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Marlies
GP: 80 | W: 34 | L: 38 | OTL: 8 | P: 76
GF: 292 | GA: 324 | PP%: 22.30% | PK%: 80.63%
GM : Pascal Landry | Morale : 36 | Team Overall : 64
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Game Center
Penguins
33-40-7, 73pts
1
FINAL
4 Marlies
34-38-8, 76pts
Team Stats
L2StreakL1
16-20-4Home Record18-19-3
17-20-3Home Record16-19-5
3-7-0Last 10 Games7-2-1
3.60Goals Per Game3.65
4.15Goals Against Per Game4.05
21.33%Power Play Percentage22.30%
76.79%Penalty Kill Percentage80.63%
Marlies
34-38-8, 76pts
3
FINAL
6 Phantoms
41-37-2, 84pts
Team Stats
L1StreakW1
18-19-3Home Record19-19-2
16-19-5Home Record22-18-0
7-2-1Last 10 Games6-4-0
3.65Goals Per Game4.03
4.05Goals Against Per Game4.01
22.30%Power Play Percentage22.57%
80.63%Penalty Kill Percentage75.15%
Team Leaders
Goals
Martin Necas
34
Assists
Pierre-Olivier Joseph
59
Points
Colton Sissons
86
Plus/Minus
Aleksi Saarela
8
Wins
Maxime Lagace
24
Save Percentage
Logan Thompson
0.885

Team Stats
Goals For
292
3.65 GFG
Shots For
2518
31.48 Avg
Power Play Percentage
22.3%
62 GF
Offensive Zone Start
35.9%
Goals Against
324
4.05 GAA
Shots Against
2661
33.26 Avg
Penalty Kill Percentage
80.6%%
61 GA
Defensive Zone Start
37.4%
Team Info

General ManagerPascal Landry
CoachTony Twist
DivisionFritz-Kraatz
ConferenceRobert-Lebel
CaptainColton Sissons
Assistant #1Aleksi Saarela
Assistant #2Jeff Corbett


Arena Info

Capacity3,000
Attendance2,788
Season Tickets300


Roster Info

Pro Team38
Farm Team20
Contract Limit58 / 250
Prospects0


Filter Tips
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.
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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
# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPAgeContractSalary
1Colton Sissons (C)X100.007952737876737475787469717665533449720251995,000$
2Aleksi Saarela (R) (A)X100.007125788369726877707175637855476249710212800,000$
3Logan Brown (R)X100.007848707779658273647574646445446940700202900,000$
4Tyler Benson (R)X100.007943727480627973617275715849446647700202900,000$
5Mathieu Olivier (R)X100.007743767582597171677372686447475849690212900,000$
6Martin Necas (R)X100.006234797256697168838774535844427548680191500,000$
7Alex Formenton (R)X100.007023836484667368657082546244427755670191500,000$
8Kole Sherwood (R)X100.008341717172588071597071655745445154670212900,000$
9Matthew Highmore (R)X100.007121836369697272757269527047474955660223500,000$
10Joel Farabee (R)X100.005038788349625284716464608540409022650182500,000$
11Tobias Lindberg (R)X100.007042727358636765706566586845463556640231500,000$
12Hugh McGing (R)X100.007344706681517166497263555643446528630202500,000$
13Brendan Guhle (R)X100.0071368672727278724975658655614559447302121,300,000$
14Jeff Corbett (R) (A)X100.006935876960787366517276746059513841700241700,000$
15Pierre-Olivier Joseph (R)X100.005328818963697389418562725348428046700191500,000$
16Lucas Carlsson (R)X100.007338877172727166466556765249456158690212900,000$
17Keaton Thompson (R)X100.006439747563647467517564745954484240680232600,000$
18Rasmus Dahlin (R)X100.005435788756546885388061694740408752670182500,000$
Scratches
1Henri Ikonen (R)X100.007245686865537266627168664846463532640231550,000$
2Isac Lundestrom (R)X100.005734675569606961667176516541437620620192500,000$
3Otto Koivula (R)X100.005532676072696169695869516843435820610202750,000$
4Jakob Forsbacka-Karlsson (R)X100.006840666957615757635270565645454320600222500,000$
5Jaden Lindo (R)X100.006534635664575863536164515844444219580221350,000$
6Jonathan Davidsson (R)X100.005821726062605561607055445643475219570213650,000$
7Jan Jenik (R)X100.006332616575556457535953484740407219560182500,000$
8Jonathan Gruden (R)X100.006243565662506457406057444740407220540182500,000$
9Radovan Bondra (R)X100.006825585556486160386556524243434219540211350,000$
10Mike Hardman (R)X100.006432516070516457485051505041415319530191500,000$
11Marc McLaughlin (R)X100.004734654952576160535355406341416118520191500,000$
12Dennis Gilbert (R)X100.007236756959676655467053754247474118660221500,000$
13Dmitri Samorukov (R)X100.006423827062627349386751754642426520640191500,000$
14Brycen Martin (R)X100.006129657057515770296949684145454519610221350,000$
15Jacob Bernard-Docker (R)X100.005741645864645662425954634440407619590182500,000$
16Xavier Bernard (R)X100.005229626548415366296441563540407219540182500,000$
TEAM AVERAGE100.00663572686661676755686461574644593464
Filter Tips
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
# Goalie Name CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SPAgeContractSalary
1Maxime Lagace100.00676765756974777571676652534164700251500,000$
2Logan Thompson99.00815775807666587270578748466648680211500,000$
Scratches
1Veini Vehvilainen (R)100.00727274575270705854787147475920630212500,000$
2Matthew Thiessen (R)100.00573850636244525553415040406920520182500,000$
TEAM AVERAGE99.7569596669656464656261694747593863
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Tony Twist76566970335663USA541550,000$


