So we had another cycle of U23 mixed. We won gold again, but didn't win the spirit award. Two years ago I put down some numbers regarding the number of touches our women had compared to our opponents in the finals (Canada). I figured I would run some of the same numbers to see how we "did" this time.
Anecdotally I felt like we used our women well this cycle, perhaps as well as we did in 2013. While we had fewer women around the disc (Claudia, Sophie and Tash in 2013 and only Q and Clare in 2015) we did a great job having more effective female cutters downfield. Also the finals were significantly less windy than in 2013, which gave us more confidence in throwing to our women. I can't remember a single instance of a woman missing a pass and not getting thrown to next time we were open. It is something that our team focuses on (putting people in places to succeed and giving them that chance when it is there) and both cycles really delivered on it.
In contrast the Aussies were running a different offensive style that was better suited for mixed exploitation (in that it used the fact that there were different genders on the field better) but used the women less.
Let's see how the numbers look. There were 252 points of contact (catches) for USX and of that 62 were by women. That breaks down to about 25% and is therefore a contact ratio of 3:1. So for every contact by a woman there were three by a man. The Australians had 118 points of contact with only 15 by women. That is a very low 13% or a 8:1 contact ratio. We also noted that of our 17 goals, 13 were on possessions where a woman touched the disc, 4 were caught by women and 6 were thrown by women.
We also noted that it took us 34 possessions to score 17 goals (exactly a 2.00 Possessions Per Goal that I felt indicated the difference between elite and good college teams) while the Bluebottles (which is apparently a jellyfish) scored 4 out of 33 possessions.
Again, I have no idea what any of this means. I think Australia's success (which I guess I should write about at some point) shows that a more balanced contact ratio doesn't necessarily indicate success. But one of our goals was to use our women to win games and these numbers feels like they support that.
Of interesting note, our contact ratio is actually worse than it was in 2013. I feel like much of that is due to the occasional use of a 4-2-1 wall zone defense by the Australians. Canada played almost exclusively man in 2013, and while zone defense did allow Q more touches, that was only on the lines where she was on the field. There were two points where we didn't have a line conducive to female handling on the field against their softer zone. Those points involved a ton of short passes between un-marked men for basically zero yards. Looking at the touches during those points there were 82 touches but only 16 were by women (leading to a ratio of 33:8 or 4.125:1). Removing those points from the previous data leads to a contact ratio of 2.7:1.
Tuesday, August 04, 2015
Friday, June 12, 2015
What Is The Value of a Break?
So what is the value of a break? Every point in ultimate is worth one point in the game, so it seems like the answer to that question you be "one." But in the elite game we all expect offensive holds and cherish breaks.
I wanted to get a better sense of breaks because I was looking at Draymond Green's plus minus rating from game four of the NBA finals and adjacent to the stat was his real plus minus. While we can easily look at an ultimate players normal plus minus (stat heavy leagues like the AUDL have those values on their stats pages already), but how can we adjust those numbers?
I guess we could do some sort of heavy adjustment talking about when the break happens, but that seems a step too far right now. Let's just set a simple bar and see if people tear it apart in the comments.
First, it is silly to think about most elite ultimate as single point endeavors. I don't have the numbers in front of me (this is part of a different project for this summer) but if the Possessions Per Goal (PPG) metric for a team is greater than two it means they will need two possessions to score and that somewhat means that a single turnover is likely on any given point. I ran the college numbers for ~12 games this season, and it seems like the most elite college teams can operate at sub 2.0 PPG, so let's assume that club teams can do similar or better. What that leaves us with is that a turnover in a possession is still unlikely (again, data unlikely) which holds with our expectation of club where offensive holds are expected.
With many elite club teams operating with an offensive line and a defensive line it makes more sense to think of a "round" of ultimate as being a two point exchange. At any given time the actual "score" of the game should reflect that exchange, and one way to do that is to include half-point into the scoring system. For example, if you receive the pull and throw a goal making the score 1-0, the score is actually +0.5 (where the plus indicates your team's value, it would be -0.5 for the opponent). Upon the opponent scoring it would be driven back to +0.
