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S74 PT # 4 - Analyze Deez

Option 1

The monarchs have been battling all season to see who can score the most points in their new analytic stat, which tracks perfect non-icing clearances. The idea is who can get the perfect distance on their clearance so as to allow clean line changes, while not icing the puck by putting it too far. Meta Knight has been doing really well at this by imaging the opponent offensive zone face off dots as the center circle in curling and just trying to chip the puck so that it settles nicely and slides just onto it. Unfortunately not all the Monarchs have been able to get the skill down, leading to many players icing the puck just to try and improve their analytics, maybe this is why the Monarchs took a step back this season. Maybe the next analytic the Monarchs should try to come up with a competition around is hits on the forecheck vs hits missed on the forecheck, so there isn't an incentive to try and fail at something next season.

Written Task, Option 1

Of course, the very first thing that came to mind when Rodrigo Banes was asked to work with KDL, 'Kelowna Down-Low,' the regional hockey insider podcast, to develop a groundbreaking new hockey stat, the answer was immediately and abundantly obvious. This new analytical tool will change the face of hockey analysis forever. Called Flow/60 or F60, for short, this stat measures individual success as a contributor of building the sport and one's personal influence/brand. F60 is calculated by the length of the player's flow, in centimeters, measured from the rear of the helmet outward, multiplied by the number of hits in the game plus the number of points. The product is then divided by the number of seconds the player is on camera during the broadcast, giving you the F60 score. F60 measures impactfulness on the game, the sport, and the sporting world, demonstrated by the player's ability to generate highlights and spark discussion.

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We've got a brand new stat for all the stat heads out there. It's called the RFI, or the Ric Flair Index. This stat measures how many times a player screams "WOO" on the ice. Our crack team of staticians and mathematicians have learned through comprehensive analysis that players who yell "WOO" on the ice are more likely to make winning plays and contribute to winning in ways that are not currently accounted for in advanced hockey analytics. It is our hope that the RFI will allow us to assign value to players who might be undervalued in other metrics. We can measure RFI per player, as well as rel RFI that measures how many times a player yells "WOO" against how many times another player yells "WOO" on another team. We believe that through extensive use of the Ric Flair Index, we can figure out who is the baddest mamma jamma in the entire simulation hockey league. Can I get a WOOOOOOOO?

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PT pass (fileworker)

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The custom hockey twitter stat we'll be using is one inspired from a custom baseball stat a couple friends of mine helped devise. It is literally a stat based on how "me" a player is: Val Index (In) Utter Moment, or VALIUM, was used to find scrappy smallball baseball players that fit how I like my baseball (penalizing home runs and walks while rewarding bunting, contact hitting, and stolen bases). We'll be retaining the name because VALIUM is fucking hilarious, but for hockey let's shake things up. We'll be penalizing physical play (Hits + PIMs) while rewarding control of possession - not just Corsi, but we'll incorporate controlled zone exits and entries along with passing percentage and assists. It's tricky to incorporate goalies, however we'll devise their own VALIUM formula later that incentivizes puckhandling because the trapezoid, like most things NHL, is stupid and bad and should go away.

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Thanks to @Ragnar, @Symmetrik, @Merica, @enigmatic, and @sulovilen for the sigs! 
Avi courtesy of @MN_Moosey
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Citadelles Switzerland Stars Blizzard 
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Option 2

One of my favorite plays we run in Minnesota is the net front dummy. Basically me, the dummy, will skate into the offensive zone and get right in front of the goalie and just be as big as humanly possible. Now, what this does is allow the defense to fire bombs at the net that may just slip by due to the screen. Another thing that can happen is I just may get that big tipper and get a goal. Those are my favorite moments. At the very least, I am pissing off the opponents' defensemen with them constantly trying to get me away from the front of the net. The other forwards get to play low and look for the right pass back to the top, or to the slot for a quick wrister. It is a win win no matter who is on the ice. This strategy works best on the power play, but can be used at any time, and I am here for it.

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Specters Monarchs Berserkers Scarecrows [Image: italian-flag.jpg?s=612x612&w=0&k=20&c=tO...eKFgvtgqU=]

Specters Armada Scarecrows Czechia
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RIP Dangel #AD26  |  RIP TDZ

Option 1

The new stat is called NWPM (Naughty Words Per Minute). The purpose of the stat is to find teams that voices out most/least naughty words per minute in game situations. The idea behind this concept is a statistical find, that the amount of cursing very heavily correlates with team success. It is believed that cursing spreads negativity, and it's also a sign that something is not right. It might be that the player is not happy, they are not familiar with the team's game system or that the team is simply not clicking for whatever reason. The statistic is tracked with mics built in the helmets. After recording, an AI tool analyzes every word and classifies its naughtyness. Historically it seems that when the NWPM per player is around 1.5, the team is having difficulties and is performing worse than average. Typically the worst performing teams have a >3 NWPM, whereas the best teams may go as little as 0.1 NWPM. This season QCC has been leading the J, while Kelowna has been the worst. In SHL the leader has been Buffalo, while Manhattan has been the naughtiest.