Filter Tips
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
# Player Name Team NamePOSGP 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
1Colton SissonsMarlies (TOR)C80305686-287401481532435915212.35%45160620.08825334520101122585353.49%19935134011.0727000662
2Pierre-Olivier JosephMarlies (TOR)D80215980-1832063143250961068.40%98192124.01121729582400222188220%05044000.8300000432
3Aleksi SaarelaMarlies (TOR)C6828427084401261282237515312.56%30131019.285712211690224962150.95%14785823001.0717000544
4Martin NecasMarlies (TOR)RW80343670-2500107782216711315.38%25143017.899142332216000142252.31%1304221010.9813000334
5Joel FarabeeMarlies (TOR)LW75303565027565742125912214.15%23110414.72651116101000052150.75%674821001.1813010342
6Mathieu OlivierMarlies (TOR)RW80292352-27595143109165549317.58%30144118.0289172620610161063237.50%1042731110.7213001213
7Tyler BensonMarlies (TOR)LW70222749-22720116851684810513.10%40137219.6189172517021372034448.39%933032100.7113000212
8Brendan GuhleMarlies (TOR)D8063743-314012718111657605.17%124222627.832911192370113302000%04593000.3900000212
9Logan BrownMarlies (TOR)C78192443-750011881142659813.38%25100512.891011513257772246.10%5512716000.8626000121
10Rasmus DahlinMarlies (TOR)D8032831-1510025838460433.57%61117914.75224584000159100%02736000.5300000000
11Jeff CorbettMarlies (TOR)D8042529-111809412410139383.96%123184723.09191091961014279110%03066000.3101000104
12Alex FormentonMarlies (TOR)LW80171229-11201326798305617.35%35129216.15022214910141262042.86%701413000.4500000330
13Kole SherwoodMarlies (TOR)RW80131427-840013660112305211.61%1695611.95000180002400056.06%661214100.5600000113
14Matthew HighmoreMarlies (TOR)C80141024-7120543598277314.29%76938.670110120000141050.99%253128010.6922000101
15Tobias LindbergMarlies (TOR)RW8071118-7220754465264210.77%166798.4900001100000218.33%121712000.5301000101
16Keaton ThompsonMarlies (TOR)D7501515-1643554694015210%5494912.6600015011021000%0933000.3200000000
17Lucas CarlssonMarlies (TOR)D8021315-1280671156316253.17%93144318.0400051080110184000%0941000.2100000010
18Henri IkonenMarlies (TOR)LW6121214-1636065487320442.74%1861910.15000070001770029.41%171110000.4500000100
19Hugh McGingMarlies (TOR)LW3634761404315318149.68%62968.2200000000000075.00%434000.4700000010
20Isac LundestromMarlies (TOR)C15303-48012592633.33%11449.61000010000140145.31%6414000.4201000001
21Jakob Forsbacka-KarlssonMarlies (TOR)C51010001020150.00%0183.7100000000011020.00%500001.0800000000
22Brycen MartinMarlies (TOR)D3000-100000000%000.290000000000000%00000000000000
23Dennis GilbertMarlies (TOR)D80005204102010%5769.620000000001000%00100000000000
24Dmitri SamorukovMarlies (TOR)D3000100000000%062.020000000000000%00000000000000
25Otto KoivulaMarlies (TOR)LW3000000000000%000.250000000000000%00000000000000
Team Total or Average1460288483771-18564715177517072518853141811.44%8752362316.1862109171266218181119442065302050.83%4907523557340.651137011363132
Filter Tips
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
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Maxime LagaceMarlies (TOR)52241950.8803.912812001831520736210.710314631242
2Logan ThompsonMarlies (TOR)3681720.8853.82174480111969493130.50022843111
3Veini VehvilainenMarlies (TOR)62310.8614.8433500271941010100617000
Team Total or Average94343980.8803.944891803212683133035338091353


