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Most Clutch Playoff Teams
As season 33 drew to a close for me and the Seattle Riot in a disappointing fashion I became salty as I watched the Wolfpack came from down 3-1 in the series yet again. The salt surrounding my season got to a high level and has led me to write this article. I have looked at team’s playoff performances when there is a chance that they could be eliminated as well as when they have an opportunity win the round. I have taken data from the past four seasons, S30 to S33, because who really cares what happened before I joined this site. This analysis should provide some information about which teams are the most clutch, or lucky, depends how you look at it. The stats that I considered are wins, losses, goals for, goals against, and goal differential. This looks at which teams improve the most in these situations, not who is the best in these situations. For example, Minnesota improves the most, but New England is the best. This is because Minnesota goes from good to elite while New England goes from elite to elite, therefore they improve less than Minnesota. I had initially planned to go more in depth, however, there’s only so much time that I can spend working with Excel in my free time before I go crazy. There are 5 teams from the West that I considered: Calgary, Edmonton, Los Angeles, Seattle, and Texas; and 6 teams from the East: Buffalo, Manhattan, Minnesota, New England, Toronto, and West Kendall.
Here’s a link to the spreadsheet if you feel like perusing it: Playoff Stats
I will provide a brief overview of my findings right here as I am stretching this article out for the double pay bonus and I know no one wants to read through about 3000 words to figure out my conclusion. To come to these conclusions, I mainly looked at how the stats differ in certain situations compared to the same stats when all games are considered. I’ll start with the stats that I found regarding performance in games where a team could be eliminated. In terms of winning games, unsurprisingly, New England has the largest positive change in their winning percentage with an improvement of 27 above normal, Minnesota is not too far behind with 25. The worst by a large margin is Toronto, who has never won a game to stay alive in the past four season. Overall, I would consider Minnesota to be the team that improves the most during clutch situations. They boast a very impressive improvement in goals for and goals against which leads to their second best winning percentage.
On to my findings for games where the team can win the series. Buffalo and Texas had to be exempted from this analysis because they have not had an opportunity to win a round over the past four seasons. Like the elimination stats, Minnesota is very good at improving their winning percentage. I would consider them the best in this section because they are by far and away the best at improving their scoring during this situation. Los Angeles is a close second, but I ranked Minnesota first because Los Angeles only has a sample size of one game in this section. If Los Angeles had as big a sample as Minnesota I would put them first. Los Angeles is very good at stopping goals against in this situation which leads to their success. Like the elimination games, Toronto is the worst. They are terrible in all categories and it is no wonder why they’ve been reverse swept so much.
All in all, I feel that four seasons may not have been enough data to accurate portray performances of all teams. I would have liked to add more, but it is a lot more work. Also, the final series for season 33 was not included in the data as I put it together before the completion of the playoffs. So, let’s move on to how I came to these conclusions.
All Games
By going through the data in the indexes I put together a list of the combined stats over four seasons. The table below shows the stats for all the teams that have made the playoffs in the last few seasons. This is the table that was used for comparison.
Table 1: All Games
As can be seen from the table above, there is a varying amount of games played for each team. For example, compare New England’s 56 games to Buffalo’s 5. This most likely leads to some inexactness in statistics as some teams will have had more games to regress to their standard while others have none. Meaning, with New England the stats provide an accurate display of what you can expect from them because of their large sample size. Whereas we don’t really have too much data on Buffalo and they could be a completely different team than the data says. Although, the data says they’re bad and they’ve only made the playoffs once, so maybe it’s not completely wrong.
Another thing that this disparity in games played leads to is skewed goal differential. The teams that have played more games will have had more opportunity to rack up a large goal differential lie New England’s +37 or Calgary’s +33. It is not displayed in the table above, but during my analysis I nominalized the value so that is was goal differential per game. There may be an issue with this method, but I cannot see what it would be at the moment.
Elimination Games
This data set was a complete pain to put together, as I had to manually seek out each and every game that a team could have been eliminated. This is one of the limiting factors of why I was unable to put together more than four seasons worth of data. The table containing all of the data that was collected can be seen below, in Table 2.
Table 2: Elimination Games
What stuck out to me about this was just how many more elimination games New England has played in compared to the rest of the league. Yet even with the bigger sample size they still manage to have a 91% winning percentage. If you look at absolute performance in elimination games, then New England is way above everyone else in the league. However, I mainly looked at how much better or worst teams get when faced with elimination compared to all time. Another example of just how good (lucky) New England is, is their ridiculous goal differential. They have both the best goals per game and goals against per game by a wide margin.
