$
14Travis HamonicX100.0073515161758088501504485527572285000341500,000$
15Mark BarberioX100.00653282608172824850454384737061245000341500,000$
16Ryan JohnsonX100.00732598868578994470474088754039675000222700,000$
Rayé
1Dylan OlsenX95.00653763658478874950454888505847285000331500,000$
MOYENNE D’ÉQUIPE99.0665318570787690606460607072625638500
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
1Devan Dubnyk100.0059798984778283838373718583225000381800,000$
2Corey Crawford100.005584888174827980807881949985000392600,000$
Rayé
1Dustin Tokarski100.0059877776718081787775707069325000341670,000$
2James Reimer100.0057827882718685838473798281395000361800,000$
MOYENNE D’ÉQUIPE100.005883838173838281817575838325500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Rob Murray79768970999964CAN5711,400,000$


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
1Landon SlaggertSyracuse (TAM)C/LW33111829-9180376215729847.01%1963719.32891762139000181046.18%64100000.9101000101
2Carl HagelinSyracuse (TAM)LW/RW3381523-131810472310340837.77%960218.252121442140000001137.50%7200000.7601002300
3Justin BaileySyracuse (TAM)LW/RW3391019-760144212532857.20%754416.5116738117000022048.28%5800000.7011000000
4Travis HamonicSyracuse (TAM)D3161016-4441056223861815.79%4451916.77123817000062100%000000.6200100120
5Rocco GrimaldiSyracuse (TAM)LW/RW317815-1100325164186310.94%1246114.89000000003711051.28%3900000.6501000012
6Ryan JohnsonSyracuse (TAM)D2531215-41002126548345.56%3757523.002133493000025200%000000.5200000110
7Nikita NesterovSyracuse (TAM)D2541014-314044265916366.78%4155922.392463497000062010%000000.5000000000
8Jori LehteraSyracuse (TAM)C/LW/RW314913-38029485114297.84%945314.63000110002720052.53%61300000.5700000021
9Pontus AbergSyracuse (TAM)LW/RW335712-102017347332536.85%1453616.260114191013850257.50%4000000.4502000001
10Damien GirouxSyracuse (TAM)C313811-5002646927664.35%1045814.801231788000021044.12%61200000.4800000000
11David DesharnaisSyracuse (TAM)C/LW314711-32011196019466.67%837812.2000000000000045.45%2200000.5801000002
12Trevor LewisSyracuse (TAM)C/LW/RW313710-24020195217335.77%433910.9700000000000045.16%6200000.5900000000
13Alex GoligoskiTampa Bay D236410-6207143782016.22%3546420.194042180000053110%000000.4301000110
14Dylan OlsenSyracuse (TAM)D31459-22200293728162914.29%6968622.15000010000642039.67%12100000.2600000000
15Brandon DavidsonTampa Bay D17066-81001511269150%3035821.12011176200006000%000000.3300000000
16Ben JonesSyracuse (TAM)C/LW25314-1331534265618325.36%541216.492021469000020045.42%29500000.1900100010
17Nicklas BergforsTampa Bay LW/RW15213-6801413419244.88%122014.73011414000030057.14%1400000.2700000001
18Trevor MooreSyracuse (TAM)LW/RW33123-5801322244234.17%92276.880002120001200045.51%15600000.2600000001
19Mark BarberioSyracuse (TAM)D2000-300113100%42713.630000000001000%00000000000000
Statistiques d’équipe totales ou en moyenne51483140223-1272152544356011203237737.41%367846616.472339622989561011054712546.81%274500000.5318202789
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
1Devan DubnykSyracuse (TAM)126320.9412.5470900305100100.71471131320
2James ReimerSyracuse (TAM)164930.9102.9097321475250020.3333160210
3Corey CrawfordSyracuse (TAM)42200.8834.8719700161370010040000
Statistiques d’équipe totales ou en moyenne32121450.9212.97188021931172013103131530