Filter Tips
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
Player Name Team NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Acquired By Last Trade Date Force Waivers Waiver Possible Contract Contract Signature Date Force UFA Emergency Recall Type Current Salary Salary RemainingSalary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10No Trade Year 2No Trade Year 3No Trade Year 4No Trade Year 5No Trade Year 6No Trade Year 7No Trade Year 8No Trade Year 9No Trade Year 10Link
Aleksi SaarelaMarlies (TOR)C211997-01-01Yes200 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm800,000$3,980$0$0$No900,000$--------No--------
Alex FormentonMarlies (TOR)LW191999-01-01Yes195 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Brendan GuhleMarlies (TOR)D211997-01-01Yes197 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,300,000$6,468$0$0$No2,000,000$--------No--------
Brycen MartinMarlies (TOR)D221996-01-01Yes198 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm350,000$1,741$0$0$No------------------
Colton SissonsMarlies (TOR)C251993-01-01No187 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm995,000$4,950$0$0$No------------------
Dennis GilbertMarlies (TOR)D221996-01-01Yes216 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Dmitri SamorukovMarlies (TOR)D191999-01-01Yes188 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Henri IkonenMarlies (TOR)LW231995-01-01Yes185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm550,000$2,736$0$0$No------------------
Hugh McGingMarlies (TOR)LW201998-01-01Yes176 Lbs5 ft8NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Isac LundestromMarlies (TOR)C191999-01-01Yes193 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Jacob Bernard-DockerMarlies (TOR)D182000-01-01Yes190 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Jaden LindoMarlies (TOR)RW221996-01-01Yes215 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm350,000$1,741$0$0$No------------------
Jakob Forsbacka-KarlssonMarlies (TOR)C221996-01-01Yes184 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No550,000$--------No--------
Jan JenikMarlies (TOR)RW182000-01-01Yes185 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Jeff CorbettMarlies (TOR)D241994-01-01Yes185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm700,000$3,483$0$0$No------------------
Joel FarabeeMarlies (TOR)LW182000-01-01Yes180 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Jonathan DavidssonMarlies (TOR)RW211997-01-01Yes181 Lbs5 ft11NoNoN/ANoNo3FalseFalsePro & Farm650,000$3,234$0$0$No650,000$650,000$-------NoNo-------
Jonathan GrudenMarlies (TOR)C182000-01-01Yes172 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Keaton ThompsonMarlies (TOR)D231995-01-01Yes185 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm600,000$2,985$0$0$No600,000$--------No--------
Kole SherwoodMarlies (TOR)RW211997-01-01Yes212 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
Logan BrownMarlies (TOR)C201998-01-01Yes227 Lbs6 ft6NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
Logan ThompsonMarlies (TOR)G211997-01-01No201 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Lucas CarlssonMarlies (TOR)D211997-01-01Yes190 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
Marc McLaughlinMarlies (TOR)C191999-01-01Yes210 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Martin NecasMarlies (TOR)RW191999-01-01Yes189 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Mathieu OlivierMarlies (TOR)RW211997-01-01Yes209 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
