tag:blogger.com,1999:blog-3299311926633621468.post8066264916624764887..comments2024-03-20T08:45:46.965-07:00Comments on Objective NHL: Team Effects and Even Strength Save PercentageJLikenshttp://www.blogger.com/profile/02570453428274983835noreply@blogger.comBlogger6125tag:blogger.com,1999:blog-3299311926633621468.post-20644861389254458862023-10-02T06:39:05.440-07:002023-10-02T06:39:05.440-07:00أسباب انسداد الشريان السباتي قد تكون:
1. تصلُّب ا...أسباب انسداد الشريان السباتي قد تكون:<br /><br />1. تصلُّب الشرايين (Atherosclerosis): حدوث تراكُم الكوليسترول والشحوم داخل جدران الشريان، مما يؤدي إلى التضخُّم وتضيُّقه وعرقلة تدفق الدم.<br /><br />2. تشكُّل الجلطات (Thrombosis): حدوث تجلُّط داخل الشريان نتيجة لتراكُم <a href="https://drmahmoudnasser.com/services/%D8%B9%D9%84%D8%A7%D8%AC-%D8%A7%D9%86%D8%B3%D8%AF%D8%A7%D8%AF-%D8%A7%D9%84%D8%B4%D8%B1%D9%8A%D8%A7%D9%86-%D8%A7%D9%84%D8%B3%D8%A8%D8%A7%D8%AA%D9%8A/" rel="nofollow">علاج ضيق الشريان السباتي</a> الدموية والعوامل الخطرة الأخرى.CLADING2222https://www.blogger.com/profile/12736101882067160075noreply@blogger.comtag:blogger.com,1999:blog-3299311926633621468.post-14123334802566518362013-05-03T12:24:04.242-07:002013-05-03T12:24:04.242-07:00it is quite interesting that you can make predicti...it is quite interesting that you can make predictions with that kind of data and you can get conclusive facts about it. Hostpph.comhttp://www.hostpph.comnoreply@blogger.comtag:blogger.com,1999:blog-3299311926633621468.post-85048557692196616002011-05-16T12:45:45.139-07:002011-05-16T12:45:45.139-07:00Strange thing about my response disappearing. Hop...Strange thing about my response disappearing. Hopefully anonymous had a chance to see it while it was still up. If not, I'll summarize what I said originally. <br /><br />But to address your comment, the point of the exercise was to see what range in team EV SQA values would produce a starter-backup correlation in the neighborhood of 0.15. Chris' data fit the observed results well in that respect, so I decided to use it instead of arbitrarily assigning my own values.<br /><br />As to the quality of the SQA data itself, I have no position either way, although it does seem that scorer bias is an issue, what with Tampa Bay consistently ending up at the top of the list.JLikenshttps://www.blogger.com/profile/02570453428274983835noreply@blogger.comtag:blogger.com,1999:blog-3299311926633621468.post-18050477232356713222011-05-13T11:06:05.647-07:002011-05-13T11:06:05.647-07:00JL,
I'm not sure what happened to your respon...JL,<br /><br />I'm not sure what happened to your response to Anonymous, it seems to have disappeared. But I wanted to point out one thing...<br /><br />If a shot quality model is measuring something other than scorer bias and playing-to-the-score effects, we should see the effects even in road games when the score is tied.<br /><br />I took Chris' data for the 2010-'11 season and assigned each team the Expected Save Percentage that Chris' model predicts they'd have at even strength due to team shot quality effects alone, i.e. if every goaltender were the same.<br /><br />I then let each team flip a coin weighted to their individual ExSVP, and flip it the number of times equal to their actual shots against at even strength on the road in tied games.<br /><br />If there were no goalie skill at all, chance and team effects alone (according to Chris' model) would result in a save percentage spread of about .015 sd.<br /><br />Turns out the actual sd was only about .013 though, so something about the model seems off. And it's not just a small sample size thing because if every team's coin were weighted to the same league average SvP, we'd see a spread of about .013 sd for EV-road-tied. So even if every goalie were the same, and the shots against sample size is as low as EV-road-tied, we should still see the results of team shot quality if the effect is as big as Chris' model assumes.<br /><br />But we don't.Sunny Mehtahttps://www.blogger.com/profile/15065546462546932579noreply@blogger.comtag:blogger.com,1999:blog-3299311926633621468.post-50077020973724852192011-05-11T12:41:55.072-07:002011-05-11T12:41:55.072-07:00That's a good question.
Because the evidenc...That's a good question. <br /><br />Because the evidence is mixed, I'm not entirely confident that there is a significant team effect. <br /><br />However, we'll work from the assumption that the correlation of 0.15 between starters and backups is both indicative of a real effect and representative of the magnitude of that effect.<br /><br />In answering your question, the relevant issue is this: What kind of team spread in shot quality allowed does there need to be in order to produce a starter-backup correlation of 0.15?<br /><br />Chris Boersma publishes EV shot quality data on his <a href="http://hockeystats.no-ip.org:81/ev.php?id=7&sit=ev" rel="nofollow">statistics website</a>. Using data from 2009-10, I assigned the starters and backups for each team an expected save percentage based on the Shot quality allowed rating of their team. <br /><br />I then simulated 50 seasons - in which the starters faced 1168 shots and backups 508 - and looked at the average correlation between starters and backups. <br /><br />The average correlation was 0.13, which closely matches the observed correlation of 0.15. <br /><br />Given that correspondence, we can look at the range in the team shot quality allowed values in order to get a sense of the practical effect size.<br /><br />Tampa Bay allowed the least dangerous shots and had an expected EV save percentage of 0.925. Carolina allowed the most dangerous shots and had an expected EV save percentage of 0.913. <br /><br />So it seems that the maximum effect that a team can have on the EV save percentage of its goaltender is approximately 0.006.JLikenshttps://www.blogger.com/profile/02570453428274983835noreply@blogger.comtag:blogger.com,1999:blog-3299311926633621468.post-10145472106573588322011-05-11T07:19:53.284-07:002011-05-11T07:19:53.284-07:00I am not a stats wizard. I was wondering if you c...I am not a stats wizard. I was wondering if you could help me by translating your analysis in to more direct prediction of how large the team effect on actual save percentage might be. For example, is it conceivable that team defense can swing a .900 goalie to a .910 goalie? (under what conditions?).Anonymousnoreply@blogger.com