Your STHS is out of Date! Please update your STHS version!
Login

Toronto Marlies
GP: 7 | W: 3 | L: 4
GF: 19 | GA: 24 | PP%: 20.00% | PK%: 72.41%
GM : Flavio | Morale : 11 | Team Overall : 60
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Utica Comets
6-7-0, 12pts
5
FINAL
2 Toronto Marlies
3-4-0, 6pts
Team Stats
L1StreakL2
2-5-0Home Record0-3-0
4-2-0Home Record3-1-0
5-5-0Last 10 Games3-4-0
3.62Goals Per Game2.71
3.15Goals Against Per Game3.43
25.45%Power Play Percentage20.00%
75.61%Penalty Kill Percentage72.41%
Toronto Marlies
3-4-0, 6pts
2
FINAL
4 Utica Comets
6-7-0, 12pts
Team Stats
L2StreakL1
0-3-0Home Record2-5-0
3-1-0Home Record4-2-0
3-4-0Last 10 Games5-5-0
2.71Goals Per Game3.62
3.43Goals Against Per Game3.15
20.00%Power Play Percentage25.45%
72.41%Penalty Kill Percentage75.61%
Team Leaders
Goals
Joseph Blandisi
3
Assists
Conor Timmins
8
Points
Conor Timmins
8
Plus/Minus
Joseph Blandisi
3
Wins
Matt Murray
3
Save Percentage
Matt Murray
0.918

Team Stats
Goals For
19
2.71 GFG
Shots For
250
35.71 Avg
Power Play Percentage
20.0%
5 GF
Offensive Zone Start
41.0%
Goals Against
24
3.43 GAA
Shots Against
280
40.00 Avg
Penalty Kill Percentage
72.4%%
8 GA
Defensive Zone Start
43.1%
Team Info

General ManagerFlavio
CoachJohn Gruden
DivisionNorth Division
ConferenceEastern Conference
Captain
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance2,975
Season Tickets0


Roster Info

Pro Team34
Farm Team18
Contract Limit52 / 70
Prospects11


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 #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 Average
1Dylan Gambrell0X100.00774086667363835871696077546158047670281775,000$
2Kieffer Bellows0XX100.00715183647360645852666166555757047640261775,000$
3Logan Shaw0X100.00555765636966646355616159587062047620321775,000$
4Alex Steeves0X100.00555866646366646155596159545855047610251775,000$
5Bobby McMann0X100.00585669627063605854586062546258047610281775,000$
6Joseph Blandisi0X100.00565764596165635970585962546760047600301775,000$
7Kyle Clifford0XX100.00616270607461655754595761547562047600331775,000$
8Fraser Minten0XXX100.006060606060606060606060606060600476002031,300,000$
9Easton Cowan (R)0XXX100.00606060606060606060606060606060047600191775,000$
10Braeden Kressler (R)0X100.00606060606060606060606060606060047600211775,000$
11Matthew Knies0XX100.005438675279675452485850575151550475602211,100,000$
12Ryan Tverberg0X100.00515165515952525152515157515149047520221775,000$
13Jake Muzzin0X100.00704076669077725740645579547765044680351775,000$
14Simon Benoit0X100.00816782577778825740695983545758042680261775,000$
15Conor Timmins0X100.00664283667670615940735675545657047660261775,000$
16William Lagesson0X100.00596272607166655840615769546258048620281775,000$
17Maxime Lajoie0X100.00555666606566646040605761546257047600271775,000$
18Noah Chadwick (R)0X100.00606060606060606060606060606060047600191775,000$
Scratches
1Josiah Slavin0XXX100.00545667576466645755565859546056024590261775,000$
2Max Ellis0XX100.00555567575660605655555761545654024570241775,000$
3Zach Solow0XX100.00565466555758585555545560546056024560261775,000$
4Dmitri Ovchinnikov0XXX100.00545468545655545455545461545352024550221775,000$
5David Farrance0X100.00555467586263615740575560555855024580251775,000$
6William Villeneuve0X100.00555462566061605744575560545453024570221775,000$
7Matteo Pietroniro0X100.00565565556261605440545460546056024570261775,000$
8Mikko Kokkonen0X100.00555462556259585544555458545553024560231775,000$
9Marshall Rifai0X100.00545257556064635438535358515853024560261775,000$
10Tommy Miller0X100.00515165536159575238525158515652024540251775,000$
11Topi Niemela0X100.00515165525452525138515157515149024530221775,000$
TEAM AVERAGE100.0059546859656362575059576355605703859
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 Average
1Matt Murray0100.0076707189797381708272836868052760302775,000$
2Keith Petruzzelli0100.0067666786666567666567666369052670251775,000$
Scratches
1Joseph Woll0100.00645959727157716265575859550346402611,000,000$
2Artur Akhtyamov (R)0100.0060606060606060606060606060034600231775,000$
3Dennis Hildeby0100.0051515173615162515552625148034550231775,000$
TEAM AVERAGE100.006461627667616862656266606004164
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
John Gruden68756468777273USA527500,000$