Perhaps this comes from a mental game as a coach, where you tell your team that a lead isn't as big as it thinks it is. Being up 4-3 but pulling means you aren't up at all. But at the same time the half-score offers something that just pure breaks doesn't allow, an indication of who will win. True, games are won by the number of breaks you get. Sure, if you get more breaks than your opponent then you will win the game. But if we just track breaks then who wins with a score of 0? The team that wins the flip! So there is good cause to think that is terms of game states the flip is worth +0.5.
Game state isn't the same as plus minus. The point of looking at the value of the flip is that it shows you the value of the change of "serve" of the game: +0.5. So if we treat an offensive hold as +1 (which seems like a good baseline) then we can argue that a break should be worth +1.5.
That is a simple formula. A players plus minus is: (O-points scored+1.5*D-points scored)/points played.
I suppose we could go with a more mathematically complicated model where we scale the break multiplier based on the number of breaks in a game. Something along the lines of
(O-points scores+(1.5-0.1*Game D-Breaks Scored)*D-points scored)/points played
This would reduce the value of your break based on the number of breaks in a game. That kind of makes sense, and perhaps allows the statistic to be used on a wider level of play. In games where offensive holds are difficult the value of a break would eventually get below 1, making it less valuable than an offensive hold.
So what are we trying to do with this statistic? The number can only fluctuate between 0 and 1.5 and would seem to measure the value of a point with a person on the field. Odds are your best offensive players are going to be just above 1.0 while a defender with a number greater than 1.0 is a godsend.
I've got some film to watch to look at PPG in the club division. Maybe I'll go through some college games and track this or track it while I am following a few club games.
I wanted to get a better sense of breaks because I was looking at Draymond Green's plus minus rating from game four of the NBA finals and adjacent to the stat was his real plus minus. While we can easily look at an ultimate players normal plus minus (stat heavy leagues like the AUDL have those values on their stats pages already), but how can we adjust those numbers?
I guess we could do some sort of heavy adjustment talking about when the break happens, but that seems a step too far right now. Let's just set a simple bar and see if people tear it apart in the comments.
First, it is silly to think about most elite ultimate as single point endeavors. I don't have the numbers in front of me (this is part of a different project for this summer) but if the Possessions Per Goal (PPG) metric for a team is greater than two it means they will need two possessions to score and that somewhat means that a single turnover is likely on any given point. I ran the college numbers for ~12 games this season, and it seems like the most elite college teams can operate at sub 2.0 PPG, so let's assume that club teams can do similar or better. What that leaves us with is that a turnover in a possession is still unlikely (again, data unlikely) which holds with our expectation of club where offensive holds are expected.
With many elite club teams operating with an offensive line and a defensive line it makes more sense to think of a "round" of ultimate as being a two point exchange. At any given time the actual "score" of the game should reflect that exchange, and one way to do that is to include half-point into the scoring system. For example, if you receive the pull and throw a goal making the score 1-0, the score is actually +0.5 (where the plus indicates your team's value, it would be -0.5 for the opponent). Upon the opponent scoring it would be driven back to +0.
Perhaps this comes from a mental game as a coach, where you tell your team that a lead isn't as big as it thinks it is. Being up 4-3 but pulling means you aren't up at all. But at the same time the half-score offers something that just pure breaks doesn't allow, an indication of who will win. True, games are won by the number of breaks you get. Sure, if you get more breaks than your opponent then you will win the game. But if we just track breaks then who wins with a score of 0? The team that wins the flip! So there is good cause to think that is terms of game states the flip is worth +0.5.
Game state isn't the same as plus minus. The point of looking at the value of the flip is that it shows you the value of the change of "serve" of the game: +0.5. So if we treat an offensive hold as +1 (which seems like a good baseline) then we can argue that a break should be worth +1.5.
That is a simple formula. A players plus minus is: (O-points scored+1.5*D-points scored)/points played.
I suppose we could go with a more mathematically complicated model where we scale the break multiplier based on the number of breaks in a game. Something along the lines of
(O-points scores+(1.5-0.1*Game D-Breaks Scored)*D-points scored)/points played
This would reduce the value of your break based on the number of breaks in a game. That kind of makes sense, and perhaps allows the statistic to be used on a wider level of play. In games where offensive holds are difficult the value of a break would eventually get below 1, making it less valuable than an offensive hold.