Matthew HighmoreMarlies (TOR)C221996-01-01Yes188 Lbs5 ft11NoNoN/ANoNo3FalseFalsePro & Farm500,000$2,488$0$0$No500,000$500,000$-------NoNo-------
Matthew ThiessenMarlies (TOR)G182000-01-01Yes208 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Maxime LagaceMarlies (TOR)G251993-01-01No190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Mike HardmanMarlies (TOR)LW191999-01-01Yes205 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Otto KoivulaMarlies (TOR)LW201998-01-01Yes220 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm750,000$3,731$0$0$No750,000$--------No--------
Pierre-Olivier JosephMarlies (TOR)D191999-01-01Yes185 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Radovan BondraMarlies (TOR)RW211997-01-01Yes217 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm350,000$1,741$0$0$No------------------
Rasmus DahlinMarlies (TOR)D182000-01-01Yes202 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Tobias LindbergMarlies (TOR)RW231995-01-01Yes185 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Tyler BensonMarlies (TOR)LW201998-01-01Yes190 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
Veini VehvilainenMarlies (TOR)G211997-01-01Yes174 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Xavier BernardMarlies (TOR)D182000-01-01Yes200 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3820.55195 Lbs6 ft11.63602,500$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Joel FarabeeAleksi SaarelaMartin Necas40122
2Tyler BensonColton SissonsMathieu Olivier30122
3Alex FormentonLogan BrownKole Sherwood20122
4Hugh McGingMatthew HighmoreTobias Lindberg10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Brendan GuhlePierre-Olivier Joseph40122
2Jeff CorbettRasmus Dahlin30122
3Keaton ThompsonLucas Carlsson20122
4Brendan GuhleJeff Corbett10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Tyler BensonColton SissonsMartin Necas60113
2Joel FarabeeAleksi SaarelaMathieu Olivier40113
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Brendan GuhlePierre-Olivier Joseph60113
2Jeff CorbettRasmus Dahlin40113
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Colton SissonsTyler Benson60122
2Logan BrownMathieu Olivier40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Brendan GuhleJeff Corbett60122
2Pierre-Olivier JosephRasmus Dahlin40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Colton Sissons60122Brendan GuhleJeff Corbett60122
2Tyler Benson40122Pierre-Olivier JosephRasmus Dahlin40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Colton SissonsMartin Necas60122
2Logan BrownMathieu Olivier40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Brendan GuhlePierre-Olivier Joseph60122
2Jeff CorbettRasmus Dahlin40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Joel FarabeeColton SissonsMartin NecasBrendan GuhlePierre-Olivier Joseph
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Tyler BensonColton SissonsMathieu OlivierBrendan GuhleLucas Carlsson
Extra Forwards
Normal PowerPlayPenalty Kill
Kole Sherwood, Tyler Benson, Martin NecasMathieu Olivier, Martin NecasLogan Brown
Extra Defensemen
Normal PowerPlayPenalty Kill
Lucas Carlsson, Keaton Thompson, Rasmus DahlinLucas CarlssonLucas Carlsson, Keaton Thompson
Penalty Shots
Logan Brown, Aleksi Saarela, Martin Necas, Colton Sissons, Mathieu Olivier
Goalie
#1 : Logan Thompson, #2 : Maxime Lagace
Custom OT Lines Forwards
Colton Sissons, Joel Farabee, Aleksi Saarela, Martin Necas, Logan Brown, Tyler Benson, Tyler Benson, Alex Formenton, Mathieu Olivier, Kole Sherwood, Matthew Highmore
Custom OT Lines Defensemen
Pierre-Olivier Joseph, Brendan Guhle, Rasmus Dahlin, Jeff Corbett, Keaton Thompson


