Uncategorized

2023 Regional Projections: Buckley Regional

Finally, the start of the season we’ve all been waiting for. Throw out all the fast times from September, but apply all the lessons learned through the summer and fall. Regional week is here and with it comes the many projections and previews I’ll write.

Just as last year and throughout the season, I’m projecting these using race simulations. Through a season’s worth of speed ratings, one can determine a runner’s average rating and the variability of those ratings. Both those factors are then weighed towards more recent meets, which are then simulated thousands of times using a Monte Carlo analysis (also described by TullyRunners here). Over those thousands of race simulations, one can determine a team’s average place and average score, a runner’s average place, odds on winning, and odds on qualifying.

These are useful in cross country scenarios, where you have consistent runners and those who are a bit more up and down. For example:

Tanner TimeTanner RatingTanner Avg.Tanner StDev.
15:30210  
15:45205  
16:00200  
16:15195  
16:301902007.91
MIXCSR TimeMIXCSR RatingMIXCSR Avg.MIXCSR StDev.
16:09197  
16:12196  
16:15195  
16:18194  
16:211931951.58

Jacob at his best might be faster than I in four of the five races during the season. I’d almost never be All-State in Division 1, but he might contend for a top-5 spot or place 60th.

If we did 20 simulations, this is how it might turn out:

RaceTanner Avg.Tanner StDevTanner RatingMIXCSR Avg.MIXCSR StDevMIXCSR Rating
12007.9202.11951.6195.6
22007.9196.21951.6194.1
32007.9190.01951.6199.2
42007.9193.41951.6192.5
52007.9206.81951.6195.7
62007.9201.81951.6196.1
72007.9171.61951.6194.9
82007.9189.21951.6195.9
92007.9205.51951.6197.0
102007.9203.81951.6192.6
112007.9192.31951.6196.5
122007.9196.91951.6196.4
132007.9198.51951.6195.6
142007.9203.21951.6194.1
152007.9193.91951.6192.6
162007.9199.31951.6193.2
172007.9208.71951.6194.2
182007.9213.71951.6194.6
192007.9212.61951.6197.1
202007.9206.31951.6193.9

I’d win four times, but I’d never have the ability to win a title like he had in Race 18. He’s usually All-State, but may cost his team a title through his effort in Race 7.

The simulations give the possibilities of those scenarios and all the various scoring scripts. A sixth girl that can pop off on any certain day, a reliable boy who always runs 17-flat, you name it. Hopefully, they better elucidate our contenders, qualifiers, and how these races play out over the weekend.

But always remember, races aren’t run on paper or on a computer. These projections are meant to better our sport, give more attention where little is given. Although I take pride in their accuracy, this endeavor would be quite boring if it were always perfect. I look forward to these being proven wrong and I expect to hear about it as well.

SUMMER PREVIEW
MID-SEASON

GIRLS

Ranked Teams

#9 Buckley
#12 Grand Traverse Academy
#13 Mason County Eastern
#26 Leland

Projected Individual Qualifier Cutoff

18th place.

Projected PlaceTeamAvg. ScoreAvg. PlaceWin %Top 3 %
1Buckley431.37195+
2Grand Traverse Academy521.82995+
3Mason County Eastern702.995+
4Leland1054.1
5Frankfort1205.1
6Lake Leelanau St. Mary1305.8
7Pentwater1717.0

Projected PlaceGradeNameTeamAvg. Place
112Aiden HarrandBuckley1.0
211Ella KnudsenLeland2.2
39Addy ZellerBear Lake-Onekama3.9
410Kinsey PeerBuckley7.5
59Addison PatrzikGrand Traverse Academy7.6
610Lauren NiedzielskiMason County Eastern8.6
710Brooklynn FrazeeBuckley8.8
812Paige BellGrand Traverse Academy10.1
910Shenoah CollierGrand Traverse Academy10.7
1011Lucy ShoupMason County Eastern10.8
119Mikayla KulawiakBuckley11.3
1210Addison ChownykFrankfort12.4
139Natalie BurpeeLeland12.5
148Claire CouturierLake Leelanau St. Mary13.4
159Bailey StephenGrand Traverse Academy15.3
1610Jennifer KmiecikBear Lake-Onekama15.9
179Brailyn JohnsonMason County Eastern16.7
1812Abby KisslingBrethren20.3
199Addison MalburgMason County Eastern21.9
2010Natalie BrownBear Lake-Onekama22.8
219Kaylee SwansonBuckley23.0
2212Olivia WingMason County Eastern23.1
239Ellen SchwaigerLeland23.1
2410Sofia AlaimoFrankfort23.5
259Madison SmithGrand Traverse Academy24.8
2612Ava ButeraGrand Traverse Academy24.8
279Bailey CasePentwater25.4
289Tess HoedelGrand Traverse Academy25.7
2912Kendra CouturierLake Leelanau St. Mary26.9
3011Emily AlaimoMaple City Glen Lake28.2