So what are we trying to do with this statistic? The number can only fluctuate between 0 and 1.5 and would seem to measure the value of a point with a person on the field. Odds are your best offensive players are going to be just above 1.0 while a defender with a number greater than 1.0 is a godsend.
I've got some film to watch to look at PPG in the club division. Maybe I'll go through some college games and track this or track it while I am following a few club games.
Thursday, April 09, 2015
Looking at numbers
I have a job for the Atlanta based AUDL team the Atlanta Hustle. I think my title is technically "advance scout" which basically means I'm going to look at film and try to give assessment docs to the coach so he can map out practices and strategy.
Anyway, the GM is a numbers guy, so I think I'll need some numbers/video to back up my assessments. Good thing the later is my strong suit. The former I need some work on, so that is what I have been doing recently.
I have a poor relationship with ultimate statistics. I loved the work that Ultiworld did a long time ago through tracking every flipping pass in NexGen games. But that app is dead, and I don't really know to do with a chart that shows me a team's scoring probability based on field position. I guess it could expose that a team is particularly weak in the coffin corner, but in general I don't know what else I can get from that information.
So this high school season, since I am a sub-called, I decided to play around with statistics for the team. We haven't been having our most successful year so I started tracking the number of unforced errors and the number of possessions. It hasn't really righted the ship, but it is interesting what the numbers show.
First a bit on "unforced errors." In order to get around the tricky subjectivity problem I decided that if the defense doesn't touch the disc it is an unforced error. There are some strange things that fall into that category that make the numbers hard to really analyze. For example a punt in the wind is considered an unforced error, as is a high stall punt that no one touches. Also a jump-ball that the defense doesn't actually touch (but they clearly influenced the play) counts as an unforced error. It would make sense to fix some of these issues, but then we get into the subjectivity of "was that a punt or a huck too far?" Or "how much did the defender actually influence that drop?" These are things that I want to avoid so I'm keeping it pure.
Basically unforced errors are possessions that end with you giving away the disc, which means you aren't making the defense take it from you, which is a bad thing . . . right? So I took the number of unforced errors, divided by the number of possessions and we now have UE% which tells us the percentage of possessions that end in unforced error.
For Paideia that number was frighteningly high (~50% or more at times) which pointed out how we were really beating ourselves. If we could improve on that number then we would at least be asking more of our opponent. I don't want to get into Paideia's season, but it has been having a good impact. One other thing I was able to track was what I am calling our "Conversion Rate" which is just the number of possessions divided by the number of scores. An average of this over multiple games tells us how many times we need the disc (on average) in order to score.
Here is where I feel like I got into something that was useful, tracking possessions. In the past many teams have been concerned with offensive holds and defensive breaks. But a defensive break that requires 4 possessions to score isn't the same as break that only takes one. I think moving away from line-based statistics and moving toward possession based statistics will offer some new insights to analyzing the sport.
After playing with this for a little bit I wondered what was a reasonable UE%? Did it change per level of play? So I set off looking at college games from this season. I have made it through just over 20 games and here is what I have found.
The average UE% of the games that Ultiworld has filmed is around 30.79%. The funny thing is that the average for a winning team isn't any lower than that of a losing team (30.75% vs 30.83%). What is even more interesting is winning the UE% battle isn't a good indicator of success. Plenty of teams have won their games despite having a worse UE% than their opponent. I guess this would speak to the idea of there being "good" turnovers. This metric still gives us a glimpse of how many times on average a good/elite college team will just give you the disc back. Looking at the similar numbers for the college women's game and the club games might provide more support for what we assume (better levels of play make fewer "mistakes").
The real insight came from conversion rate. First of all, looking at the conversion rate of a single game is boring. Because possessions for each team are never more than one away from each other if you win the game you won the conversion rate. This is one of the things I hate about certain statistics like "breaks" and "turns." Guess what, if you get more breaks than your opponent you won the game. If you commit fewer turns, you won the game.
But this metric did offer some insight over a number of games. For example, there seems to be a clear line between the best teams and the next step down. Elite teams (Pitt, Oregon, UNCW) have a conversion rate that is typically sub 2.00. Other teams tend to operate above that mark, with some of the worst being as high as 3+ (which is where my high school team operates at times). It is no surprise that the average for winning teams would be lower than that for losing teams. Conversion Rate basically tells you the number of possessions you need to score (on average) so winning means a lower number. The winning teams have an average of 2.06 while the losing teams have an average of 2.47. There are some teams that lose with a CR below 2. Those are typically good, or at least efficient, games.
