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 Time	Tanner Rating	Tanner Avg.	Tanner StDev.
15:30	210
15:45	205
16:00	200
16:15	195
16:30	190	200	7.91
MIXCSR Time	MIXCSR Rating	MIXCSR Avg.	MIXCSR StDev.
16:09	197
16:12	196
16:15	195
16:18	194
16:21	193	195	1.58

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 60^th.

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

Race	Tanner Avg.	Tanner StDev	Tanner Rating	MIXCSR Avg.	MIXCSR StDev	MIXCSR Rating
1	200	7.9	202.1	195	1.6	195.6
2	200	7.9	196.2	195	1.6	194.1
3	200	7.9	190.0	195	1.6	199.2
4	200	7.9	193.4	195	1.6	192.5
5	200	7.9	206.8	195	1.6	195.7
6	200	7.9	201.8	195	1.6	196.1
7	200	7.9	171.6	195	1.6	194.9
8	200	7.9	189.2	195	1.6	195.9
9	200	7.9	205.5	195	1.6	197.0
10	200	7.9	203.8	195	1.6	192.6
11	200	7.9	192.3	195	1.6	196.5
12	200	7.9	196.9	195	1.6	196.4
13	200	7.9	198.5	195	1.6	195.6
14	200	7.9	203.2	195	1.6	194.1
15	200	7.9	193.9	195	1.6	192.6
16	200	7.9	199.3	195	1.6	193.2
17	200	7.9	208.7	195	1.6	194.2
18	200	7.9	213.7	195	1.6	194.6
19	200	7.9	212.6	195	1.6	197.1
20	200	7.9	206.3	195	1.6	193.9

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 Place	Team	Avg. Score	Avg. Place	Win %	Top 3 %
1	Kingston	32	1.0	95+	95+
2	Unionville-Sebewaing	68	2.1		95+
3	Ubly	80	2.9		95+
4	Dryden	107	4.7
5	Brown City	107	4.9
6	Harbor Beach	111	5.4
7	Deckerville	166	7.0

Projected Place	Grade	Name	Team	Avg. Place
1	10	Lilah Kiley	Kingston	1.3
2	12	Alberta Reinbold	Unionville-Sebewaing	3.4
3	10	Katie Sweeney	Ubly	3.6
4	12	Lily Lemanski	Marlette	3.9
5	12	Gracy Walker	Kingston	6.0
6	11	Reece Wruble	Harbor Beach	6.2
7	11	Kyra Beemer	Brown City	7.8
8	12	Zoe Van Rijn	Kingston	8.3
9	11	Julia Rogers	New Life Christian Academy	10.0
10	10	Cara Prusakiewicz	Dryden	10.4
11	11	Meeghan Flikkie	Kingston	10.8
12	10	Molly Walker	Kingston	10.9
13	11	Sarah Nimtz	Unionville-Sebewaing	12.0
14	11	Cambree Torma	Unionville-Sebewaing	13.6
15	12	Audrey Napolitano	Dryden	14.4
16	12	Erica Klee	Ubly	14.7
17	10	Hailey McGuire	Kingston	16.6
18	11	Megan Peter	Unionville-Sebewaing	19.4
19	11	Bridget Anderson	Harbor Beach	20.4
20	12	Aran Harris	Ubly	20.8
21	11	Emma Ramisch	Harbor Beach	22.5
22	12	Lily Finnigan	Dryden	22.9
23	10	HarLee Leasher	Brown City	23.2
24	11	Skylar Vincent	Brown City	24.9
25	9	Nicole Klee	Ubly	25.3
26	12	Emily Greyerbiehl	Ubly	27.9
27	10	Mya Garza	Deckerville	28.7
28	11	Danielle Hunt	Unionville-Sebewaing	28.7
29	12	Johanna Kubacki	Deckerville	29.3
30	10	Maleah Roth	Ubly	30.0

BOYS

Ranked Teams

#10 Harbor Beach

Projected Individual Qualifier Cutoff

15th place.

Projected Place	Team	Avg. Score	Avg. Place	Win %	Top 3 %
1	Harbor Beach	53	1.0	95+	95+
2	Dryden	97	2.5		93
3	Mayville	99	2.8		84
4	Marlette	111	3.7		23
5	Unionville-Sebewaing	143	5.7
6	Ubly	146	6.0
7	New Life Christian Academy	158	7.1
8	Kingston	163	7.2
9	Deckerville	194	8.9
10	Brown City	241	10.0

Projected Place	Grade	Name	Team	Avg. Place
1	10	Brody Karg	Harbor Beach	1.2
2	12	Aiden Fitchett	Dryden	2.5
3	10	Carson Burgess	Brown City	3.5
4	12	Utah Gusa	Ubly	4.4
5	11	Matthew Pasiak	Harbor Beach	4.4
6	11	Turlough Bennett	Marlette	6.8
7	12	Gavin Helgeson	Mayville	7.6
8	11	Zack Becker	Unionville-Sebewaing	8.6
9	11	Samuel Shatto	Harbor Beach	9.4
10	10	Michael Walsh	Ubly	10.4
11	11	Isaac Bignall	Unionville-Sebewaing	11.3
12	9	Thijs Van Rijn	Kingston	12.6
13	11	Noah Hall	Dryden	13.5
14	11	Joel Enos	Mayville	13.5
15	12	Ben Gura	New Life Christian Academy	16.3
16	10	Nino Perna	Marlette	17.1
17	10	Logan Romain	Dryden	18.0
18	9	Owen Wruble	Harbor Beach	18.3
19	9	Brennan Robinson	Kingston	18.8
20	11	Isaac Roggenbuck	Harbor Beach	21.2
21	11	Colin Beck	Deckerville	22.1
22	12	Sam Keller	New Life Christian Academy	22.4
23	12	Christopher Gonzales	Mayville	24.3
24	12	Jacob Bulgrien	Harbor Beach	26.4
25	11	Caden Meyer	Marlette	26.7
26	10	Kole Franzel	Mayville	27.9
27	12	Connor Wolff	Dryden	28.0
28	10	James Nelson	New Life Christian Academy	28.3
29	10	Luke Thomas	Marlette	28.4
30	9	Donovan Glasgow	Capac	28.5