BOYS

Ranked Teams

#5 Mason County Eastern
#11 Maple City Glen Lake
#19 Frankfort
#27 Pentwater

Projected Individual Qualifier Cutoff

17th place.

Projected PlaceTeamAvg. ScoreAvg. PlaceWin %Top 3 %
1Mason County Eastern601.095+95+
2Maple City Glen Lake862.195+
3Frankfort1032.995+
4Pentwater1294.4
5Leland1365.0
6Bear Lake-Onekama1496.0
7Lake Leelanau St. Mary1707.7
8Mesick1717.8
9Grand Traverse Academy1788.2
10Walkerville25010.0

Projected PlaceGradeNameTeamAvg. Place
111Mason SinkeBear Lake-Onekama1.8
212Abe VanDuinenPentwater2.6
39Kyle RedmanMesick3.3
411Colebrook SutherlandMaple City Glen Lake4.2
511Alex TyndallMason County Eastern4.6
69Ty RedmanMesick5.4
712Kaden ForwardBear Lake-Onekama6.4
812Mitchel DanielsPentwater8.7
99Sebastian DunawayFrankfort9.8
1011Carroll RobothamFrankfort10.6
1112Luke NiedzielskiMason County Eastern11.5
129Abraham FeeneyMaple City Glen Lake12.9
1311Henry MalburgMason County Eastern14.0
149Milo ShoupMason County Eastern15.0
1512Peter HybzaMason County Eastern15.5
1610Keith CromptonFrankfort15.7
1712Agustin CreamerLeland16.0
1810Liam McCawMaple City Glen Lake17.0
1911Greyson HoeflingerMason County Eastern19.6
2011Parker RubinGrand Traverse Academy20.1
2110Cody CouturierLake Leelanau St. Mary21.5
2210Matthew BentleyBuckley22.4
239Evan KeenLeland24.4
2410Oliver MitchellLake Leelanau St. Mary24.9
259Joel MartinMaple City Glen Lake27.2
269Aron MascorroWalkerville30.0
2711Ron HasenbankMason County Eastern30.2
2810Wyatt RobertsPentwater30.2
2910Easton NowakBear Lake-Onekama31.5
3010Jacob PlamondonMaple City Glen Lake32.2
Uncategorized

2023 Regional Projections: Wagener Park Regional

Finally, the start of the season we’ve all been waiting for. Throw out all the fast times from September, but apply all the lessons learned through the summer and fall. Regional week is here and with it comes the many projections and previews I’ll write.

Just as last year and throughout the season, I’m projecting these using race simulations. Through a season’s worth of speed ratings, one can determine a runner’s average rating and the variability of those ratings. Both those factors are then weighed towards more recent meets, which are then simulated thousands of times using a Monte Carlo analysis (also described by TullyRunners here). Over those thousands of race simulations, one can determine a team’s average place and average score, a runner’s average place, odds on winning, and odds on qualifying.

These are useful in cross country scenarios, where you have consistent runners and those who are a bit more up and down. For example:

Tanner TimeTanner RatingTanner Avg.Tanner StDev.
15:30210  
15:45205  
16:00200  
16:15195  
16:301902007.91
MIXCSR TimeMIXCSR RatingMIXCSR Avg.MIXCSR StDev.
16:09197  
16:12196  
16:15195  
16:18194  
16:211931951.58

Jacob at his best might be faster than I in four of the five races during the season. I’d almost never be All-State in Division 1, but he might contend for a top-5 spot or place 60th.