What I'm curious about now is how good a predictor average CR for a pair of teams is for the game's outcome. In general does the team with the lowest CR win future games. How should standard deviation of CR play into that calculation. Washington has a poor CR (2.41) but was able to post one sub-2.0 number. Could they get hot and beat an elite team by putting up their best efficiency number (1.83). Pitt (1.76!) has a fairly stable CR, so the likelihood of getting a "bad" game out of them seems low.
I feel like there is some room for innovation there. Given enough data we could look at the effect a "good defensive team's"impact on opponent's CR as compared to that opponent's average CR. Anyway, I have to go. Hopefully I didn't ramble too much.
Anyway, the GM is a numbers guy, so I think I'll need some numbers/video to back up my assessments. Good thing the later is my strong suit. The former I need some work on, so that is what I have been doing recently.
I have a poor relationship with ultimate statistics. I loved the work that Ultiworld did a long time ago through tracking every flipping pass in NexGen games. But that app is dead, and I don't really know to do with a chart that shows me a team's scoring probability based on field position. I guess it could expose that a team is particularly weak in the coffin corner, but in general I don't know what else I can get from that information.
So this high school season, since I am a sub-called, I decided to play around with statistics for the team. We haven't been having our most successful year so I started tracking the number of unforced errors and the number of possessions. It hasn't really righted the ship, but it is interesting what the numbers show.
First a bit on "unforced errors." In order to get around the tricky subjectivity problem I decided that if the defense doesn't touch the disc it is an unforced error. There are some strange things that fall into that category that make the numbers hard to really analyze. For example a punt in the wind is considered an unforced error, as is a high stall punt that no one touches. Also a jump-ball that the defense doesn't actually touch (but they clearly influenced the play) counts as an unforced error. It would make sense to fix some of these issues, but then we get into the subjectivity of "was that a punt or a huck too far?" Or "how much did the defender actually influence that drop?" These are things that I want to avoid so I'm keeping it pure.
Basically unforced errors are possessions that end with you giving away the disc, which means you aren't making the defense take it from you, which is a bad thing . . . right? So I took the number of unforced errors, divided by the number of possessions and we now have UE% which tells us the percentage of possessions that end in unforced error.
For Paideia that number was frighteningly high (~50% or more at times) which pointed out how we were really beating ourselves. If we could improve on that number then we would at least be asking more of our opponent. I don't want to get into Paideia's season, but it has been having a good impact. One other thing I was able to track was what I am calling our "Conversion Rate" which is just the number of possessions divided by the number of scores. An average of this over multiple games tells us how many times we need the disc (on average) in order to score.
Here is where I feel like I got into something that was useful, tracking possessions. In the past many teams have been concerned with offensive holds and defensive breaks. But a defensive break that requires 4 possessions to score isn't the same as break that only takes one. I think moving away from line-based statistics and moving toward possession based statistics will offer some new insights to analyzing the sport.
After playing with this for a little bit I wondered what was a reasonable UE%? Did it change per level of play? So I set off looking at college games from this season. I have made it through just over 20 games and here is what I have found.
The average UE% of the games that Ultiworld has filmed is around 30.79%. The funny thing is that the average for a winning team isn't any lower than that of a losing team (30.75% vs 30.83%). What is even more interesting is winning the UE% battle isn't a good indicator of success. Plenty of teams have won their games despite having a worse UE% than their opponent. I guess this would speak to the idea of there being "good" turnovers. This metric still gives us a glimpse of how many times on average a good/elite college team will just give you the disc back. Looking at the similar numbers for the college women's game and the club games might provide more support for what we assume (better levels of play make fewer "mistakes").
The real insight came from conversion rate. First of all, looking at the conversion rate of a single game is boring. Because possessions for each team are never more than one away from each other if you win the game you won the conversion rate. This is one of the things I hate about certain statistics like "breaks" and "turns." Guess what, if you get more breaks than your opponent you won the game. If you commit fewer turns, you won the game.