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
1Conor TimminsToronto Marlies (TOR)D7088-140912173100%1215922.800441221000019000%000001.0000000011
2William LagessonToronto Marlies (TOR)D7246-1001010125616.67%916323.40202821000024000%000000.7300000001
3Dylan GambrellToronto Marlies (TOR)C713414017283010273.33%414020.020006200002190050.87%23000100.5700000100
4Joseph BlandisiToronto Marlies (TOR)C731432049143521.43%0557.9400001000001054.29%7000001.4400000100
5Logan ShawToronto Marlies (TOR)C7044-2201015247170%214020.000445230000210041.62%17300000.5700000000
6Noah ChadwickToronto Marlies (TOR)D7134-1120266113109.09%1314620.93101722000018010%000000.5500000010
7Jake MuzzinToronto Marlies (TOR)D703302014963100%811516.4700000000010000%000000.5200000000
8Kieffer BellowsToronto Marlies (TOR)LW/RW721314095245188.33%114120.250005200001210033.33%1200000.4200000100
9Kyle CliffordToronto Marlies (TOR)LW/RW7213-3001152071110.00%011917.12101623000021016.67%600000.5000000010
10Simon BenoitToronto Marlies (TOR)D7123011511913147.69%510515.060000000002000%000000.5700010000
11Alex SteevesToronto Marlies (TOR)C7202-320481341115.38%112517.890003210000240036.57%17500000.3200000000
12Bobby McMannToronto Marlies (TOR)C720200014102820.00%010314.7700000000040083.33%600000.3900000001
13Maxime LajoieToronto Marlies (TOR)D7022-11001510104100%1114620.93011623000018000%000000.2700000000
14Fraser MintenToronto Marlies (TOR)C/LW/RW7022-3207510480%18111.6900000000010066.67%600000.4900000000
15Matthew KniesToronto Marlies (TOR)LW/RW71123207291411.11%1537.690000000000000%300000.7400000000
16Braeden KresslerToronto Marlies (TOR)C7202-3402031651012.50%111716.76101623000001041.67%1200000.3400000000
17Ryan TverbergToronto Marlies (TOR)C7000320402120%0537.630000000000000%10000000000000
18Easton CowanToronto Marlies (TOR)C/LW/RW7000-3002019430%08011.4600000000000083.33%60000000000000
Team Total or Average126193554-10635199141250721747.60%69204916.2759146422600031913145.00%70000100.5300010333
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
1Matt MurrayToronto Marlies (TOR)73400.9183.2941920232790010070000
Team Total or Average73400.9183.294192023279001070000


