Zone Rating seems to be the go to defensive stat for ootp but I've never been quite sure what the other two advanced defensive metrics meant? Any answers appreciated even if its just speculation

Our offense is currently second best in the league at converting on 3rd down, behind only Green Bay.

The weird thing is, if you look at Football Outsider’s ALEX stat, Josh Allen ranks super low (23rd).

ALEX is “Air Less EXpected” on 3rd downs. Essentially, it measures the average distance between the air yards of each pass compared to yards needed to gain a first down (e.g. an 8 yard pass on 3rd and 10, would be -2 in ALEX)

Does this mean our receivers have been elite at picking up the necessary YAC on 3rd down? If you look at most of the other good 3rd down offenses, their QBs are ranked fairly high in ALEX

Hi there, hope you are all doing well. The world is a crazy place, now more then ever, and I just hope everyone here is taking care of themselves too and staying safe.

I am a 3rd year student, who plans to go into a math degree with stats as my concentration. Although I love math and stats, I have been having some trouble with my current stats class. This class is known to be brutal in my uni, so I am not to hard on myself. That being said however, I would like to improve.

I noticed that my biggest issue is fully understanding what technique to apply to what situation, but as I started addressing that problem, it came to light that I might not be as efficient in my studying as I would like.

Being more efficient, of course, gives me more time to focus on other classes, instead of being stuck studying one class for far to much time.

So to put it simply, I would love to know techniques that you guys use that really helped out your efficiency, either in stats or just for studying in general.

I thank you all so much.

TLDR; What techniques do you guys have to be more efficient in studying stats, or just studying in general?

All,

I am working on putting together statistics for Super Mechs to benefit the community. These statistics are on damage per weight, armor value per weight, etc.

http://www.puresimplicity.net/~delahunt/misc/sm_spreadsheet.html

I need your help. I need statistics (screenshots if you wish) on weapons at level 1 of all scarcity levels (common, rare, epic, legendary, mythical, divine). Currently, my statistics are based on my own inventory. And not to be rude, but the SuperMechs fandom wiki doesn't have a lot of these.

Please DM, reply, or even (from the website) click contact and email me statistics. Screenshots are preferred but not required.

Thanks!

SawzAll

Introduction

You want your top dawg taking the biggest shots to get you wins, but is it true that more shots lead to more wins? The BrownMamba has been the go-to guy for the BrownBallers since the beginning — hell, he’s the one who started it all ! — and he has put on some sensational scoring clinics. But how much winning did those buckets lead to? Rather than raw scoring, is efficiency the answer to success? What is the tradeoff between volume and efficiency?

Data Collection and Methodology

For this analysis, we will be examining data exclusively from BrownBall Season 1 (2017-18). I select a couple of different metrics for the purpose of linear regression. Since “winning” isn’t technically a quantifiable category in and of itself and simply using win-counts would be insufficient for this regression since we are analyzing data on a section-by-section basis, I opted to calculate the margin of victory for each section.

Why section-by-section? The main limitation of the data at hand is that BrownBall points are tallied on a section-by-section basis but are not broken down on a game-by-game basis. A section consists of multiple games; however, some of those games might be losses, and some of those games might be wins. The statistical challenge is that the only available data simply looks at total points across the whole section rather than how many points a player scored in each game in that section. As a result, we can only analyze the margin of victory in the entire section as opposed to the margin of victory in each game.

The next variable we want to account for is how much the BrownMamba was scoring. We don’t simply want to take his raw point total, as depending on how many points each team was playing to, there might be high variance in his scoring output. What we are looking for is the share of the team’s total points that the BrownMamba scored, the idea being that if the BrownMamba scores a larger portion of his team’s points, we can infer whether running the offense through him led to a larger or smaller margin of victory.

We also want to account for the BrownMamba’s efficiency — just because you score a lot doesn’t mean your immune to the pitfalls of what I call “The Jerry Stackhouse Effect.” I used effective field goal percentage (eFG%) as a measure of efficiency since it takes into account that a made three-pointer is worth one and a half times as much as a made two-pointer.