But this metric did offer some insight over a number of games. For example, there seems to be a clear line between the best teams and the next step down. Elite teams (Pitt, Oregon, UNCW) have a conversion rate that is typically sub 2.00. Other teams tend to operate above that mark, with some of the worst being as high as 3+ (which is where my high school team operates at times). It is no surprise that the average for winning teams would be lower than that for losing teams. Conversion Rate basically tells you the number of possessions you need to score (on average) so winning means a lower number. The winning teams have an average of 2.06 while the losing teams have an average of 2.47. There are some teams that lose with a CR below 2. Those are typically good, or at least efficient, games.
What I'm curious about now is how good a predictor average CR for a pair of teams is for the game's outcome. In general does the team with the lowest CR win future games. How should standard deviation of CR play into that calculation. Washington has a poor CR (2.41) but was able to post one sub-2.0 number. Could they get hot and beat an elite team by putting up their best efficiency number (1.83). Pitt (1.76!) has a fairly stable CR, so the likelihood of getting a "bad" game out of them seems low.
I feel like there is some room for innovation there. Given enough data we could look at the effect a "good defensive team's"impact on opponent's CR as compared to that opponent's average CR. Anyway, I have to go. Hopefully I didn't ramble too much.
The re-emergence of the pivot reset (Incomplete)
Two years ago I would have argued that I watch about as much film on ultimate as anyone with a job (there was no way that I could keep up with some high school kid's youTube binging). That isn't really the case anymore with the proliferation of film through the now defunct NexGen, Sky'd and Ultiworld. I still watch a lot of film, but I find less of a need to spout off about things that I see now that there are other (arguably more capable) people doing that.
But watching the Stanford women's team's games from this year's Stanford Invite I saw the re-emergence of a move that has been building for a few years, and so I feel the need to point it out.
When explaining a vertical stack I will at times refer to the person at the front of that stack as the "Pivot." The idea is that when the disc swings from one third to the other the top of the stack is the rotation point (pivot) of that swing. We all know what a reset is.
The pivot reset is by no means a new idea. I first learned of it over a decade ago from a former Godiva player, who used it over a decade before that as the primary reset style. So let me have a brief history lesson while understanding that despite playing for 20+ years I'm talking about things older than myself and am bound to get something wrong.
There was a time when the concept of having a player behind the disc seemed ridiculous (at least to me). We want to move the disc forward, so that is where the people should be. If a person couldn't get open by 10 (which was longer back then) then we would punt. While my team was stuck punting some teams had figured out how to reset the count from the front of the stack. One of those teams was Lady Godiva.
The idea of Godiva's reset structure was that the first two people in the stack were the resets. If flow couldn't continue those people would run a specific pattern. This involved cutting forward to break your defenders positioning (either by turning their hips or getting them to backpedal) then a 90 turn to either side. The next person would then do the same to the other side. Weaklings would default to the open side, which would still work often. But Godiva players were good at throwing the around so they would use that break often.
This isn't exactly a pivot reset, but lays the groundwork for what happened almost 20 years later. The vertical stack changed drastically in the 90's (Tiina, help me out here and tell me how wrong I am). We moved resets behind the disc because there was more space there and the forward reset died off a bit. Then horizontal offenses became en-vogue and the whole structure of resets changed for a while.
Some college teams, and maybe even some club teams would run a front of the stack reset, but it had moved out of the zeitgeist. As few as 6 years ago I started noticing more New England college teams running it, perhaps as Godiva players started coaching or because defenses became bad at it. There were evolutions to the system, and it didn't much look like what Godiva ran decades before. (This was probably a good choice because what Godiva ran required solid discipline and excellent timing, which are not abundant in the college division).
Instead teams were often running it with a backfield reset as well. The backfield would serve as a primary, and if that wasn't working then they would shift to the front. This made tons of sense and was a logical continuation of a horizontal reset scheme where you look at one side and if that doesn't work you check with the other side that is running counterflow.
Those college players eventually move to club, and club defenses get used to particular offenses, so lo-and-behold we can see club teams using this strategy more and more. But still it was more regulated to the northeast than other schemes. Ironside has been using it more and more over the past few years. It is difficult to defend against, especially with the increase in off-hand throws and creative breaks. The pivot defender has to choose between overplaying the breakside to prevent this reset and allowing the openside pass, or play to the openside and risk being exposed by a (tight-windowed) break. I'll get into defending this later.