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Option 1:

The stat we developed is aggression per 60, or shortened to AGR/60. This stat cumulates all the hits, PIMs and informal scrums within the game. These categories are also ranked - tripping might be a 1 while a cross check to the face is a 10. Put all the categories into a formula and it will give you the AGR/60 ratio. As it is in the name, the players with higher AGR/60 are your rough and tumble goons, while players with a low rating stay out of the fray, may even be "soft." Taking this analytic stat into roster building, it may be useful to see who has the "it" factor when it comes to staning your ground come playoff time. I personally likes to see players with higher AGR/60 and are pushing for those turd ferguson awards! Beck has always wanted a ferguson, and maybe some added aggression is the ticket to the promised land!

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Credit to enigmatic, Merica, and tweedledunn for sigs




Option 1: Lias has created a new stat about the most meatballs each player in the league can eat, and has correlated that with goalscoring data. He has used this to create the new stat, "Meatballs per point" or "MPP" and it measures how many meatballs each player consumed in order to fuel their points. Obviously, meatball efficiency is paramount, so a lower MPP value is better, but then there are also some real bragging rights that come with winning a league-wide meatball eating contest, so the values for this stat are kind of all over the place. That's why he had to introduce some more advanced elements. Adjusted meatballs per point (AMPP) is how many meatballs a player consumed minus the number of meatballs their teammates consumed, divided by the number of points that player scored, multiplied by eight for literally no reason at all besides it sounded good at the time. This stat will become extremely important in the future.

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O2

Nash's favorite set play on buffalo is the called the B play. Essentially the puck starts with Casey Fantobens passing the puck up into our zone. The play essentially having all of our players skating in the shape of the letter B as part of one big cycle around the net. We keep circling and passing the puck around the boards. Its an easy kind of play because we know where someone is going to be at all times. Everyone also know the alphabet and even if they don't, its literally just the second letter. B so it shouldn't be that hard to figure out. ITs the perfect letter for a cycle and people criss corssing around the ice in a pattern ONLY known within our locker room and war room. So far as you can see with Buffalo finishing second in the standings its worked out pretty well for us. Not to mention Buffalo starts with B so. We have that going for us as well. Which is nice.

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option 1

Leonard Wood's very own advanced stat is bench temperature vs moisture ratio. The stat is designed to measure how much a player plays on the ice along with his work ethic. It's meant to go far beyond just an time on ice statistic. If the bench is dry but warm, the player isn't getting much ice time and is obviously not working very hard. This player won't be getting an increase in playing time due to poor work ethic. Perhaps he should even be placed on the trade block. Now however if the bench is warm and soaking wet with sweat, it means this player is red hot! You need to get him off of the bench ASAP so he can go score some goals. If the metal bench is ice cold, it probably means someone isn't sitting there currently. Specialized sensors will be installed across the entire metal bench. The company who installs the sensors recommends players do not pass gas while sitting on the sensor as it will improperly skew the stat.

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Isfl affiliate

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we've created a new pair of stats: TSO and SO/M - Total Slime Output and Slime Output/Minute. high tech sensors in the rink can detect slime outputs left by players on the ice and on the boards - it gathers measurements during tv timeouts and retroactively matches slime detected to player movement throughout the course of play. this technology was developed by researchers at University of Oregon doing really important research at the specific request of their famous alum/mascot Puddles Of Duck @Z-Whiz and just rolled out this season for mainstream usage.

philippe eko eel is the perennial leader in this category because he is an eel and much slimier than most players because they are humans who are often less slimy than eels. second in these metrics is almost always red kirkby @Acsolap - he is a human but he's just such an incredible perverted skeezy slimeball that he also oozes slime on the ice at nearly the rate an eel does

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thanks @Carpy48 and @frithjofr and @rum_ham and @Julio Tokolosh and @Briedaqueduc for the sigs
Armada Inferno norway

With the advances in the scientific fields, a stunning new study came to fruition when it was discovered that a persons foot size has a great deal to do with how fast they can skate. This seemingly generic study broke new ground when it differentiated the size of a persons foot compared to the length of their toes. A never done before aspect of the foot to speed statistic. So Mads joined with a local texan blog to track, not only his speed to toe length but other Renegades as well. Unfortunately, the study took a turn for the worse when several players discovered pictures of their feet were being sold online. This has caused quite the uproar amongst the team and many people have been accused of profiting from this. Due to those unforeseen circumstances, the study and all materials associated with the new statistic has been permanently erased after the judges ruling.

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