Results

(Note that sample size discrepancies are due t

In the statistics tab.

There is a triangle with 3 corners: Map awareness, Gold Efficiency, and Combat.

The gold one is my lowest thing stat, but I am not sure what that means or how to improve it.

it asks me to use more characters in order to ask the question so this is just filler text.

Example: Task #1 from the Dec. 7, 2020 Exam

How might someone replicate (or closely mirror) the sample solution output from the file linked above?

The syllabus mentions that we won't have access to certain shortcut keys, which consequently prevents us from using the Capture program to grab a quick cropped screenshot.

Another Reddit post mentioned using Excel as an alternative, but I've had difficulty doing so (perhaps since I'm using MS Office 2019?). The process seems easier with data frames, but things get messy with the summary function.

The best solution I've been able to come up with is to use the PrtScr key to grab a full screenshot, paste it into Word, then crop within Word. If no other solution is mentioned, I guess this'll be my procedure, but it seems like there should be a better way to perform this action.

Any insight would be highly appreciated!

Again, all of this trouble might just be due to my MS Office version, so if anyone can verify whether this is case (or if it's something we'll definitely need to contend with at the exam center), that'd also be useful input.

Relevant Posts

• Tua finishing his season with the all-time record
• Mount Union QB D'Angelo Fulford breaking a 25-year NCAA record at 229.45
• Visualization of the all-time passing leaders over time
• Tagovailoa, Burrow, and Hurts are all ahead of the all-time FBS Passing Efficiency Record

This is a follow up to a few posts about the all-time passing efficiency record. It's been a phenomenal year for passing QBs at multiple levels in particular at FBS and D3. I had previously reported that given that Tua's season was over, he finished his season by breaking his own FBS record of 199.4 with a mark of 206.9. /u/AmidoBlack pointed out that per the FBS Record Book:

> A passer must play in at least 75 percent of his team’s games to qualify for the rankings (for example, a player on a team with a nine-game season could qualify by playing in seven games)

Tagovailoa has played in parts of 9/12 regular season games, and is at that threshold, but will fall below it if Alabama plays in a bowl game and Tagovailoa does not participate. I wrote to NCAA Associate Director, Media Coordination and Statistics Jeff Williams to confirm that, Tagovailoa: 1) would not break his record if Alabama plays a bowl game that he does not participate in, 2) would break his record if he is on the field for one snap. Williams confirmed that understanding.

I also wrote to confirm that Mount Union's D'Angelo Fulford has broken the all-time NCAA passing efficiency record set by Eureka's Mike Simpson in 1994. He confirmed that as well. Here's the full text of his reply:

> All per-game and percentage categories require individuals to participate in 75 percent of the team’s games. If a player does not meet that minimum qualification he would not be listed among the national leaders in that category and it would not be a record.

> Another member of our staff maintains the Division III record but it does appear that Fulford should be the new record holder. Please note, though, Broc Rutter from North Central (IL) is playing in the Division III championship game and is second nationally in pass efficiency.

While scrolling through r/nba today in church, I was taken aback - not by the rampant homoeroticism for Miles Plumlee's three-pointer (not even top 5 most attractive on the Nuggets tbh wtf guys) - but by r/nba's constant inability to comprehend advanced statistics.

Some problems (like homosexuality, according to my pastor) can't be solved. But a lack of understanding of advanced statistics can be.

Advanced statistics, as the name advanced would suggest, are complicated. At the end I'll make a tl;dr as brief as I can for the Mike Tyson wannabes out there who don't like reading.

Player Efficiency Rating (PER)

Player Efficiency Rating, or PER, was developed by John Hollinger, a very intelligent man who works in the Memphis front office (can you be intelligent and work for the Grizzlies at the same time?). It's designed to quantify a player's total contribution with one number.

Positives:

PER takes into account every box-score statistic there is, which allows for a fairly complete look at a player's statistics. Every season, it is adjusted so that the league average PER is 15. This makes comparing across eras easier.