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 Salaire restantPlafond 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
Anders LeeSyracuse (TAM)LW331990-07-03USANo235 Lbs6 ft3NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$455,385$0$0$No---------------------------Lien / Lien NHL
Ben JonesSyracuse (TAM)C/LW251999-02-26CANYes187 Lbs6 ft0NoNoProspectNoNo12025-11-01FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------
Carl HagelinSyracuse (TAM)LW/RW351988-08-23SWENo195 Lbs5 ft11NoNoFree AgentNoNo12025-09-30FalseFalsePro & Farm800,000$455,385$0$0$No---------------------------Lien
Corey CrawfordSyracuse (TAM)G391984-12-31CANNo221 Lbs6 ft2NoNoFree AgentNoNo22025-09-27FalseFalsePro & Farm600,000$341,538$0$0$No600,000$--------600,000$--------No--------Lien
Damien GirouxSyracuse (TAM)C242000-03-03CANYes179 Lbs5 ft10NoNoTrade2025-08-27NoNo1FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------
David DesharnaisSyracuse (TAM)C/LW371986-09-14CANNo177 Lbs5 ft7NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------Lien
Devan DubnykSyracuse (TAM)G381986-05-04CANNo221 Lbs6 ft6NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$455,385$0$0$No---------------------------
Dustin TokarskiSyracuse (TAM)G341989-09-16CANNo203 Lbs5 ft11NoNoFree AgentNoNo12024-10-09FalseFalsePro & Farm670,000$381,385$0$0$No---------------------------Lien
Dylan OlsenSyracuse (TAM)D331991-01-03USANo233 Lbs6 ft2NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------Lien
James ReimerSyracuse (TAM)G361988-01-21CANNo228 Lbs6 ft2NoNoFree AgentNoNo12024-10-21FalseFalsePro & Farm800,000$455,385$0$0$No---------------------------Lien NHL
Jori LehteraSyracuse (TAM)C/LW/RW361987-12-23FINNo212 Lbs6 ft2NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------Lien
Justin BaileySyracuse (TAM)LW/RW291995-07-01USANo220 Lbs6 ft3NoNoFree Agent2025-03-23NoNo12025-09-30FalseFalsePro & Farm800,000$455,385$0$0$No---------------------------Lien / Lien NHL
Landon SlaggertSyracuse (TAM)C/LW222002-06-25USAYes180 Lbs6 ft0NoNoProspectNoNo32025-11-01FalseFalsePro & Farm500,000$284,615$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------
Mark BarberioSyracuse (TAM)D341990-03-23CANNo209 Lbs6 ft1NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------
Nikita NesterovSyracuse (TAM)D301994-03-28RUSNo197 Lbs5 ft11NoNoFree AgentNoNo12024-10-11FalseFalsePro & Farm800,000$455,385$0$0$No---------------------------Lien
Pontus AbergSyracuse (TAM)LW/RW301993-09-23SWENo197 Lbs6 ft0NoNoFree AgentNoNo12025-09-27FalseFalsePro & Farm700,000$398,462$0$0$No---------------------------Lien
Rocco GrimaldiSyracuse (TAM)LW/RW311993-02-08USANo183 Lbs5 ft6NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$284,615$0$0$No---------900,000$900,000$----------------Lien
Ryan JohnsonSyracuse (TAM)D222001-07-24USANo195 Lbs6 ft1NoNoProspectNoNo22024-10-08FalseFalsePro & Farm700,000$398,462$0$0$No700,000$--------700,000$--------No--------
Travis HamonicSyracuse (TAM)D341990-01-19CANNo219 Lbs6 ft3NoNoFree Agent2025-03-19NoNo12025-11-05FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------Lien NHL
Trevor LewisSyracuse (TAM)C/LW/RW371987-01-08USANo208 Lbs6 ft1NoNoFree AgentNoNo12025-11-05FalseFalsePro & Farm500,000$284,615$0$0$No---------------------------Lien / Lien NHL
Trevor MooreSyracuse (TAM)LW/RW291995-03-31USANo186 Lbs5 ft10NoNoFree AgentNoNo12025-09-30FalseFalsePro & Farm800,000$455,385$0$0$No---------------------------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2131.81204 Lbs6 ft01.19631,905$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Landon SlaggertCarl Hagelin32005
2Justin BaileyDamien Giroux30005
3Trevor LewisPontus Aberg25122
4David DesharnaisJori LehteraRocco Grimaldi13122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
138014
232122
3Travis Hamonic30122
40122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Landon SlaggertCarl Hagelin65005
2Damien GirouxJustin Bailey35005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
150005
250005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Pontus Aberg50122
2Jori LehteraRocco Grimaldi50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
150122
2Travis Hamonic50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
15012250122
2Jori Lehtera50122Travis Hamonic50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Pontus Aberg50122
2Justin BaileyLandon Slaggert50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
150122
2Travis Hamonic50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Carl HagelinLandon SlaggertJustin Bailey
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Pontus AbergJustin Bailey
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Carl Hagelin, Trevor Moore, Carl HagelinTrevor Moore
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, , Travis Hamonic, Travis Hamonic
Tirs de pénalité
, Pontus Aberg, Justin Bailey, Landon Slaggert, Carl Hagelin
Gardien
#1 : , #2 :
Lignes d’attaque personnalisées en prolongation
Landon Slaggert, Carl Hagelin, , Justin Bailey, Damien Giroux, , Jori Lehtera, , Trevor Lewis, Rocco Grimaldi
Lignes de défense personnalisées en prolongation
, , , Travis Hamonic,