If we did 20 simulations, this is how it might turn out:

RaceTanner Avg.Tanner StDevTanner RatingMIXCSR Avg.MIXCSR StDevMIXCSR Rating
12007.9202.11951.6195.6
22007.9196.21951.6194.1
32007.9190.01951.6199.2
42007.9193.41951.6192.5
52007.9206.81951.6195.7
62007.9201.81951.6196.1
72007.9171.61951.6194.9
82007.9189.21951.6195.9
92007.9205.51951.6197.0
102007.9203.81951.6192.6
112007.9192.31951.6196.5
122007.9196.91951.6196.4
132007.9198.51951.6195.6
142007.9203.21951.6194.1
152007.9193.91951.6192.6
162007.9199.31951.6193.2
172007.9208.71951.6194.2
182007.9213.71951.6194.6
192007.9212.61951.6197.1
202007.9206.31951.6193.9

I’d win four times, but I’d never have the ability to win a title like he had in Race 18. He’s usually All-State, but may cost his team a title through his effort in Race 7.

The simulations give the possibilities of those scenarios and all the various scoring scripts. A sixth girl that can pop off on any certain day, a reliable boy who always runs 17-flat, you name it. Hopefully, they better elucidate our contenders, qualifiers, and how these races play out over the weekend.

But always remember, races aren’t run on paper or on a computer. These projections are meant to better our sport, give more attention where little is given. Although I take pride in their accuracy, this endeavor would be quite boring if it were always perfect. I look forward to these being proven wrong and I expect to hear about it as well.

SUMMER PREVIEW
MID-SEASON

GIRLS

Ranked Teams

#8 Kingston
#20 Unionville-Sebewaing
#23 Ubly

Projected Individual Qualifier Cutoff

Tons of USA, Kingston, and Ubly girls occupying the 11th-20th spots moves the expected cutoff to 19th.

Projected PlaceTeamAvg. ScoreAvg. PlaceWin %Top 3 %
1Kingston321.095+95+
2Unionville-Sebewaing682.195+
3Ubly802.995+
4Dryden1074.7
5Brown City1074.9
6Harbor Beach1115.4
7Deckerville1667.0

Projected PlaceGradeNameTeamAvg. Place
110Lilah KileyKingston1.3
212Alberta ReinboldUnionville-Sebewaing3.4
310Katie SweeneyUbly3.6
412Lily LemanskiMarlette3.9
512Gracy WalkerKingston6.0
611Reece WrubleHarbor Beach6.2
711Kyra BeemerBrown City7.8
812Zoe Van RijnKingston8.3
911Julia RogersNew Life Christian Academy10.0
1010Cara PrusakiewiczDryden10.4
1111Meeghan FlikkieKingston10.8
1210Molly WalkerKingston10.9
1311Sarah NimtzUnionville-Sebewaing12.0
1411Cambree TormaUnionville-Sebewaing13.6
1512Audrey NapolitanoDryden14.4
1612Erica KleeUbly14.7
1710Hailey McGuireKingston16.6
1811Megan PeterUnionville-Sebewaing19.4
1911Bridget AndersonHarbor Beach20.4
2012Aran HarrisUbly20.8
2111Emma RamischHarbor Beach22.5
2212Lily FinniganDryden22.9
2310HarLee LeasherBrown City23.2
2411Skylar VincentBrown City24.9
259Nicole KleeUbly25.3
2612Emily GreyerbiehlUbly27.9
2710Mya GarzaDeckerville28.7
2811Danielle HuntUnionville-Sebewaing28.7
2912Johanna KubackiDeckerville29.3
3010Maleah RothUbly30.0

BOYS

Ranked Teams

#10 Harbor Beach

Projected Individual Qualifier Cutoff

15th place.

Projected PlaceTeamAvg. ScoreAvg. PlaceWin %Top 3 %
1Harbor Beach531.095+95+
2Dryden972.593
3Mayville992.884
4Marlette1113.723
5Unionville-Sebewaing1435.7
6Ubly1466.0
7New Life Christian Academy1587.1
8Kingston1637.2
9Deckerville1948.9
10Brown City24110.0