But the thing that convinced me that this is coming back was Stanford's use of this system. This is a west coast team utilizing a scheme that is entrenched in northeast history. So apparently someone was paying attention and soon other teams will be as Stanford's women's team looks pretty darn good right now. Despite being understaffed from a roster standpoint, Stanford hung with powerhouse Oregon by using this reset scheme.
In the clip below (sorry for its length) Annee Rempel (#15) is playing the pivot through a series of throwers. When she gets the disc and throws it, she clears back to the front. When the thrower is in trouble she knows to expect a throw to the break side. She even bites on a Stephanie Lim breakmark flick, thinking that it might be for her.
Is this a model for teams that are under-athletic to compete against large schools and their hulking athletes? Not so fast.
First let's analyze the modern iteration of this scheme. The primary reset is still behind, but you have a secondary reset at the front of the stack. When the disc is on the wide side of the field the pivot has the skinny lane as an option (something similar to a pocket pass in basketball). When the thrower looks at the pivot they then get the option of juking to get open. When the disc is trapped this system doesn't work as effectively, but you still can use the pivot to replenish a backfield reset when the original reset cuts downline.
One thing that is particularly difficult about this reset is the possibility of the pivot post. A "post" is basically the same as a post-up entry pass. The pivot is in position and the thrower is just going to put it to a space knowing that the pivot has best line of sight and should be able to get to it first. This post happens often on a backfield reset when the defender is playing straight up. But a pivot post is incredibly difficult to defend without losing position on the pivot. In order to prevent the post you need to be able to see the disc, but you can't see the disc without at least turning 90 degrees on the pivot, which gives them an advantage towards one direction. Due to the short length of the throw, that isn't much time for a defender to recover from that advantage. So to take away the advantage the pivot defender will play straight-up (faceguarding), which opens up the post pass. You can see the issue.
This is why it was working so well for Stanford. Looking at their percentage of unforced errors per possession in the finals against Oregon it was a jaw dropping 29%. Much of that was because Oregon was getting blocks, but it also means that Stanford was only giving away the disc only three out of ten times. By contrast Oregon's %UE was upwards of 43% (mostly on long hucks). Stanford was able to keep possession and in large part it was due to this reset system and excellent handing.
And that is really the key to this scheme, you need to have great handlers. They need to have some good throws to tight spaces (such as Monisha White's use of her lefty backhand) and they need to be able to lead a pass well when needed. Your resets (both front and back) need to be able to stay close without clogging lanes. If your back reset creeps in too much they allow their defender to sag into the throwing lane without being punished. If your pivot reset shifts to the openside too early they alert their defender while also crimping the openside pass.
So I don't think this is a scheme that just any team can work with and expect success. But if you are a team with some incredibly strong handlers with good vision and chemistry (looking at you Texas A&M) this becomes a viable structure that can allow you to hang with more athletic teams while saving your legs for sunday.
But watching the Stanford women's team's games from this year's Stanford Invite I saw the re-emergence of a move that has been building for a few years, and so I feel the need to point it out.
When explaining a vertical stack I will at times refer to the person at the front of that stack as the "Pivot." The idea is that when the disc swings from one third to the other the top of the stack is the rotation point (pivot) of that swing. We all know what a reset is.
The pivot reset is by no means a new idea. I first learned of it over a decade ago from a former Godiva player, who used it over a decade before that as the primary reset style. So let me have a brief history lesson while understanding that despite playing for 20+ years I'm talking about things older than myself and am bound to get something wrong.
There was a time when the concept of having a player behind the disc seemed ridiculous (at least to me). We want to move the disc forward, so that is where the people should be. If a person couldn't get open by 10 (which was longer back then) then we would punt. While my team was stuck punting some teams had figured out how to reset the count from the front of the stack. One of those teams was Lady Godiva.
The idea of Godiva's reset structure was that the first two people in the stack were the resets. If flow couldn't continue those people would run a specific pattern. This involved cutting forward to break your defenders positioning (either by turning their hips or getting them to backpedal) then a 90 turn to either side. The next person would then do the same to the other side. Weaklings would default to the open side, which would still work often. But Godiva players were good at throwing the around so they would use that break often.