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 AverageSalary Ave 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
Alex SteevesToronto Marlies (TOR)C2510.12.1999No89 Kg183 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Artur AkhtyamovToronto Marlies (TOR)G2331.10.2001Yes76 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Bobby McMannToronto Marlies (TOR)C2815.06.1996No95 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Braeden KresslerToronto Marlies (TOR)C2105.01.2003Yes79 Kg175 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Conor TimminsToronto Marlies (TOR)D2618.09.1998No92 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
David FarranceToronto Marlies (TOR)D2523.06.1999No86 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Dennis HildebyToronto Marlies (TOR)G2319.08.2001No106 Kg198 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Dmitri OvchinnikovToronto Marlies (TOR)C/LW/RW2219.08.2002No74 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Dylan GambrellToronto Marlies (TOR)C2826.08.1996No84 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link / NHL Link
Easton CowanToronto Marlies (TOR)C/LW/RW1920.05.2005Yes84 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Fraser MintenToronto Marlies (TOR)C/LW/RW2005.07.2004 06:31:35No87 Kg188 CMNoNoN/ANoNo3FalseFalsePro & Farm1,300,000$1,300,000$0$0$No1,300,000$1,300,000$-------NoNo-------
Jake MuzzinToronto Marlies (TOR)D3521.02.1989No103 Kg191 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Joseph BlandisiToronto Marlies (TOR)C3018.07.1994No83 Kg183 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Joseph WollToronto Marlies (TOR)G2612.07.1998No92 Kg191 CMNoNoN/ANoNo1FalseFalsePro & Farm1,000,000$1,000,000$0$0$No------------------Link
Josiah SlavinToronto Marlies (TOR)C/LW/RW2631.12.1998No86 Kg191 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Keith PetruzzelliToronto Marlies (TOR)G2509.02.1999No84 Kg196 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Kieffer BellowsToronto Marlies (TOR)LW/RW2610.06.1998No89 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Kyle CliffordToronto Marlies (TOR)LW/RW3313.01.1991No99 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Logan ShawToronto Marlies (TOR)C3205.10.1992No94 Kg193 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Marshall RifaiToronto Marlies (TOR)D2616.03.1998No86 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Matt MurrayToronto Marlies (TOR)G3025.05.1994No92 Kg196 CMNoNoN/ANoNo2FalseFalsePro & Farm775,000$775,000$0$0$No775,000$--------No--------Link
Matteo PietroniroToronto Marlies (TOR)D2620.10.1998No84 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Matthew KniesToronto Marlies (TOR)LW/RW2217.10.2002No95 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm1,100,000$1,100,000$0$0$No------------------Link
Max EllisToronto Marlies (TOR)LW/RW2418.01.2000No78 Kg175 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Maxime LajoieToronto Marlies (TOR)D2705.11.1997No89 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Mikko KokkonenToronto Marlies (TOR)D2318.01.2001No91 Kg183 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Noah ChadwickToronto Marlies (TOR)D1910.05.2005Yes91 Kg193 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Ryan TverbergToronto Marlies (TOR)C2230.01.2002No86 Kg183 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Simon BenoitToronto Marlies (TOR)D2619.09.1998No92 Kg191 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link / NHL Link
Tommy MillerToronto Marlies (TOR)D2506.03.1999No88 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Topi NiemelaToronto Marlies (TOR)D2225.03.2002No77 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
William LagessonToronto Marlies (TOR)D2822.02.1996No94 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
William VilleneuveToronto Marlies (TOR)D2220.03.2002No83 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Zach SolowToronto Marlies (TOR)LW/RW2606.11.1998No80 Kg175 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3425.3288 Kg185 CM1.09806,618$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Kieffer BellowsDylan GambrellBobby McMann33122
2Braeden KresslerLogan ShawKyle Clifford30122
3Fraser MintenAlex SteevesEaston Cowan25122
4Matthew KniesJoseph BlandisiRyan Tverberg12122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Conor TimminsWilliam Lagesson33122
2Noah ChadwickMaxime Lajoie30122
3Jake MuzzinSimon Benoit25122
4Conor TimminsWilliam Lagesson12122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Kieffer BellowsDylan GambrellAlex Steeves50122
2Braeden KresslerLogan ShawKyle Clifford50122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Conor TimminsWilliam Lagesson50122
2Noah ChadwickMaxime Lajoie50122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Dylan GambrellKieffer Bellows50122
2Alex SteevesLogan Shaw50122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Conor TimminsWilliam Lagesson50122
2Noah ChadwickMaxime Lajoie50122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Dylan Gambrell50122Conor TimminsWilliam Lagesson50122
2Kieffer Bellows50122Noah ChadwickMaxime Lajoie50122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Dylan GambrellKieffer Bellows50122
2Alex SteevesLogan Shaw50122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Conor TimminsWilliam Lagesson50122
2Noah ChadwickMaxime Lajoie50122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Kieffer BellowsDylan GambrellLogan ShawConor TimminsWilliam Lagesson
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Kieffer BellowsDylan GambrellLogan ShawConor TimminsWilliam Lagesson
Extra Forwards
Normal PowerPlayPenalty Kill
Joseph Blandisi, Braeden Kressler, Alex SteevesJoseph Blandisi, Braeden KresslerAlex Steeves
Extra Defensemen
Normal PowerPlayPenalty Kill
Conor Timmins, William Lagesson, Noah ChadwickConor TimminsWilliam Lagesson, Noah Chadwick
Penalty Shots
Dylan Gambrell, Kieffer Bellows, Bobby McMann, Logan Shaw, Alex Steeves
Goalie
#1 : Matt Murray, #2 : Keith Petruzzelli
Custom OT Lines Forwards
Dylan Gambrell, Kieffer Bellows, Fraser Minten, Logan Shaw, Alex Steeves, Bobby McMann, Bobby McMann, Easton Cowan, Kyle Clifford, Joseph Blandisi, Braeden Kressler
Custom OT Lines Defensemen
Conor Timmins, William Lagesson, Noah Chadwick, Maxime Lajoie, Simon Benoit