Projected PlaceGradeNameTeamAvg. Place
110Brody KargHarbor Beach1.2
212Aiden FitchettDryden2.5
310Carson BurgessBrown City3.5
412Utah GusaUbly4.4
511Matthew PasiakHarbor Beach4.4
611Turlough BennettMarlette6.8
712Gavin HelgesonMayville7.6
811Zack BeckerUnionville-Sebewaing8.6
911Samuel ShattoHarbor Beach9.4
1010Michael WalshUbly10.4
1111Isaac BignallUnionville-Sebewaing11.3
129Thijs Van RijnKingston12.6
1311Noah HallDryden13.5
1411Joel EnosMayville13.5
1512Ben GuraNew Life Christian Academy16.3
1610Nino PernaMarlette17.1
1710Logan RomainDryden18.0
189Owen WrubleHarbor Beach18.3
199Brennan RobinsonKingston18.8
2011Isaac RoggenbuckHarbor Beach21.2
2111Colin BeckDeckerville22.1
2212Sam KellerNew Life Christian Academy22.4
2312Christopher GonzalesMayville24.3
2412Jacob BulgrienHarbor Beach26.4
2511Caden MeyerMarlette26.7
2610Kole FranzelMayville27.9
2712Connor WolffDryden28.0
2810James NelsonNew Life Christian Academy28.3
2910Luke ThomasMarlette28.4
309Donovan GlasgowCapac28.5
Uncategorized

2023 Regional Projections: Holly Regional

Finally, the start of the season we’ve all been waiting for. Throw out all the fast times from September, but apply all the lessons learned through the summer and fall. Regional week is here and with it comes the many projections and previews I’ll write.

Just as last year and throughout the season, I’m projecting these using race simulations. Through a season’s worth of speed ratings, one can determine a runner’s average rating and the variability of those ratings. Both those factors are then weighed towards more recent meets, which are then simulated thousands of times using a Monte Carlo analysis (also described by TullyRunners here). Over those thousands of race simulations, one can determine a team’s average place and average score, a runner’s average place, odds on winning, and odds on qualifying.

These are useful in cross country scenarios, where you have consistent runners and those who are a bit more up and down. For example:

Tanner TimeTanner RatingTanner Avg.Tanner StDev.
15:30210  
15:45205  
16:00200  
16:15195  
16:301902007.91
MIXCSR TimeMIXCSR RatingMIXCSR Avg.MIXCSR StDev.
16:09197  
16:12196  
16:15195  
16:18194  
16:211931951.58

Jacob at his best might be faster than I in four of the five races during the season. I’d almost never be All-State in Division 1, but he might contend for a top-5 spot or place 60th.

If we did 20 simulations, this is how it might turn out:

RaceTanner Avg.Tanner StDevTanner RatingMIXCSR Avg.MIXCSR StDevMIXCSR Rating
12007.9202.11951.6195.6
22007.9196.21951.6194.1
32007.9190.01951.6199.2
42007.9193.41951.6192.5
52007.9206.81951.6195.7
62007.9201.81951.6196.1
72007.9171.61951.6194.9
82007.9189.21951.6195.9
92007.9205.51951.6197.0
102007.9203.81951.6192.6
112007.9192.31951.6196.5
122007.9196.91951.6196.4
132007.9198.51951.6195.6
142007.9203.21951.6194.1
152007.9193.91951.6192.6
162007.9199.31951.6193.2
172007.9208.71951.6194.2
182007.9213.71951.6194.6
192007.9212.61951.6197.1
202007.9206.31951.6193.9

I’d win four times, but I’d never have the ability to win a title like he had in Race 18. He’s usually All-State, but may cost his team a title through his effort in Race 7.

The simulations give the possibilities of those scenarios and all the various scoring scripts. A sixth girl that can pop off on any certain day, a reliable boy who always runs 17-flat, you name it. Hopefully, they better elucidate our contenders, qualifiers, and how these races play out over the weekend.

But always remember, races aren’t run on paper or on a computer. These projections are meant to better our sport, give more attention where little is given. Although I take pride in their accuracy, this endeavor would be quite boring if it were always perfect. I look forward to these being proven wrong and I expect to hear about it as well.

SUMMER PREVIEW
MID-SEASON

GIRLS

Ranked Teams

#16 Linden
#18 Dearborn Divine Child
#26 Pontiac Notre Dame Prep

Projected Individual Qualifier Cutoff

18th place.