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
1Bakersfield2110000045-1000000000002110000045-120.500481200332623365399382362338220162811218.18%8275.00%0607127747.53%627133946.83%24352346.46%739494833258429211
2Bridgeport21000001550210000015500000000000030.75058130033262336639938236233672014259222.22%70100.00%0607127747.53%627133946.83%24352346.46%739494833258429211
3Coachella Valley1010000037-41010000037-40000000000000.000369003326233353993823623334146263133.33%30100.00%0607127747.53%627133946.83%24352346.46%739494833258429211
4Eagles2020000068-21010000034-11010000034-100.000610160033262335839938236233551718268337.50%9366.67%0607127747.53%627133946.83%24352346.46%739494833258429211
5Grand Rapids422000001214-21010000014-3321000001110140.5001224361033262331413993823623317047276219210.53%11372.73%0607127747.53%627133946.83%24352346.46%739494833258429211
6Hartford2010010058-31000010034-11010000024-210.25059140033262335239938236233793636318225.00%10190.00%0607127747.53%627133946.83%24352346.46%739494833258429211
7Laval2020000039-62020000039-60000000000000.000358103326233703993823623378241633900.00%7185.71%0607127747.53%627133946.83%24352346.46%739494833258429211
8Lehigh Valley21000100550000000000002100010055030.7505914003326233613993823623386251831400.00%90100.00%0607127747.53%627133946.83%24352346.46%739494833258429211
9Manitoba22000000514110000003121100000020241.0005914013326233813993823623363251226800.00%60100.00%0607127747.53%627133946.83%24352346.46%739494833258429211
10Ontario1010000034-11010000034-10000000000000.000347003326233413993823623332821510220.00%110.00%0607127747.53%627133946.83%24352346.46%739494833258429211
11Providence1010000023-1000000000001010000023-100.00023500332623327399382362333515813300.00%30100.00%0607127747.53%627133946.83%24352346.46%739494833258429211
12Rochester1000010034-1000000000001000010034-110.500347003326233553993823623325981110330.00%4250.00%0607127747.53%627133946.83%24352346.46%739494833258429211
13Rockford31200000610-431200000610-40000000000020.333612180033262331183993823623312233204614214.29%8362.50%0607127747.53%627133946.83%24352346.46%739494833258429211
14San Diego1000000145-1000000000001000000145-110.50045900332623345399382362335015413300.00%20100.00%0607127747.53%627133946.83%24352346.46%739494833258429211
15San Jose2010100056-11010000024-21000100032120.50059140033262335939938236233702112304125.00%6183.33%0607127747.53%627133946.83%24352346.46%739494833258429211
16Texas32001000963210010007521100000021161.000914230033262331263993823623313841124713215.38%50100.00%1607127747.53%627133946.83%24352346.46%739494833258429211
17Utica 1010000014-31010000014-30000000000000.00011200332623328399382362333516812400.00%40100.00%0607127747.53%627133946.83%24352346.46%739494833258429211
18Wilkes-Barre/Scranton1010000035-21010000035-20000000000000.00036910332623339399382362332672137228.57%10100.00%0607127747.53%627133946.83%24352346.46%739494833258429211
Total3310160230284109-2518411011014366-231565012014143-2290.4398414623031332623311673993823623312473932394881472416.33%1041783.65%1607127747.53%627133946.83%24352346.46%739494833258429211
_Since Last GM Reset3310160230284109-2518411011014366-231565012014143-2290.4398414623031332623311673993823623312473932394881472416.33%1041783.65%1607127747.53%627133946.83%24352346.46%739494833258429211
_Vs Conference1648003013957-18815001011631-15833002002326-3120.375396910830332623353939938236233601199137231731115.07%56787.50%0607127747.53%627133946.83%24352346.46%739494833258429211
_Vs Division825001002030-1030300000413-9522001001617-150.31320365620332623329339938236233308955911941512.20%25676.00%0607127747.53%627133946.83%24352346.46%739494833258429211