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
1Utica Comets734000001924-530300000412-8431000001512360.4291935541082902508476900280696519925520.00%29872.41%012728744.25%13130243.38%5711151.35%160103163579649
Total734000001924-530300000412-8431000001512360.4291935541082902508476900280696519925520.00%29872.41%012728744.25%13130243.38%5711151.35%160103163579649
_Since Last GM Reset734000001924-530300000412-8431000001512360.4291935541082902508476900280696519925520.00%29872.41%012728744.25%13130243.38%5711151.35%160103163579649
_Vs Conference734000001924-530300000412-8431000001512360.4291935541082902508476900280696519925520.00%29872.41%012728744.25%13130243.38%5711151.35%160103163579649

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
76L2193554250280696519910
All Games
GPWLOTWOTL SOWSOLGFGA
73400001924
Home Games
GPWLOTWOTL SOWSOLGFGA
3030000412
Visitor Games
GPWLOTWOTL SOWSOLGFGA
43100001512
Last 10 Games
WLOTWOTL SOWSOL
340000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
25520.00%29872.41%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
84769008290
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
12728744.25%13130243.38%5711151.35%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
160103163579649


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
12Toronto Marlies5Utica Comets3WBoxScore
310Toronto Marlies4Utica Comets2WBoxScore
518Utica Comets4Toronto Marlies1LBoxScore
726Utica Comets3Toronto Marlies1LBoxScore
934Toronto Marlies4Utica Comets3WBoxScore
1142Utica Comets5Toronto Marlies2LBoxScore
1350Toronto Marlies2Utica Comets4LBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance6,0002,924
Attendance PCT100.00%97.47%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
4 2975 - 99.16% 84,620$253,860$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
0$ 2,742,500$ 2,742,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 0$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 0$ 0$




Toronto 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

Toronto Marlies Goalies Stat Leaders (Regular Season)

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

Toronto 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

Toronto 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

Toronto Marlies Goalies Stat Leaders (Play-Off)

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