It also allows a player's total worth to be summed up into one number evaluating their impact. Although no method of doing this can be complete, PER comes the closest. A 35 PER indicates an all time great season, anything above 25 an All-Star, 15 an average player, and below 10 for players who shouldn't be in the league.

Negatives:

Like a Dwight Howard post up, PER can work sometimes - but if it's your only tool, you're screwed. PER is per minute, not per game, and does not account for opponent strength. This inflates the PER of bench players and players who don't play very many minutes.

For example, Boban Marjanovic's career PER is 27.8, which would put him in MVP contention. However, when taken in context this just shows that Boban is dominant in the limited minutes he player. Good, sure; MVP candidate, no.

Also, PER only takes into account box score defensive statistics like steals and blocks, giving guys who gamble for steals like Russell Westbrook or blocks like Javale McGee an inflated defensive PER.

TL;DR

PER is PER-haps (haha) the best single number to evaluate a player by, but it's not perfect. It overrates bench players who play low minutes and doesn't throughly evaluate defensive performance.

RN I'm planning on just doing ore plus water for the pure recipe.

Video link for context. https://youtu.be/Ihh8-QoaFzk

I recently wrote a script to calculate the ducat per relic for me. Here are the results:

Ignoring multiple rewards, the old void key averages about 25 ducats per key(I had this calculated with an older iteration of my script but I don't recall the exact number, and I don't have the drop table anymore). And you can get 4 runs per key from keysharing. Making that about 100 ducats on average per key spent by you.

Relics average about(taking the average of the relic average because I'm looking for the average per relic, not the average per item) 19.84 per intact, 22.24 per exceptional, 25.34 per flawless, 29.49 per radiant, if you're running them solo.

When running a in a group of 4:

• Chances of getting at least one rare is 1-(1-rare_chance)^4
• Chances of getting all common is total_common_chance^4
• Chances of getting at least one uncommon and no rare is 1-(1-(1-rare_chance)^4 + total_common_chance^4 )

Keeping that in mind when weighing the ducats of the item drops, we get:

32.73 per intact, 37.90 per exceptional, 40.90 per flawless, 51.93 per radiant.

So, in the most ideal situation, we get; on average, 51.93 ducats per relic, compared to the previous 100 ducats per key.

But most of the time, we would get 32.73 per relic, since very few people use radiants or any other variation in public.

And keep in mind that this comparison is done ignoring the multiple rewards from missions like survival, sabotage, defense and interception. So the original ducat per key is actually significantly higher than 100 ducats, meaning more tedious key farming for those who don't have a large abundance of keys. Hooray.

Edit: format

Edit: Information taken from https://github.com/VoiDGlitch/WarframeData/blob/master/MissionDecks.txt

Edit: fixed value error due to missing brackets in calculations...

Also, how good is the "Efficiency" stat at predicting a player's ability and performance?

I think this could be a really useful statistic to be able to rate players based on their on field efficiency vs their cost. I've tried incorporating Minutes Played Per Point Scored and dividing by it, but it didn't provide an accurate representation of efficiency. I'm sure there is someone smarter than me that can figure out a better equation?

This is more a question on opinion, rather than statistically powerful builds.

Is there joy in playing intentionally bad characters?

In one of my groups, a player has created a Fighter. But going by his stats, he is going to be the worst fighter ever.

Rolled stats are so so low, and STR and DEX are not the highest of the available rolls.

But! This character is an old man. He is a retired city guard and has been dragged out of retirement. His strength is failing him and he can barely swing his axe, so the stats fit the man.

So

1. Do people enjoy making characters that are intentionally bad, for the sake of the story?

2. Are these types of build discussed on this subreddit? I am new here and would love to discuss character background history.

EDIT: thank you to everyone for the responses. I don't think I'm wrong in being a bit frustrated, but in reading the comments, I do think I can find ways to think of this positively and ensure everyone has a fun game. Thanks all.

Hey guys!