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3329L2841462301167124739323948831
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
331016230284109
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
1841111014366
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
156512014143
Derniers 10 matchs
WLOTWOTL SOWSOL
530200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1472416.33%1041783.65%1
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
399382362333326233
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
607127747.53%627133946.83%24352346.46%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
739494833258429211


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
17Syracuse5Grand Rapids4WSommaire du match
316Laval6Syracuse2LSommaire du match
730Utica 4Syracuse1LSommaire du match
1146Syracuse3Eagles4LSommaire du match
1459Rockford3Syracuse4WSommaire du match
1776Bridgeport2Syracuse1LXXSommaire du match
22100Rockford4Syracuse1LSommaire du match
27126Wilkes-Barre/Scranton5Syracuse3LSommaire du match
30137Syracuse3Lehigh Valley2WSommaire du match
32149Syracuse3Bakersfield1WSommaire du match
33155Eagles4Syracuse3LSommaire du match
36174Grand Rapids4Syracuse1LSommaire du match
38184Syracuse3Grand Rapids5LSommaire du match
39193Syracuse2Hartford4LSommaire du match
41203Hartford4Syracuse3LXSommaire du match
44220Syracuse2Manitoba0WSommaire du match
46226Syracuse2Providence3LSommaire du match
47232Laval3Syracuse1LSommaire du match
50248Syracuse3San Jose2WXSommaire du match
52258Rockford3Syracuse1LSommaire du match
55273Syracuse1Bakersfield4LSommaire du match
57283Manitoba1Syracuse3WSommaire du match
59293Syracuse4San Diego5LXXSommaire du match
62306Syracuse3Rochester4LXSommaire du match
63313Bridgeport3Syracuse4WSommaire du match
67333Texas2Syracuse3WSommaire du match
70349Syracuse2Texas1WSommaire du match
71357Ontario4Syracuse3LSommaire du match
75378Texas3Syracuse4WXSommaire du match
77390Syracuse3Grand Rapids1WSommaire du match
78401Syracuse2Lehigh Valley3LXSommaire du match
80409San Jose4Syracuse2LSommaire du match
83429Coachella Valley7Syracuse3LSommaire du match
85443Syracuse-Charlotte-
86451Syracuse-Abbotsford-
88461Hartford-Syracuse-
91475Syracuse-Coachella Valley-
93482Rochester-Syracuse-
97504Eagles-Syracuse-
99515Syracuse-Rockford-
101524Syracuse-Charlotte-
103533Springfield-Syracuse-
106555Grand Rapids-Syracuse-
107564Syracuse-Iowa-
109577Syracuse-Rochester-
111586Bakersfield-Syracuse-
113599Syracuse-Manitoba-
114609San Diego-Syracuse-
118629Syracuse-Cleveland-
119633Cleveland-Syracuse-
122652Utica -Syracuse-
124661Syracuse-Bridgeport-
127679Cleveland-Syracuse-
130692Syracuse-Hartford-
132700Syracuse-Hershey-
133709Rochester-Syracuse-
136725Syracuse-Hershey-
137734Wilkes-Barre/Scranton-Syracuse-
140753Providence-Syracuse-
141760Syracuse-Providence-
143775Syracuse-Laval-
145782Syracuse-Springfield-
147788Abbotsford-Syracuse-
150805Syracuse-Eagles-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
151811Syracuse-Utica -
153821Iowa-Syracuse-
156838Providence-Syracuse-
158854Abbotsford-Syracuse-
160862Syracuse-Cleveland-
163880Syracuse-Ontario-
164887Lehigh Valley-Syracuse-
166897Syracuse-Bridgeport-
169910Charlotte-Syracuse-
171922Syracuse-Wilkes-Barre/Scranton-
174934Charlotte-Syracuse-
177947Syracuse-Utica -
180961Lehigh Valley-Syracuse-
182971Syracuse-Wilkes-Barre/Scranton-
185982Hershey-Syracuse-
1901004Syracuse-Laval-
1921010Hershey-Syracuse-
1931015Syracuse-Ontario-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance26,80813,480
Assistance PCT74.47%74.89%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
23 2238 - 74.61% 130,860$2,355,477$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,225,680$ 1,327,000$ 1,327,000$ 1,400,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
6,805$ 622,192$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
3,009,776$ 111 13,985$ 1,552,335$