Projected PlaceTeamAvg. ScoreAvg. PlaceWin %Top 3 %
1Dearborn Divine Child541.46195+
2Linden561.63995+
3Pontiac Notre Dame Prep803.095+
4Detroit Country Day1184.0
5Bloomfield Hills Cranbrook-Kingswood1585.9
6Pinckney1606.2
7Bloomfield Hills Marian1696.9
8Orchard Lake St. Mary’s1777.6
9Lake Fenton1868.4
10Garden City32010.0
11Detroit Cody36211.0
12Dearborn Henry Ford Academy38012.0

Projected PlaceGradeNameTeamAvg. Place
111Mea D’AgostinoOrchard Lake St. Mary’s1.6
29Jaelyn RayPinckney2.2
311Maria NunningPontiac Notre Dame Prep3.4
411Chloe JosephsonLinden3.7
512Kirsten KossDearborn Divine Child6.5
611Kathryn KurtinaitisDearborn Divine Child7.6
79Melody MeckstrothLinden7.9
811Kayla SladeDearborn Divine Child9.5
99Diya GoyalBloomfield Hills Cranbrook-Kingswood9.9
1010Anna KujansuuDearborn Divine Child10.6
1111Nell StoverDetroit Country Day12.5
129Addison JosephsonLinden12.6
1311Skylar VanheckePontiac Notre Dame Prep12.9
149Sidney ShepardLinden14.6
1511Claire HellerDetroit Country Day14.7
169Claire DunnPontiac Notre Dame Prep15.3
1712Reagan BrooksLinden17.4
1812Molly O’BrienBloomfield Hills Marian18.9
1911Mary LaroccaPontiac Notre Dame Prep19.3
209Elliana HuftonLake Fenton19.9
2111Kate PaluszewskiDearborn Divine Child21.4
2212Chloe KurschatBloomfield Hills Cranbrook-Kingswood22.2
2312Ava FahrenkopfLinden23.2
2411Madalynn KarsiesPinckney24.7
2510Elizabeth SalinasDearborn Divine Child26.3
269Georgia HopkinsDetroit Country Day26.3
2711Jillian WygonikDearborn Divine Child27.5
2812Kaitlyn HatfieldLake Fenton28.8
299Lucille ClarkBloomfield Hills Marian29.9
309Charlotte HartleyDetroit Country Day31.9

BOYS

Ranked Teams

#5 Pinckney

Projected Individual Qualifier Cutoff

19th Place.

Projected PlaceTeamAvg. ScoreAvg. PlaceWin %Top 3 %
1Pinckney281.095+95+
2Detroit Country Day1032.495+
3Dearborn Divine Child1082.984
4Bloomfield Hills Cranbrook-Kingswood1244.121
5Orchard Lake St. Mary’s1334.8
6Lake Fenton1566.2
7Pontiac Notre Dame Prep1697.1
8Linden1777.6
9Redford Union2509.0
10Melvindale29810.1
11Dearborn Henry Ford Academy31611.1
12Garden City32511.8
13Detroit Henry Ford36813.0
14Detroit Southeastern Tech41714.0
15Detroit Cody47315.0

Projected PlaceGradeNameTeamAvg. Place
112Evan LoughridgePinckney1.3
212Solomon KwartowitzBloomfield Hills Cranbrook-Kingswood3.1
311Colin MurrayDearborn Divine Child3.3
412Nolan PinionLake Fenton4.5
512Paul MoorePinckney4.6
612Ethan SandulaPinckney5.2
711Jacob HopkinsDetroit Country Day7.9
89Cole McCrawPinckney9.3
912Joshua SimpsonOrchard Lake St. Mary’s9.9
1012Arnot HellerDetroit Country Day10.0
1111Zach NewmanPinckney11.6
1211Kyle OsbornePinckney12.2
1312Parker HaysPinckney12.7
1411Isaak BrookPontiac Notre Dame Prep13.5
1512Ian MartinLinden13.7
1611Tamer ZahrDearborn Divine Child17.0
179Omar ElbashirDetroit Country Day17.6
1812Eric ShanBloomfield Hills Cranbrook-Kingswood18.9
1912Eamon KennedyDearborn Henry Ford Academy20.2
2010Jake YonoOrchard Lake St. Mary’s20.6
219Cooper SteckrothLake Fenton21.3
2210Bela MatyusOrchard Lake St. Mary’s21.5
2311Blaise GoodingLinden23.3
2411Nicholas NakicDearborn Divine Child25.7
2511Ryan WojichowskiPontiac Notre Dame Prep27.3
2611Alex KitsopanidisDetroit Country Day27.6
2711Jaime SaucedoMelvindale27.7
2812Krish KalmadiBloomfield Hills Cranbrook-Kingswood28.0
2911Maximiliano JuarezDearborn Divine Child30.6
3012Joshua Sharp-PeltoGarden City31.2

SUMMER PREVIEW
MID-SEASON

GIRLS

Ranked Teams

#3 Brighton
#13 Ann Arbor Skyline
#15 Davison
#20 Dexter

Projected Individual Qualifier Cutoff

Anywhere from 20th to 22nd place.