This isn't exactly a pivot reset, but lays the groundwork for what happened almost 20 years later. The vertical stack changed drastically in the 90's (Tiina, help me out here and tell me how wrong I am). We moved resets behind the disc because there was more space there and the forward reset died off a bit. Then horizontal offenses became en-vogue and the whole structure of resets changed for a while.
Some college teams, and maybe even some club teams would run a front of the stack reset, but it had moved out of the zeitgeist. As few as 6 years ago I started noticing more New England college teams running it, perhaps as Godiva players started coaching or because defenses became bad at it. There were evolutions to the system, and it didn't much look like what Godiva ran decades before. (This was probably a good choice because what Godiva ran required solid discipline and excellent timing, which are not abundant in the college division).
Instead teams were often running it with a backfield reset as well. The backfield would serve as a primary, and if that wasn't working then they would shift to the front. This made tons of sense and was a logical continuation of a horizontal reset scheme where you look at one side and if that doesn't work you check with the other side that is running counterflow.
Those college players eventually move to club, and club defenses get used to particular offenses, so lo-and-behold we can see club teams using this strategy more and more. But still it was more regulated to the northeast than other schemes. Ironside has been using it more and more over the past few years. It is difficult to defend against, especially with the increase in off-hand throws and creative breaks. The pivot defender has to choose between overplaying the breakside to prevent this reset and allowing the openside pass, or play to the openside and risk being exposed by a (tight-windowed) break. I'll get into defending this later.
But the thing that convinced me that this is coming back was Stanford's use of this system. This is a west coast team utilizing a scheme that is entrenched in northeast history. So apparently someone was paying attention and soon other teams will be as Stanford's women's team looks pretty darn good right now. Despite being understaffed from a roster standpoint, Stanford hung with powerhouse Oregon by using this reset scheme.
In the clip below (sorry for its length) Annee Rempel (#15) is playing the pivot through a series of throwers. When she gets the disc and throws it, she clears back to the front. When the thrower is in trouble she knows to expect a throw to the break side. She even bites on a Stephanie Lim breakmark flick, thinking that it might be for her.
Is this a model for teams that are under-athletic to compete against large schools and their hulking athletes? Not so fast.
First let's analyze the modern iteration of this scheme. The primary reset is still behind, but you have a secondary reset at the front of the stack. When the disc is on the wide side of the field the pivot has the skinny lane as an option (something similar to a pocket pass in basketball). When the thrower looks at the pivot they then get the option of juking to get open. When the disc is trapped this system doesn't work as effectively, but you still can use the pivot to replenish a backfield reset when the original reset cuts downline.
One thing that is particularly difficult about this reset is the possibility of the pivot post. A "post" is basically the same as a post-up entry pass. The pivot is in position and the thrower is just going to put it to a space knowing that the pivot has best line of sight and should be able to get to it first. This post happens often on a backfield reset when the defender is playing straight up. But a pivot post is incredibly difficult to defend without losing position on the pivot. In order to prevent the post you need to be able to see the disc, but you can't see the disc without at least turning 90 degrees on the pivot, which gives them an advantage towards one direction. Due to the short length of the throw, that isn't much time for a defender to recover from that advantage. So to take away the advantage the pivot defender will play straight-up (faceguarding), which opens up the post pass. You can see the issue.
This is why it was working so well for Stanford. Looking at their percentage of unforced errors per possession in the finals against Oregon it was a jaw dropping 29%. Much of that was because Oregon was getting blocks, but it also means that Stanford was only giving away the disc only three out of ten times. By contrast Oregon's %UE was upwards of 43% (mostly on long hucks). Stanford was able to keep possession and in large part it was due to this reset system and excellent handing.
And that is really the key to this scheme, you need to have great handlers. They need to have some good throws to tight spaces (such as Monisha White's use of her lefty backhand) and they need to be able to lead a pass well when needed. Your resets (both front and back) need to be able to stay close without clogging lanes. If your back reset creeps in too much they allow their defender to sag into the throwing lane without being punished. If your pivot reset shifts to the openside too early they alert their defender while also crimping the openside pass.
So I don't think this is a scheme that just any team can work with and expect success. But if you are a team with some incredibly strong handlers with good vision and chemistry (looking at you Texas A&M) this becomes a viable structure that can allow you to hang with more athletic teams while saving your legs for sunday.
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