Syracuse 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
1Charles Hudon1173157881842811713648.52%10215318.41823317410112250.57%00.8247
2Tom Wilson110493079715429310435813.69%15186416.95139227711246448.92%10.8501
3Sonny Milano80374077-622311135010.57%4156219.531512277710117249.66%00.9916
4Mason Marchment7624517515781331162868.39%5146519.29316196400002147.89%01.0206
5Ryan Donato80234669-732911532509.20%12159419.93717244701102149.33%00.8705

Syracuse 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
1Sergei Bobrovsky58282730.9053.09345712117818710100.76913
2Anthony Stolarz2312740.9232.69140821638220300.69213
3Cory Schneider62400.9173.02358001821800000
4Magnus Hellberg72500.9193.16418002227000000

Syracuse 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
Saison régulière
2082353407303260269-941191603102133127641161804201127142-1590260456716057499807264986092183444283881484813903457120.58%3696582.38%31487305248.72%1479312147.39%655131149.96%1917128119726221072533
233310160230284109-2518411011014366-231565012014143-2298414623031332623311673993823623312473932394881472416.33%1041783.65%1607127747.53%627133946.83%24352346.46%739494833258429211
Total Saison régulière115455009605344378-3459232704203176193-1756222305402168185-17119344602946361071251031038161259130311967740851207108718784929519.31%4738282.66%42094432948.37%2106446047.22%898183448.96%2657177528058811502744
Séries éliminatoires
20624000001520-531200000811-33120000079-2415284310724219659605126258698610223417.39%33875.76%010722547.56%13630045.33%479847.96%154105160508542
2114860000059451474300000292277430000030237165910616511271615162322021018310618188161248491122.45%741185.14%035065753.27%31966148.26%12124649.19%32821833611218591
Total Séries éliminatoires20101000000746591055000003733410550000037325207413420821341819381927927023436876257247350721520.83%1071982.24%045788251.81%45596147.35%16834448.84%482323497163270133

Syracuse 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
1Noah Cates29252954816507916714.97%959220.4299184300005153.62%21.8200
2Logan O'Connor2914264002362431529.21%458320.13410144000000243.24%01.3700
3Charles Hudon2916233972302213511.85%556719.5766123200002060.34%01.3700
4Ryan Donato18101525-21619288811.36%135619.835492700003045.71%01.4000
5Fredrik Olofsson2991524-3215577811.54%258220.092351700001052.44%00.8200

Syracuse 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
1Magnus Hellberg2214610.9113.521277417584701000
2Sergei Bobrovsky72310.9183.62365202226701100
3Robin Lehner31100.8834.061330097700000