So I'm a big fan of Dota 2, especially the pro scene. I grew up watching Major League Baseball as well and got caught up in the wave of Sabermetrics around when Moneyball was released. I loved looking into really deep statistics to determine a Player's true value and seeing what statistics were overrated (cough batting average cough), and which ones were overlooked.

This type of statistical analysis is something I think is largely missing from Dota, and eSports in general. There are some absolutely fantastic sites out there, such as Dotabuff and Dota Academy but they don't go deep enough into the statistics of individual players to satisfy my curiosity. So I spent a little bit of time this afternoon pulling a Bill James and trying to come up with some individual statistics to determine a player's worth.

The statistic I thought up was Carry Efficiency.

As a general rule, efficiency equations follow the rule of:

   Efficiency = Output / Input

So I created this formula to measure Carry Efficiency:

   Carry Efficiency =  ((Kills + (Assists/3) - Deaths) / GPM) * 100

What this statistic does is attempt to quantify how efficient a carry is at doing just that, by measuring how well they are at getting kills and limiting deaths at a given amount of farm. Assists were given a value of 1/3 of that of a kill and the final number is multiplied by 100 to get a more pleasing decimal position.

For example, here is Dendi's career professional game statline (taken from Dota-Academy):

Kills - 7.3

Deaths - 3.7

Assists - 9.9

GPM - 416

Therefore, using the formula his Carry Efficiency is 1.67

But that's just a random number, we have no idea if that's good or not. So let's compare Dendi's number to his teammates on Natus Vincere:

XBOCT - 1.44

LightOfHeaven - 1.01

Puppey - 0.86

Ars-Art - 0.97

As you can see, Dendi's carry efficiency is higher than Xboct's, which may seem surprising since Xboct normally plays the 1 position, the most farm dependent and the "hard carry". However, if you look into the stats, Dendi averages .2 more kills, .2 less deaths, and .1 more assists than Xboct, and he does it while averaging 32 less GPM. When taking that into account, it makes sense that Dendi's carry efficiency rating would be higher than Xboct's. It also makes sense that his would be higher

Greetings inquisitive spaceship pilots!

As the war in Delve draws to an ugly stalemate, it seems an opportune moment to share updated statistics from the active combat zone. This is a follow-on thread from https://www.reddit.com/r/Eve/comments/n36edu/968bn_and_counting/ and https://www.reddit.com/r/Eve/comments/nfcuib/23_days_of_carnage_stats_from_the_assault_on_the/

I have continued to run a br.evetools report each day (00:00 to 23:59) for the active combat zone of the 1DQ constellation + neighbouring systems T5Z and E-V.

These br.evetools reports provide a focused view of active combat for the 1DQ constellation, and in particular the SRP'able costs of combat, and active PvP pilot numbers.

Now we have a reasonable number of data points, we can identify some interesting trends. Let's start with the raw data:

https://preview.redd.it/pjz8ydr08g471.png?width=875&format=png&auto=webp&s=894b65c262a15bee443ddfd91074dac096585da4

We can also, now we have sufficient data points, look at participation trends over time. While Imperium numbers over the last 6 weeks are largely stable, there is a noticeable downward trend for PAPI;

Linear trendline

7 day moving average

Highlights;

• Since the last update, where the ISK war was 50/50, Imperium have pulled ahead in efficiency ("the ISK war"), and have now inflicted 213bn ISK more losses on PAPI than they have suffered themselves (2.7tn v 2.9tn ISK in favour of Imperium)
• In contrast to the start of the assault, Imperium now clearly outnumber PAPI on the majority of days - in the last 3 weeks (21 days), Imperium have outnumbered PAPI on 18 of those days
• Compared to the start of the assault, there are now noticeably more 'quiet days' (total active pilots under 2000) than at the start - in the last week, only two days saw active pilot numbers above 2000
• PAPI's numbers are on a significant downward trend, and that trend shows no signs of stabilising or reversing in recent data - it continues to fall, while Imperium numbers are stable
• There is a notable

I can understand a little of French and German, so if you know a good handball news site or page please let me know