Filter Tips
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
OverallHomeVisitor
# VS Team 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
1Admirals302010001113-21010000045-12010100078-120.33311162700681021121697752892838701094522729222.22%11463.64%0927173953.31%916181550.47%651129650.23%170394317147521440716
2Americans311001001011-1211000005501000010056-130.50010182800681021121610375289283870893036665360.00%18194.44%0927173953.31%916181550.47%651129650.23%170394317147521440716
3Barracuda302010001215-31000100043120200000812-420.3331223351068102112161047528928387095323042200.00%15380.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
4Bears2110000035-21010000014-31100000021120.5003580068102112165975289283870722010513133.33%50100.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
5Canucks41101010131303100101011831010000025-360.7501319320068102112161307528928387012654398111436.36%13192.31%0927173953.31%916181550.47%651129650.23%170394317147521440716
6Checkers2110000089-11010000057-21100000032120.500812201068102112166675289283870712414537228.57%7185.71%0927173953.31%916181550.47%651129650.23%170394317147521440716
7Comets3210000015105110000006242110000098140.66715233800681021121694752892838701112324785240.00%13192.31%3927173953.31%916181550.47%651129650.23%170394317147521440716
8Condors312000001112-1211000007611010000046-220.333112031006810211216937528928387010632206713323.08%10370.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
9Crunch210001001055110000007161000010034-130.750101828006810211216717528928387049218388225.00%40100.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
10Eagles2010010069-31010000035-21000010034-110.250610160068102112165775289283870652510546116.67%5180.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
11Griffins31200000711-41010000046-22110000035-220.3337101710681021121687752892838701013718661218.33%9277.78%0927173953.31%916181550.47%651129650.23%170394317147521440716
12Icehogs312000001113-21010000036-32110000087120.33311182900681021121676752892838709630266511218.18%12375.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
13Islander21100000660110000003211010000034-120.5006915006810211216817528928387060288511000.00%4250.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
14Little Stars302001001018-81010000038-520100100710-310.1671019290068102112169675289283870105381653700.00%8187.50%0927173953.31%916181550.47%651129650.23%170394317147521440716
15Moose514000001325-122110000078-130300000617-1120.20013233600681021121614975289283870171494111716318.75%18477.78%0927173953.31%916181550.47%651129650.23%170394317147521440716
16Penguins22000000835110000004131100000042241.000813210068102112166975289283870512012519222.22%6183.33%0927173953.31%916181550.47%651129650.23%170394317147521440716
17Phantoms623000012126-531200000912-3311000011214-250.41721375800681021121619975289283870193576711733927.27%30680.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
18Punishers202000001014-41010000045-11010000069-300.0001017270068102112167075289283870761614348450.00%7185.71%0927173953.31%916181550.47%651129650.23%170394317147521440716
19Reign724010002430-6403010001217-5321000001213-160.42924396310681021121620175289283870241817216427725.93%371072.97%1927173953.31%916181550.47%651129650.23%170394317147521440716
20Rocket30300000812-42020000058-31010000034-100.00081220006810211216887528928387010434246910110.00%12283.33%0927173953.31%916181550.47%651129650.23%170394317147521440716
21Senators320000011578210000019631100000061550.83315243900681021121688752892838701083618699222.22%9188.89%0927173953.31%916181550.47%651129650.23%170394317147521440716
22Silver Knights21001000862100010005411100000032141.00081523006810211216727528928387057198468112.50%4175.00%0927173953.31%916181550.47%651129650.23%170394317147521440716
23Thunderbirds411000111819-12100000199020100010910-150.6251827450068102112161317528928387012940368814321.43%17570.59%3927173953.31%916181550.47%651129650.23%170394317147521440716
24Wolfpack21000010963110000007521000001021141.000915240068102112165875289283870682124464250.00%12191.67%0927173953.31%916181550.47%651129650.23%170394317147521440716
25Wranglers612011102526-1301001101214-2311010001312170.58325416610681021121617975289283870208635813731516.13%29679.31%1927173953.31%916181550.47%651129650.23%170394317147521440716
Total80243806543292324-3240121904122149157-840121902421143167-24760.475292483775506810211216251875289283870266187565517752786222.30%3156180.63%8927173953.31%916181550.47%651129650.23%170394317147521440716
_Since Last GM Reset80243806543292324-3240121904122149157-840121902421143167-24760.475292483775506810211216251875289283870266187565517752786222.30%3156180.63%8927173953.31%916181550.47%651129650.23%170394317147521440716
_Vs Conference48122704212168201-3324514021118196-15247130210187105-18380.396168281449406810211216146475289283870162152643210511783821.35%2104578.57%2927173953.31%916181550.47%651129650.23%170394317147521440716
_Vs Division1959021117082-121016011103343-10943010013739-2180.4747011718720681021121657975289283870642201197418912123.08%962277.08%2927173953.31%916181550.47%651129650.23%170394317147521440716

