The accuracy of this simulation can be improved if some basic updates are implemented, such as:
(1) fill in the missing athletes, e.g., Hedengren; (2) make some warranted finer adjustments in the expected top 7’s for each team, e.g. Napoleon’s rating should be no less than 15:33; (3) add in some expected fill-in athletes, particularly after the 3’s, to get an idea on the placements separation;
(4) limit each team to just seven athletes.
There seems to be a bug when posting LACCTiC simulations: with low sticks previously deleted, they still get put back in when sharing the simulation.
LACCTiC simulations could be greatly improved if they are manually modified, particularly in the early season, to account for missing athletes, athletes that haven’t yet competed, etc.
Because of some current limitations in being able to modify and share LACCTiC simulations, a running spreadsheet with updated LACCTiC data would be a nice tool to share, if anyone is so inclined to create/update such a spreadsheet.👍
The above simulation basically includes just the current LACCTiC Ratings of the top seven athletes from the expected Top 5 Teams. Results for the above simulation are: 1 NC State 40 2 Florida 60 3 Oregon 73 4 New Mexico 74 5 BYU 89
The above simulation basically includes just the current LACCTiC Ratings of the top seven athletes from the expected Top 5 Teams. Results for the above simulation are: 1 NC State 40 2 Florida 60 3 Oregon 73 4 New Mexico 74 5 BYU 89
Let’s try this again. If we simply have LACCTiC simulate current ratings for the expected Top 5 Teams, we get the following result:
1 NC State 40 2 Florida 55 3 Oregon 68 4 BYU 84 5 New Mexico 96
Note, that simulation does not include Hedengren or D. Cherotich from Oregon, currently having no results this season, and thus, without provision to include them in LACCTiC.
. If we simply have LACCTiC simulate current ratings for the expected Top 5 Teams, we get the following result:
1 NC State 40 2 Florida 55 3 Oregon 68 4 BYU 84 5 New Mexico 96
Note, that simulation does not include Hedengren or D. Cherotich from Oregon, currently having no results this season, and thus, without provision to include them in LACCTiC.
That simulation included Hartman, Hutchins, and Ayyildiz. Adding in Kosgei gives: 1 NC State 45 2 Florida 60 3 Oregon 73 4 New Mexico 74 5 BYU 89
That’s with LACCTiC’s team top 7’s being:
NC State: Hartman, Gapes, Michalak, Putman, Rauber, Napoleon, Englehardt (Napoleon will likely move up in this lineup)
Florida: Olemomoi, J. Chepkoech, Wilson, D. Chepkoech, Gilmore, Wells, Morley
Oregon: Cherubet, Ayyildiz, Thompson, Frias, Thorsett, Clute, Ince (D. Cherotich not included)
New Mexico: Kosgei, Jepngetich, Jansen, Seguin, Nisoli, Wood, Kirarei
Interesting. I expect Fleur Templier to be a contender for NC State’s lineup at the end of the year. She was 11th in last year’s west regional when she was at Portland. Kaylie Armitage may also be in that 7. The 5-7 spots on the team are very much up in the air.
Interesting. I expect Fleur Templier to be a contender for NC State’s lineup at the end of the year. She was 11th in last year’s west regional when she was at Portland. Kaylie Armitage may also be in that 7. The 5-7 spots on the team are very much up in the air.
Those 4-7’s are all close enough that swapping them will not affect much change on the team results. Napoleon as the 3-4 will improve their score.
If we include the teams of LACCTiC’s current Top 20 athletes, we get: 1 NC State 97 2 Florida 119 3 Alabama 127 4 Oregon 135 5 New Mexico 139 6 BYU 168 7 Stanford 179 8 Iowa State 190 9 Washington State 217 10 Tulane 260 11 Clemson 260 12 West Virginia 293 13 Tennessee 300 14 Arkansas 309
If we include the teams of LACCTiC’s current Top 20 athletes, we get: 1 NC State 97 2 Florida 119 3 Alabama 127 4 Oregon 135 5 New Mexico 139 6 BYU 168 7 Stanford 179 8 Iowa State 190 9 Washington State 217 10 Tulane 260 11 Clemson 260 12 West Virginia 293 13 Tennessee 300 14 Arkansas 309
The accuracy of this simulation can be improved if some basic updates are implemented, such as:
(1) fill in the missing athletes, e.g., Hedengren; (2) make some warranted finer adjustments in the expected top 7’s for each team, e.g. Napoleon’s rating should be no less than 15:33; (3) add in some expected fill-in athletes, particularly after the 3’s, to get an idea on the placements separation;
(4) limit each team to just seven athletes.
There seems to be a bug when posting LACCTiC simulations: with low sticks previously deleted, they still get put back in when sharing the simulation.
Any simulation that doesn’t have Hedengren running and BYU winning handily is just that - a simulation.
This is all a laudable effort but I fear fruitless at this point. Athlete's weighting are affected a lot by early season results, many of which appear very inferior to what they have shown in the past. Whether that is their current fitness, or reflects the affects of heavy training is an unknown. I think for many of the top teams the capabilities of their top 4 runners are known - but the questions are where are the 5th runners, whose improvement from past results is not known. We have seen some results for NC state, but nothing really for OR, BYU, NM and maybe FL. So it is all a guess (to me) at this point.
I continue to think the top 3-4 for OR, NC St, BYU, FL (and maybe NM) appear 1) very strong and 2) pretty close in likely scoring (in total).
This post was edited 10 minutes after it was posted.
Reason provided:
added FL
The accuracy of this simulation can be improved if some basic updates are implemented, such as:
(1) fill in the missing athletes, e.g., Hedengren; (2) make some warranted finer adjustments in the expected top 7’s for each team, e.g. Napoleon’s rating should be no less than 15:33; (3) add in some expected fill-in athletes, particularly after the 3’s, to get an idea on the placements separation;
(4) limit each team to just seven athletes.
There seems to be a bug when posting LACCTiC simulations: with low sticks previously deleted, they still get put back in when sharing the simulation.
Any simulation that doesn’t have Hedengren running and BYU winning handily is just that - a simulation.
Of course, BYU will move up when Hedengren is added; I already showed the effect of adding Kosgei.
This is all a laudable effort but I fear fruitless at this point. ... So it is all a guess (to me) at this point.
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And yet, you have probably looked at your personal spreadsheet upside down and sideways, eh? 😆
well yes, as opposed to going with the LAACTiC data. It is basing any conclusion from that data at this point I find fruitless. and, no offense, scoring just 5 teams and ignoring all the other runners can distort results. So at a minimum go with the prediction from the "whole field".
This post was edited 2 minutes after it was posted.
“LACCTiC simulations could be greatly improved if they are manually modified, particularly in the early season, to account for missing athletes, athletes that haven’t yet competed, etc.”
That’s what this discussion is about, to try and improve LACCTiC’s current simulation in order to get a better prediction of the likely outcome.
Based on everything I’ve seen so far, NC State is solidly the favorite, as LACCTiC is predicting.
Go ahead and hand them the trophy now, if you please.
And yet, you have probably looked at your personal spreadsheet upside down and sideways, eh? 😆
well yes, as opposed to going with the LAACTiC data. It is basing any conclusion from that data at this point I find fruitless. and, no offense, scoring just 5 teams and ignoring all the other runners can distort results. So at a minimum go with the prediction from the "whole field".
Apart from just throwing the whole field up, the progressive additions above gives the reader an idea on how results are influenced, particularly for the teams of interest, I.e., those with a decent shot of making the top three rungs of the podium, without getting buried in the ‘noise’ of early season data.
“LACCTiC simulations could be greatly improved if they are manually modified, particularly in the early season, to account for missing athletes, athletes that haven’t yet competed, etc.”
That’s what this discussion is about, to try and improve LACCTiC’s current simulation in order to get a better prediction of the likely outcome.
Based on everything I’ve seen so far, NC State is solidly the favorite, as LACCTiC is predicting.
Go ahead and hand them the trophy now, if you please.
I don't see how NC St can score only ~100 points. For them that would mean something like 5/10/20/30/35 which seems very aggressive for their 4/5 runners. OR in theory could go ~10/10/15/30/40 (Thompson scored 24 last year and Barnett 37 in 2022) but I think the field is deeper now.
I don't see how NC St can score only ~100 points. For them that would mean something like 5/10/20/30/35 which seems very aggressive for their 4/5 runners. OR in theory could go ~10/10/15/30/40 (Thompson scored 24 last year and Barnett 37 in 2022) but I think the field is deeper now.
No offense, but I really do not think you can be that obtuse to be looking at the absolute value of the scores when the simulations are obviously limited in scope regarding the potential sheer numbers of athletes in a full field simulation.
The important things to be looking at here are team placement and how the point deltas between the top teams are being influenced.
This is all great stuff and it is easy to be a contrarian. Let's wait to see what happens at Nuttycombe and at the ACC's. ND is at a completely different level than they were last year and they won the ACC. I think they are being dismissed a bit early and have some of the greatest depth and smallest spread 1-7. I think the real story at the end of the season is going to be the influx of foreign recruits into the mix, many of whom are virtually unknown. The top 20 list is predominantly Kenyan and there are probably some missing. If these recruits were concentrated more effectively on one team, the outcome would be a foregone conclusion. It is only a matter of time before that happens and Florida is closest. Paradigm shifts are ahead and I doubt NC State or BYU wins the title. Odds favor Florida particularly when they sort out the 5th spot.
I don't see how NC St can score only ~100 points. For them that would mean something like 5/10/20/30/35 which seems very aggressive for their 4/5 runners. OR in theory could go ~10/10/15/30/40 (Thompson scored 24 last year and Barnett 37 in 2022) but I think the field is deeper now.
No offense, but I really do not think you can be that obtuse to be looking at the absolute value of the scores when the simulations are obviously limited in scope regarding the potential sheer numbers of athletes in a full field simulation.
The important things to be looking at here are team placement and how the point deltas between the top teams are being influenced.
For example, a ‘closer look’ provided with these simulations confirms one thing we have been suspecting: that unless Florida pull a 5th rabbit out of their hat, the chances of them winning the trophy are not great. Adding more athletes to the simulations makes that point even more convincing.