Intro:

The NCAA Tournament is the best sporting event on the planet. Some naysayers may point to the World Cup or Super Bowl. They are wrong. From 48 games in 4 days to buzzer beaters to Cinderellas, the majesty of March Madness is unrivaled. And, last year, it was stolen from us. This isn't tragic, because tragedy is 500,000 Americans (and millions more around the world) dead from a pandemic. There may be some COVID jokes in here. Know that I mean no ill will to those of you who lost someone close to them due to this disease. I'm a firm believer that humor helps us heal, helps humble us. A lot of you messaged me or tagged me in posts asking when I would have this up. It's appreciated. It feels normal. And normalcy is something we haven't had a lot of the past 365 days. I'm glad to be back.

Preamble and Disclaimer:

As usual, these are not meant to be rules in the strictest sense of the word. They are guidelines, suggestions, items to take into consideration along with all of the other great research posted here and on other sites around the internet. Also, watch the games. Probably more advice for next year, but YouTube exists so you can still watch teams who will be playing starting Friday. In general, don't even use the numbers as hard guidelines, but the principles behind them.

Data scientists will tell you that output is dependent on input. Computers aren't magic. Normal seasons have a rhythm. They start with a slate of big OOC games with a few random mid or low-majors upsetting blue bloods (remember when Evansville beat Kentucky? That seems like it was ten years ago). Then, some buy games followed by a full conference slate. This gives the computers a generally even playing field on which to judge. This year? It's a mystery. We might see total chaos. Teams might be way overseeded or underseeded and we'll have no idea. Hell, a #3 seed and a #4 seed are coming off a COVID pause. Most of their players will be available, but they can't practice.

That's a long-winded way of saying that if all of this is completely wrong, I blame COVID.

Also, some statistics professor is going to pop in here and ask me if I backdated the dataset along the x/y axis to account for variations of the Permian equation. I did not. I'm a fan, not a mathematician. Take your questions elsewhere, nerds.

EDIT: I’ll also just urge you not to treat this as gospel. This isn’t rigorous statistical analysis. It’s just me trying to find patterns and sharing it with you. D

Hey all! I'm currently playing a Divine Soul Sorcerer with the intent of level-dipping into Life Domain Cleric and was really curious to see what the efficiency and scaling of the Healing Word spell looked like.

Using the Disciple of Life feature from Life Domain Cleric and the metamagic Twinned Spell, I made several columns using the average rolls for each spell level with different combinations of either or. Note this uses a Wisdom Modifier of +1 due to my character only having a 13 in Wisdom*. The data points would increase marginally for a higher modifier, so the value and scaling will remain constant.

^(*I intend to prepare Healing Word on my Cleric spell list rather than learning it on my Sorcerer spell list.)

Disciple of Life

Also starting at 1st level, your healing spells are more effective. Whenever you use a spell of 1st level or higher to restore hit points to a creature, the creature regains additional hit points equal to 2 + the spell's level.

Twinned Spell

When you cast a spell that targets only one creature and doesn't have a range of self, you can spend a number of sorcery points equal to the spell's level to target a second creature in range with the same spell (1 sorcery point if the spell is a cantrip). To be eligible for Twinned Spell, a spell must be incapable of targeting more than one creature at the spell's current level.

The data points for averages are as follows:

Once again, this is using the average of each roll (for a base Healing Word, it would be a minimum of 2 healing + a maximum of 5 healing, and taking the average at 3.5). Note the difference between using a Disciple of Life 1st level Healing Word vs a Twinned 1st level Healing Word. While Twinned Spell would allow for two allies to come back from being unconscious, the total healing is nearly the same.

Below is the graph with these statistics:

https://imgur.com/a/lyBGExD

Due to the combination of the incredibly focused nature of Sorcerers with their so few spells known and the pitfall of being a solo healer in a party of 4, I wanted to make the most out of my very few spells known with spells like Healing Word.

All in all, I understand that 5e makes healing very inefficient, but I wanted to figure out