Projected PlaceTeamAvg. ScoreAvg. PlaceWin %Top 3 %
1Brighton321.095+95+
2Ann Arbor Skyline782.491
3Davison872.981
4Dexter983.728
5Grand Blanc1255.3
6Hartland1315.7
7Fenton1717.0
8Lapeer2558.5
9Howell2608.8
10Holly28010.0
11Flushing29610.7
12Swartz Creek37212.0

Projected PlaceGradeNameTeamAvg. Place
110Lydia LaMarraBrighton2.8
211Elle BissettBrighton3.8
312Carrigan EberlyBrighton4.0
411Grace TykockiGrand Blanc4.3
511Alena BlumbergDexter5.5
612Allison MayerAnn Arbor Skyline6.1
712Paige McArdleDavison7.3
89Ava GoodmanHartland9.7
912Nina FrostFenton10.4
1010Juliet LewisBrighton10.7
119Becca van LentAnn Arbor Skyline10.8
1212Sydney SmithDavison13.8
1312Gabrielle BolithoBrighton14.0
1412Megan KowalskiBrighton14.7
1510Nevaeh PolovinaDavison15.5
169Irie ScraseAnn Arbor Skyline16.4
1711Addison BruckmanDexter17.7
1812Nikki CarothersBrighton17.7
1911Annabel O’HaverDexter18.8
209Becca vanLentAnn Arbor Skyline19.9
2112Brooke LemosDavison22.7
2210Reese CanadaFenton24.2
2312Samantha WogamanGrand Blanc25.0
2411Ayla BalazerAnn Arbor Skyline25.1
2512Samantha ShaverGrand Blanc25.5
269Kodie SnyderDexter26.2
2710Elliana NeuerHartland26.8
289Brooklyn WiltseDavison27.7
2911Zoe HowardHartland29.4
3010Sarah AlbrightGrand Blanc30.3

BOYS

Ranked Teams

#2 Brighton

Projected Individual Qualifier Cutoff

20th place.

Projected PlaceTeamAvg. ScoreAvg. PlaceWin %Top 3 %
1Brighton321.095+95+
2Dexter882.395+
3Howell952.895+
4Ann Arbor Skyline1274.4
5Davison1364.7
6Hartland1615.8
7Holly2097.3
8Grand Blanc2308.3
9Flushing2388.8
10Lapeer2569.8
11Fenton27911.2
12Swartz Creek28711.7
13Jackson35813.0

Projected PlaceGradeNameTeamAvg. Place
112Brandon AndersonDexter2.2
212Tyler LangleyBrighton3.1
312Luke SulimanAnn Arbor Skyline4.2
49Jack MacGregorHowell4.3
512Iain ForrestDavison4.5
612Luke CampbellBrighton4.9
711Brady MillingtonBrighton7.7
811Tyler BrockBrighton8.4
911Elijah ForbordBrighton10.3
1011Tyler OutlawBrighton10.5
1112Mason JettAnn Arbor Skyline10.6
1212Bode CooperBrighton11.9
1311James LatstetterFlushing13.7
1411Julian LinebaughDexter15.4
1511Jacob EssenmacherLapeer16.5
1611Lucas WoodHowell17.3
1711Caleb SnyderDexter17.4
1812Carson CookHartland18.2
1911Drake WallaceHowell20.6
2011Jacob HuntoonFenton23.2
2110Griffin GoodFlushing25.1
2211Maxwell MerrillGrand Blanc25.6
2312Gavin SmithDavison25.7
2412Noah DeLandHowell26.4
2512Liam HooverHowell26.9
269Trevor MurphyHolly27.2
2710Bruno CifaldiAnn Arbor Skyline27.4
2811Elijah SmithDexter28.2
2911Scott SmithDexter28.6
3012Anthony MainiFenton28.9