The data in Table 2 was then compared to the data in Table 1 to create Table 3, as seen below. Table 3 displays how a team’s performance differs in elimination situations.
Table 3: Deviation in Elimination Chances
The cells that are highlighted green denote the best and the red denotes the worst. These colours were assigned based on whether the stat was above or below an arbitrarily chosen value.
The column for winning percentage was calculated by subtracting a team’s winning percentage in elimination games by their normal winning percentage.
The GF/G column was calculated by subtracting the GF/G in elimination situations by the normal GF/G. This difference was then divided by the normal GF/G to find this column in percentage form. This provides exactly how many percent more, or less, goals a team will score. So, for example if, say, New England normally scores 6 goals per game then they could be expected to score slightly under 7 goals per game when faced with elimination.
GA/G is calculated the same way as GF/G, except that it uses GA instead, obviously. In this case, it is better to have a negative value than a positive one.
The goal differential is taken the goal differential when faced with elimination compared to normal. This is kind of a useless stat as there is a fairly large gap between games played normally and in elimination opportunities.
Goal differential per game is my method for fixing the issue above. What I did for this stat is that I got the goal normalized the goal differential for elimination opportunities and all games then found their difference. So, it is goals for minus goals against divided by total games all for elimination games then I did the same thing for all games. Then I subtracted the value that I found for all games from the value for elimination games. This should give a fairly accurate representation of how much a team’s performance changes taking into account goal scoring, defense, and goal tending.
What this table it appears to show is that the Minnesota Chiefs are the best at upping their performance during elimination games. They have the highest goal differential per game which I consider to be one of the main analysis points. They are the best at upping their scoring in these situations, producing 17.6% more goals per game. In conjunction with that, they improve their goals against by letting in 14.3% fewer goals. On top of that they are second behind only New England in win percentage, by a measly 2%. Keep in mind that Minnesota is pretty garbage in a normal game, which means it is easier to them to up their performance compared to a team like New England who is always good.
I would consider New England to be the second most solid team in these situations as they lead in winning percentage, which is what it all comes down to. Interestingly, their goal differential per goal decreases. I am not sure what to this means, possibly that my method does not work, because their goal scoring appears to get better and their goals against also improves. How those two things can improve yet their goal differential gets worst beats me. I could probably figure it out, but I don’t think it’s worth the time it would require.
After these two teams, it is pretty much up in the air about who is third best. Los Angeles, Seattle, Manhattan, and West Kendall are all fairly average during elimination games. They tend perform pretty much the same in normal games.
After them, I would put Buffalo. They are about average, maybe slightly worst. They only have a sample size of one game so it is not really fair to evaluate them too much.
The next worst two teams are Calgary and Edmonton, which is sort of surprising. Calgary has the worst change in their goal differential. Which might not actually mean that much because it seems like a messed up stat now that I’m actually looking at it. Edmonton’s ability to score plummets during these games making it difficult for them to win games, which leads to their poor winning percentage. On top of goal scoring they manage to let in 51.3% more goals. Yet somehow their goal differential improves, further proving that I messed something up with that. I think the fact that they’re in a lower tier in this category is that normally these two teams perform at a high level, so there is more room for their performance to drop.
I would say that Toronto is probably the worst team in this situation. Their goals against increases by 61%, the most in the league. This is something that cannot happen if you want to win games. In addition, their goal scoring also falters. These two things are the cause of their absolutely abysmal winning percentage during elimination. Their winning percentage decreases by 61% in these situations. Given, they have only played two games in this situation so it is a small sample size, but they also are pretty bad.
Sample size was not taken into too much consideration during this analysis as it made my life much more complicated. I also don’t want to deal with probabilities in a paper that I am writing in my free time.
Round Winning Opportunities
The data shown below for the round winning opportunities was compiled using the same method as the elimination data. All of the categories and teams are the same.
Table 3: Round Winning Opportunities
There is a fair bit of disparity in the sample sizes for this set of data, as the good teams have played way more games than everyone else. This is due to the same teams winning season after season. New England, Calgary, Edmonton, and Toronto (because they keep getting reverse swept) have played in a ton of these games where as every other team has only played one or two, except West Kendall who is somewhere in the middle. Texas and Buffalo have not had an opportunity to win a four in the past four season and have therefore not been considered for this section.
All of the stats were calculated using the same methods as before. As I found out while writing the previous section it seems that the goal differential percentage is kind of useless because it doesn’t change how it should in terms of changes within goals for and against.