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8076L129248377525182661875655177550
All Games
GPWLOTWOTL SOWSOLGFGA
8024386543292324
Home Games
GPWLOTWOTL SOWSOLGFGA
4012194122149157
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4012192421143167
Last 10 Games
WLOTWOTL SOWSOL
720001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2786222.30%3156180.63%8
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
752892838706810211216
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
927173953.31%916181550.47%651129650.23%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
170394317147521440716


Last Played Games
Filter Tips
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
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
314Reign5Marlies3LR1BoxScore
527Canucks2Marlies3WXBoxScore
953Phantoms6Marlies3LR1BoxScore
1161Marlies4Phantoms5LXXBoxScore
1374Marlies1Griffins4LBoxScore
1581Wranglers8Marlies7LXR1BoxScore
1795Marlies4Wranglers3WXBoxScore
20109Marlies1Moose3LBoxScore
22117Reign4Marlies2LR1BoxScore
24130Marlies3Reign6LBoxScore
26140Rocket4Marlies2LBoxScore
28150Marlies5Icehogs3WBoxScore
31167Senators5Marlies4LXXBoxScore
34182Marlies4Wranglers2WR1BoxScore
36190Marlies5Admirals4WXBoxScore
37200Wranglers4Marlies2LR1BoxScore
41219Griffins6Marlies4LBoxScore
45237Checkers7Marlies5LBoxScore
50261Moose3Marlies5WBoxScore
53275Marlies3Crunch4LXBoxScore
55283Marlies4Condors6LBoxScore
57293Canucks3Marlies4WXXBoxScore
59300Marlies6Reign5WR1BoxScore
61314Marlies6Thunderbirds5WXXBoxScore
63324Bears4Marlies1LBoxScore
66339Marlies2Moose6LBoxScore
67350Little Stars8Marlies3LBoxScore
70367Marlies4Barracuda6LBoxScore
72376Wranglers2Marlies3WXXR1BoxScore
75393Marlies2Griffins1WBoxScore
77402Barracuda3Marlies4WXBoxScore
79412Marlies6Senators1WBoxScore
82427Canucks3Marlies4WBoxScore
84441Marlies5Wranglers7LR1BoxScore
86451Marlies6Punishers9LBoxScore
87458Phantoms3Marlies5WR1BoxScore
92480Americans4Marlies2LBoxScore
95498Silver Knights4Marlies5WXBoxScore
97508Marlies4Penguins2WBoxScore
99517Marlies3Icehogs4LBoxScore
101531Moose5Marlies2LBoxScore
104544Marlies2Canucks5LBoxScore
106557Phantoms3Marlies1LR1BoxScore
111580Condors3Marlies5WBoxScore
113592Marlies3Silver Knights2WBoxScore
115601Marlies3Moose8LBoxScore
116610Condors3Marlies2LBoxScore
120628Marlies3Eagles4LXBoxScore
121637Marlies2Comets6LBoxScore
122640Reign3Marlies4WXR1BoxScore
125663Reign5Marlies3LBoxScore
128680Marlies5Americans6LXBoxScore
130687Marlies4Little Stars6LBoxScore
131694Punishers5Marlies4LBoxScore
134712Comets2Marlies6WBoxScore
136721Marlies3Thunderbirds5LBoxScore
138734Marlies3Checkers2WBoxScore
140741Eagles5Marlies3LBoxScore
142756Marlies3Islander4LBoxScore
144768Marlies3Little Stars4LXBoxScore
145773Crunch1Marlies7WBoxScore
146786Marlies3Reign2WR1BoxScore
149798Rocket4Marlies3LBoxScore
151810Marlies2Wolfpack1WXXBoxScore
153819Marlies7Comets2WBoxScore
155826Marlies4Barracuda6LBoxScore
156831Senators1Marlies5WBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
160852Marlies3Rocket4LBoxScore
161857Icehogs6Marlies3LBoxScore
164870Marlies2Admirals4LBoxScore
167882Islander2Marlies3WBoxScore
170898Marlies2Bears1WBoxScore
171909Americans1Marlies3WBoxScore
176933Wolfpack5Marlies7WBoxScore
180955Admirals5Marlies4LBoxScore
183975Thunderbirds5Marlies4LXXBoxScore
188996Thunderbirds4Marlies5WBoxScore
1911010Marlies5Phantoms3WR1BoxScore
1971026Penguins1Marlies4WBoxScore
1981031Marlies3Phantoms6LR1BoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price7040
Attendance75,05136,479
Attendance PCT93.81%91.20%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 2788 - 92.94% 176,209$7,048,369$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,878,174$ 2,289,500$ 2,254,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
11,391$ 2,250,775$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 1 14,127$ 14,127$




Marlies Players Stat Leaders (Regular Season)

# Player Name 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

Marlies Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Marlies Career Team Stats

OverallHomeVisitor
Year 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

Marlies Players Stat Leaders (Play-Off)

# Player Name 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

Marlies Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA