Lacrosse Analytics

D1 Mens Lacrosse
ICGrad
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Re: Lacrosse Analytics

Post by ICGrad »

laxreference wrote: Sun Apr 23, 2023 9:13 am In the most recent simulation, here's how the bids projected for each conference in DI MLAX. We didn't add any new locks since PSU on Friday, but we did lose a few teams from the Work-to-Do bucket.


ncaa_projections_NCAAD1Men_20230423.jpg
Couple of interesting takeaways here that fly in the face of conventional FanLax wisdom:

1. UNC is out. Most here believe that with a win over ND they are in, and a good number believe that, even with a loss, a 7-7 UNC squad has a chance.
2. The Ivies have a good shot at getting not just 2, but 3 teams in. A good number of forumites see the Ivies as a one or, at best, two bid league.
laxreference
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Re: Lacrosse Analytics

Post by laxreference »

ICGrad wrote: Sun Apr 23, 2023 10:11 am
laxreference wrote: Sun Apr 23, 2023 9:13 am In the most recent simulation, here's how the bids projected for each conference in DI MLAX. We didn't add any new locks since PSU on Friday, but we did lose a few teams from the Work-to-Do bucket.


ncaa_projections_NCAAD1Men_20230423.jpg
Couple of interesting takeaways here that fly in the face of conventional FanLax wisdom:

1. UNC is out. Most here believe that with a win over ND they are in, and a good number believe that, even with a loss, a 7-7 UNC squad has a chance.
2. The Ivies have a good shot at getting not just 2, but 3 teams in. A good number of forumites see the Ivies as a one or, at best, two bid league.
1. UNC is very much where Cuse was. Yes, if they win, they'll have a shot, but it's very narrow and would rely on a lot of other things breaking correctly for them. It's not that there is no road for them if they beat ND, it's just that it's such a narrrow road, they didn't breach the 1% threshold.

2. I think Yale's resume is a lot better than people have given them credit for; 10th best set of victories and the 5th least damaging set of losses. Yale could theoretically lose to Harvard and still have a worthy resume. Penn is pretty close as well by some of the more traditional RPI numbers.
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laxreference
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Re: Lacrosse Analytics

Post by laxreference »

Here are the MLAX Tewaaraton nominees (offense-only). Kirst has the production crown, but Cormier is the most efficient (by a mile).


Fua9PdlXsAA-tAz.png
Fua9PdlXsAA-tAz.png (39.28 KiB) Viewed 1692 times
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nms
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Re: Lacrosse Analytics

Post by nms »

If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Brownlax
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Re: Lacrosse Analytics

Post by Brownlax »

nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
I’ll take Kirst!!
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Re: Lacrosse Analytics

Post by laxreference »

nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
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UVAlaxfan
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Re: Lacrosse Analytics

Post by UVAlaxfan »

laxreference wrote: Sun Apr 23, 2023 6:41 pm
nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
how is expected goals added computed?
laxreference
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Re: Lacrosse Analytics

Post by laxreference »

UVAlaxfan wrote: Mon Apr 24, 2023 8:49 am
laxreference wrote: Sun Apr 23, 2023 6:41 pm
nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
how is expected goals added computed?
How EGA is calculated

The core of EGA is that every type of play has a value in terms of how often it leads to a goal for your team vs the other team. Picking up a GB has a positive EGA value. Committing a turnover has a negative. Taking a shot that is saved is worse for your EGA than a shot that is missed. Assisted goals split credit between the assister and scorer. The article above explains it in more detail.

How Usage Adjusted EGA differs from EGA

uaEGA basically takes your EGA production and adjusts it based on how much you show up in the box score so that you have something akin to production-per-touch.
Data Engineer/Lacrosse Fan --- Twitter: @laxreference --- Informed fans get Expected Goals, the new daily newsletter from LacrosseReference
10stone5
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Re: Lacrosse Analytics

Post by 10stone5 »

nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
In the upper right hand box, you have,

Eamon McEneaney :)
laxreference
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Re: Lacrosse Analytics

Post by laxreference »

CJ Kirst ( vs BRWN ) had the most impressive statistical performance of the past week in DI MLAX

weekly_ega_NCAAD1Men_20230425.jpg
weekly_ega_NCAAD1Men_20230425.jpg (152.54 KiB) Viewed 1323 times
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Re: Lacrosse Analytics

Post by laxreference »

I have great news! We are going to take a look back at the 2022 MLAX selection process. But it's not what you think. The thing that always irked me about last year's at-large choices was not which teams got in and which were left out. It was that it felt like there wasn't a consistent internal logic to it. ND didn't beat any tournament teams...unless they had given Duke an at-large.

But I have finally found it. A not-too-complex system using SOR as the basis which produces the same at-large choices that the committee made. This is not to say that they deliberately picked this system and then the choices followed. But they might as well have. And it's not like they had any crazy rules. It's an RPI-based Strength-of-Record system along the same lines as the one I laid out here

Before I get into the rules that produced their choices, here's the important thing. If you didn't like the choices that they made last year, they you have to say which part of their "system" you disagree with. And there are 3 components to it.

First, change the RPI weights from 25% win pct / 50% opp win pct / 25% opp opp win pct to 25% / 60% / 15%.

Next, strongly de-emphasize a team's lesser wins. In effect, focus on a team's 4 or 5 best wins and ignore the rest.

Last, include a head-to-head rule where if the first-team-out has a win against the last-team-in, then flip them so that the first-team-out gets the bid.

You can see the results here (I've pre-loaded the settings), but such a system leaves you with Harvard/OSU in and Duke/ND out.

Basically Harvard is in because their wins were as good as anyone's. Duke is out because their volume of decent wins is ignored. ND would get the bid because their SOR was higher than OSU, but the Buckeyes get the nod because of the H2H victory over the Irish.

Again, you may not like the outcome, but your argument is with the settings used, not the results. If you don't like their results, which part of the system would you change. Share your preferred rules and we can figure out which makes the most sense. If you did think the choices were justified, is this a system you feel comfortable with? If not, how would you tweak it?

Until now, it was a valid argument to say, "well there is something about all this that numbers can't capture." If that was your argument, I wouldn't have had an answer. But now I do. There is a system that captures the decision-process the committee used. And that means that when the selections come out this year, we can see if they used the same logic or not. When you use wins vs the various RPI tiers, you are using an SOR-based system. Now I've got the rules to prove it.
Data Engineer/Lacrosse Fan --- Twitter: @laxreference --- Informed fans get Expected Goals, the new daily newsletter from LacrosseReference
joewillie78
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Re: Lacrosse Analytics

Post by joewillie78 »

laxreference wrote: Fri Apr 28, 2023 1:02 pm I have great news! We are going to take a look back at the 2022 MLAX selection process. But it's not what you think. The thing that always irked me about last year's at-large choices was not which teams got in and which were left out. It was that it felt like there wasn't a consistent internal logic to it. ND didn't beat any tournament teams...unless they had given Duke an at-large.

But I have finally found it. A not-too-complex system using SOR as the basis which produces the same at-large choices that the committee made. This is not to say that they deliberately picked this system and then the choices followed. But they might as well have. And it's not like they had any crazy rules. It's an RPI-based Strength-of-Record system along the same lines as the one I laid out here

Before I get into the rules that produced their choices, here's the important thing. If you didn't like the choices that they made last year, they you have to say which part of their "system" you disagree with. And there are 3 components to it.

First, change the RPI weights from 25% win pct / 50% opp win pct / 25% opp opp win pct to 25% / 60% / 15%.

Next, strongly de-emphasize a team's lesser wins. In effect, focus on a team's 4 or 5 best wins and ignore the rest.

Last, include a head-to-head rule where if the first-team-out has a win against the last-team-in, then flip them so that the first-team-out gets the bid.

You can see the results here (I've pre-loaded the settings), but such a system leaves you with Harvard/OSU in and Duke/ND out.

Basically Harvard is in because their wins were as good as anyone's. Duke is out because their volume of decent wins is ignored. ND would get the bid because their SOR was higher than OSU, but the Buckeyes get the nod because of the H2H victory over the Irish.

Again, you may not like the outcome, but your argument is with the settings used, not the results. If you don't like their results, which part of the system would you change. Share your preferred rules and we can figure out which makes the most sense. If you did think the choices were justified, is this a system you feel comfortable with? If not, how would you tweak it?

Until now, it was a valid argument to say, "well there is something about all this that numbers can't capture." If that was your argument, I wouldn't have had an answer. But now I do. There is a system that captures the decision-process the committee used. And that means that when the selections come out this year, we can see if they used the same logic or not. When you use wins vs the various RPI tiers, you are using an SOR-based system. Now I've got the rules to prove it.
Great system and analysis. I especially like the H2H rule of ,if they are that close, then the H2H winner gets in, even if they were originally just out.

Can you do this for 2019, and let me know if Cornell is still out, even though they beat ND AT ND, in H2H competition?

Gobigred
Joewillie78
laxreference
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Re: Lacrosse Analytics

Post by laxreference »

joewillie78 wrote: Fri Apr 28, 2023 1:37 pm
laxreference wrote: Fri Apr 28, 2023 1:02 pm I have great news! We are going to take a look back at the 2022 MLAX selection process. But it's not what you think. The thing that always irked me about last year's at-large choices was not which teams got in and which were left out. It was that it felt like there wasn't a consistent internal logic to it. ND didn't beat any tournament teams...unless they had given Duke an at-large.

But I have finally found it. A not-too-complex system using SOR as the basis which produces the same at-large choices that the committee made. This is not to say that they deliberately picked this system and then the choices followed. But they might as well have. And it's not like they had any crazy rules. It's an RPI-based Strength-of-Record system along the same lines as the one I laid out here

Before I get into the rules that produced their choices, here's the important thing. If you didn't like the choices that they made last year, they you have to say which part of their "system" you disagree with. And there are 3 components to it.

First, change the RPI weights from 25% win pct / 50% opp win pct / 25% opp opp win pct to 25% / 60% / 15%.

Next, strongly de-emphasize a team's lesser wins. In effect, focus on a team's 4 or 5 best wins and ignore the rest.

Last, include a head-to-head rule where if the first-team-out has a win against the last-team-in, then flip them so that the first-team-out gets the bid.

You can see the results here (I've pre-loaded the settings), but such a system leaves you with Harvard/OSU in and Duke/ND out.

Basically Harvard is in because their wins were as good as anyone's. Duke is out because their volume of decent wins is ignored. ND would get the bid because their SOR was higher than OSU, but the Buckeyes get the nod because of the H2H victory over the Irish.

Again, you may not like the outcome, but your argument is with the settings used, not the results. If you don't like their results, which part of the system would you change. Share your preferred rules and we can figure out which makes the most sense. If you did think the choices were justified, is this a system you feel comfortable with? If not, how would you tweak it?

Until now, it was a valid argument to say, "well there is something about all this that numbers can't capture." If that was your argument, I wouldn't have had an answer. But now I do. There is a system that captures the decision-process the committee used. And that means that when the selections come out this year, we can see if they used the same logic or not. When you use wins vs the various RPI tiers, you are using an SOR-based system. Now I've got the rules to prove it.
Great system and analysis. I especially like the H2H rule of ,if they are that close, then the H2H winner gets in, even if they were originally just out.

Can you do this for 2019, and let me know if Cornell is still out, even though they beat ND AT ND, in H2H competition?

Gobigred
Joewillie78
2019 is a bit simpler than 2022. All you need to do is really de-emphasize losses (like really really de-emphasize losses) and then apply the H2H tiebreaker. That's how you can get Cuse as the last team in with Cornell as the first team out (Cuse gets it because of the H2H). Here's the head to head for those last 4 teams.

The interesting thing is that, from what I understand, the ND vs Cornell debate was the key here given the H2H win for Cornell over ND. But at least using this comparison, ND would have been safely in and Cuse/Cornell would have been the final 2 with the H2H actually working against Cornell. I'd be curious if anyone can find settings that make ND vs Cornell the last comparison.

If you used the 2019 rules last year, Duke would have been in instead of Harvard. OSU would still have needed the H2H jump to get over ND.
Data Engineer/Lacrosse Fan --- Twitter: @laxreference --- Informed fans get Expected Goals, the new daily newsletter from LacrosseReference
nms
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Re: Lacrosse Analytics

Post by nms »

laxreference wrote: Fri Apr 28, 2023 3:23 pm
joewillie78 wrote: Fri Apr 28, 2023 1:37 pm
laxreference wrote: Fri Apr 28, 2023 1:02 pm I have great news! We are going to take a look back at the 2022 MLAX selection process. But it's not what you think. The thing that always irked me about last year's at-large choices was not which teams got in and which were left out. It was that it felt like there wasn't a consistent internal logic to it. ND didn't beat any tournament teams...unless they had given Duke an at-large.

But I have finally found it. A not-too-complex system using SOR as the basis which produces the same at-large choices that the committee made. This is not to say that they deliberately picked this system and then the choices followed. But they might as well have. And it's not like they had any crazy rules. It's an RPI-based Strength-of-Record system along the same lines as the one I laid out here

Before I get into the rules that produced their choices, here's the important thing. If you didn't like the choices that they made last year, they you have to say which part of their "system" you disagree with. And there are 3 components to it.

First, change the RPI weights from 25% win pct / 50% opp win pct / 25% opp opp win pct to 25% / 60% / 15%.

Next, strongly de-emphasize a team's lesser wins. In effect, focus on a team's 4 or 5 best wins and ignore the rest.

Last, include a head-to-head rule where if the first-team-out has a win against the last-team-in, then flip them so that the first-team-out gets the bid.

You can see the results here (I've pre-loaded the settings), but such a system leaves you with Harvard/OSU in and Duke/ND out.

Basically Harvard is in because their wins were as good as anyone's. Duke is out because their volume of decent wins is ignored. ND would get the bid because their SOR was higher than OSU, but the Buckeyes get the nod because of the H2H victory over the Irish.

Again, you may not like the outcome, but your argument is with the settings used, not the results. If you don't like their results, which part of the system would you change. Share your preferred rules and we can figure out which makes the most sense. If you did think the choices were justified, is this a system you feel comfortable with? If not, how would you tweak it?

Until now, it was a valid argument to say, "well there is something about all this that numbers can't capture." If that was your argument, I wouldn't have had an answer. But now I do. There is a system that captures the decision-process the committee used. And that means that when the selections come out this year, we can see if they used the same logic or not. When you use wins vs the various RPI tiers, you are using an SOR-based system. Now I've got the rules to prove it.
Great system and analysis. I especially like the H2H rule of ,if they are that close, then the H2H winner gets in, even if they were originally just out.

Can you do this for 2019, and let me know if Cornell is still out, even though they beat ND AT ND, in H2H competition?

Gobigred
Joewillie78
2019 is a bit simpler than 2022. All you need to do is really de-emphasize losses (like really really de-emphasize losses) and then apply the H2H tiebreaker. That's how you can get Cuse as the last team in with Cornell as the first team out (Cuse gets it because of the H2H). Here's the head to head for those last 4 teams.

The interesting thing is that, from what I understand, the ND vs Cornell debate was the key here given the H2H win for Cornell over ND. But at least using this comparison, ND would have been safely in and Cuse/Cornell would have been the final 2 with the H2H actually working against Cornell. I'd be curious if anyone can find settings that make ND vs Cornell the last comparison.

If you used the 2019 rules last year, Duke would have been in instead of Harvard. OSU would still have needed the H2H jump to get over ND.
I don't want to discourage you, because I really do appreciate all the analysis that you provide, but...I fear that you are looking for a mathematical solution to a problem that is not mathematical. There is no formula, plan, calculation, or consistent definitive rules used by the committee. They simply decide which schools they feel deserve to be in the tournament and justify it any way they see fit.

If one year, they chose to claim that they left out teams because of low RPI, or bad losses, NOTHING prevents them from saying the next year, they left out teams because they had no quality wins, or too weak a schedule.
PizzaSnake
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Re: Lacrosse Analytics

Post by PizzaSnake »

laxreference wrote: Mon Apr 24, 2023 8:58 am
UVAlaxfan wrote: Mon Apr 24, 2023 8:49 am
laxreference wrote: Sun Apr 23, 2023 6:41 pm
nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
how is expected goals added computed?
How EGA is calculated

The core of EGA is that every type of play has a value in terms of how often it leads to a goal for your team vs the other team. Picking up a GB has a positive EGA value. Committing a turnover has a negative. Taking a shot that is saved is worse for your EGA than a shot that is missed. Assisted goals split credit between the assister and scorer. The article above explains it in more detail.

How Usage Adjusted EGA differs from EGA



uaEGA basically takes your EGA production and adjusts it based on how much you show up in the box score so that you have something akin to production-per-touch.
Why? While a saved shot (shot on goal) could in theory have resulted in a score, a missed shot (not on goal) will never result in a score.
"There is nothing more difficult and more dangerous to carry through than initiating changes. One makes enemies of those who prospered under the old order, and only lukewarm support from those who would prosper under the new."
rolldodge
Posts: 1164
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Re: Lacrosse Analytics

Post by rolldodge »

PizzaSnake wrote: Fri Apr 28, 2023 7:24 pm
laxreference wrote: Mon Apr 24, 2023 8:58 am
UVAlaxfan wrote: Mon Apr 24, 2023 8:49 am
laxreference wrote: Sun Apr 23, 2023 6:41 pm
nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
how is expected goals added computed?
How EGA is calculated

The core of EGA is that every type of play has a value in terms of how often it leads to a goal for your team vs the other team. Picking up a GB has a positive EGA value. Committing a turnover has a negative. Taking a shot that is saved is worse for your EGA than a shot that is missed. Assisted goals split credit between the assister and scorer. The article above explains it in more detail.

How Usage Adjusted EGA differs from EGA



uaEGA basically takes your EGA production and adjusts it based on how much you show up in the box score so that you have something akin to production-per-touch.
Why? While a saved shot (shot on goal) could in theory have resulted in a score, a missed shot (not on goal) will never result in a score.
Because it’s a turnover.
PizzaSnake
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Re: Lacrosse Analytics

Post by PizzaSnake »

rolldodge wrote: Fri Apr 28, 2023 7:40 pm
PizzaSnake wrote: Fri Apr 28, 2023 7:24 pm
laxreference wrote: Mon Apr 24, 2023 8:58 am
UVAlaxfan wrote: Mon Apr 24, 2023 8:49 am
laxreference wrote: Sun Apr 23, 2023 6:41 pm
nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
how is expected goals added computed?
How EGA is calculated

The core of EGA is that every type of play has a value in terms of how often it leads to a goal for your team vs the other team. Picking up a GB has a positive EGA value. Committing a turnover has a negative. Taking a shot that is saved is worse for your EGA than a shot that is missed. Assisted goals split credit between the assister and scorer. The article above explains it in more detail.

How Usage Adjusted EGA differs from EGA



uaEGA basically takes your EGA production and adjusts it based on how much you show up in the box score so that you have something akin to production-per-touch.
Why? While a saved shot (shot on goal) could in theory have resulted in a score, a missed shot (not on goal) will never result in a score.
Because it’s a turnover.
Not necessarily. Closest to ball…
"There is nothing more difficult and more dangerous to carry through than initiating changes. One makes enemies of those who prospered under the old order, and only lukewarm support from those who would prosper under the new."
rolldodge
Posts: 1164
Joined: Fri Feb 08, 2019 10:28 pm

Re: Lacrosse Analytics

Post by rolldodge »

PizzaSnake wrote: Fri Apr 28, 2023 8:13 pm
rolldodge wrote: Fri Apr 28, 2023 7:40 pm
PizzaSnake wrote: Fri Apr 28, 2023 7:24 pm
laxreference wrote: Mon Apr 24, 2023 8:58 am
UVAlaxfan wrote: Mon Apr 24, 2023 8:49 am
laxreference wrote: Sun Apr 23, 2023 6:41 pm
nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
how is expected goals added computed?
How EGA is calculated

The core of EGA is that every type of play has a value in terms of how often it leads to a goal for your team vs the other team. Picking up a GB has a positive EGA value. Committing a turnover has a negative. Taking a shot that is saved is worse for your EGA than a shot that is missed. Assisted goals split credit between the assister and scorer. The article above explains it in more detail.

How Usage Adjusted EGA differs from EGA



uaEGA basically takes your EGA production and adjusts it based on how much you show up in the box score so that you have something akin to production-per-touch.
Why? While a saved shot (shot on goal) could in theory have resulted in a score, a missed shot (not on goal) will never result in a score.
Because it’s a turnover.
Not necessarily. Closest to ball…
Agree. Would be interesting if they could track that. Shots that result in turnovers as general category.
JHU69
Posts: 133
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Location: East bank of the lower Willamette

Re: Lacrosse Analytics

Post by JHU69 »

PizzaSnake wrote: Fri Apr 28, 2023 8:13 pm
rolldodge wrote: Fri Apr 28, 2023 7:40 pm
PizzaSnake wrote: Fri Apr 28, 2023 7:24 pm
laxreference wrote: Mon Apr 24, 2023 8:58 am
UVAlaxfan wrote: Mon Apr 24, 2023 8:49 am
laxreference wrote: Sun Apr 23, 2023 6:41 pm
nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
how is expected goals added computed?
How EGA is calculated

The core of EGA is that every type of play has a value in terms of how often it leads to a goal for your team vs the other team. Picking up a GB has a positive EGA value. Committing a turnover has a negative. Taking a shot that is saved is worse for your EGA than a shot that is missed. Assisted goals split credit between the assister and scorer. The article above explains it in more detail.

How Usage Adjusted EGA differs from EGA



uaEGA basically takes your EGA production and adjusts it based on how much you show up in the box score so that you have something akin to production-per-touch.
Why? While a saved shot (shot on goal) could in theory have resulted in a score, a missed shot (not on goal) will never result in a score.
Because it’s a turnover.
Not necessarily. Closest to ball…
A saved shot is a turnover!!!
I believe that if life gives you lemons, you should make lemonade... And try to find somebody whose life has given them vodka, and have a party.
PizzaSnake
Posts: 5027
Joined: Tue Mar 05, 2019 8:36 pm

Re: Lacrosse Analytics

Post by PizzaSnake »

JHU69 wrote: Fri Apr 28, 2023 8:36 pm
PizzaSnake wrote: Fri Apr 28, 2023 8:13 pm
rolldodge wrote: Fri Apr 28, 2023 7:40 pm
PizzaSnake wrote: Fri Apr 28, 2023 7:24 pm
laxreference wrote: Mon Apr 24, 2023 8:58 am
UVAlaxfan wrote: Mon Apr 24, 2023 8:49 am
laxreference wrote: Sun Apr 23, 2023 6:41 pm
nms wrote: Sun Apr 23, 2023 6:05 pm If I am reading it correctly, Kirst is #1 in production and #3 in efficiency,
while Cormier is about #9 in production and #1 in efficiency

I don't believe that the quadrants in this particular graph do anything more than serve as visual aids.
Correct on all 3 counts
how is expected goals added computed?
How EGA is calculated

The core of EGA is that every type of play has a value in terms of how often it leads to a goal for your team vs the other team. Picking up a GB has a positive EGA value. Committing a turnover has a negative. Taking a shot that is saved is worse for your EGA than a shot that is missed. Assisted goals split credit between the assister and scorer. The article above explains it in more detail.

How Usage Adjusted EGA differs from EGA



uaEGA basically takes your EGA production and adjusts it based on how much you show up in the box score so that you have something akin to production-per-touch.
Why? While a saved shot (shot on goal) could in theory have resulted in a score, a missed shot (not on goal) will never result in a score.
Because it’s a turnover.
Not necessarily. Closest to ball…
A saved shot is a turnover!!!
So “saved” means stopped shot with residual possession? Is there a stat for shots stopped without residual possession? What’s that called?
"There is nothing more difficult and more dangerous to carry through than initiating changes. One makes enemies of those who prospered under the old order, and only lukewarm support from those who would prosper under the new."
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