Table 5: Deviation in round winning opportunities
Like the elimination opportunities, it seems that Minnesota is the best at upping their performance in these situations. They have the second best winning percentage and their goal scoring improves drastically. They score 88.2% more goals than normal while at three wins in a playoffs series. One downside for them is that their goals against numbers suffer. Although, they allow 42.9% more goals during these situations which is the worst in the league by a significant margin. I would still consider them the best because they have a larger sample size than Los Angeles but they’re fairly similar teams.
Los Angeles has got to be considered next best in this situation. They have the best winning percentage during these situations paired with a modest increase in goal scoring and a large improvement in goals against. They have the second-best increase in goal scoring, yet it is only about half of Minnesota’s. They are, however, very far ahead of the rest of the league in terms of stopping the other team from scoring. Really, it could be a toss up between them and Minnesota for best team; depends on whether you prefer offense or defense.
Beyond Minnesota and Los Angeles there isn’t really any teams that stick out to me. Calgary, Edmonton, Seattle, Manhattan, New England, and West Kendall are all fairly average and perform about as expected. Of the teams that I just mentioned New England and Calgary are negative in winning percentage where as everyone else is positive. I account this to them being the best two teams in normal play so there is more room for them to get worst.
Again, I’m going to have to say that Toronto is the worst team in this situation. They have been reverse swept multiple times in the last four years (lol), so they’re stats in this category have taken a hit. They have the worst change in win percentage, losing a whopping 20% more games during this situation. This is due to their abysmal goal scoring. They score 26.4% less goals in this situation, which is the difference between scoring 4 goals and 3 goals. That makes a huge difference in these tight playoff games. On top of that they let in 32.3% more goals, so instead of only allowing 3 they let in 4 goals. Again, that is a large disadvantage in tight playoff games. Based on these stats it is no wonder that they have been reverse swept so much.
Keep in mind that the evaluations made in this analysis are about how much better a team performs in this situation compared to normal games. It is easy to see that New England and Calgary have the highest level of performance when they have a chance to win a round. This means that there is less room for them to improve leading these stats not reflecting how good they are. Minnesota is a mediocre team that seems to get very good during round winning opportunities, so that is why they are ranked first.
Conclusion
Based on this analysis it seems that the Minnesota Chiefs are the most clutch team when it comes to the playoffs. They are second best in winning percentage by very slim margins in both elimination games and round winning opportunities. But, what puts them over the top is their ability to score so many more goals during these clutch situations, while also allowing a modest amount less. They truly are blessed with a clutch core of players. These stats may change as they begin a new era. The undisputed most unclutch team is easily the Toronto North Stars. I feel sorry for any members of that team as you are damned to a life of losing key games. Toronto is a team that plays at a mediocre level regularly then somehow finds a way to get even worst during clutch games. The rest of the teams are fairly average in this analysis.
I found that the goal differential in percent stat that I calculated is kind of useless, so I wouldn’t put too much stock into it. Winning percentage, goals for per game, and goals against are definitely useful and were given the bulk of the weight when choosing the best teams. Another thing that may cause issues with this analysis is the poor sample sizes for some teams. Due to the nature of this league to have the same team winning over and over again, some teams have a ton of games while others have very little. I also only looked at four seasons, which does not provide enough data to see the entire life cycle of a teams’ success. Teams will rise and fall through the seasons, but this just looks at a time when the same teams remain on top.
If I were to conduct this analysis again, I would start by making a larger sample size. Ten seasons would most likely provide a better representation. An issue with this is that not all the indexes for then exist making it difficult. Another thing would be to rework the goal differential per game category, as at the moment it seems like it is broken. Making that a useful category could provide some much more useful information.
Player Page --- Update Page Picture credit to Allen, Jenny, enigmatic, Wasty, ckroyal92, 701, and EJ
300+ Career Goals, 750+ Career Points
5th All-Time Goals Scored for WKP,8th All-Time Goals Scored for SEA/TBB
3rd All-Time in Playoff Points
17th All-Time in Goals 6 Consecutive 50+ Point Seasons, 7 Total
Quote:"idc if ur naked if ur holding that cup" -Jenny
Quote:Originally posted by dankoa@Mar 31 2017, 09:19 AM Most Crutch Playoff Teams: LA
They suck so much normally, that all they can do in the playoffs is improve
Player Page --- Update Page Picture credit to Allen, Jenny, enigmatic, Wasty, ckroyal92, 701, and EJ
300+ Career Goals, 750+ Career Points
5th All-Time Goals Scored for WKP,8th All-Time Goals Scored for SEA/TBB
3rd All-Time in Playoff Points
17th All-Time in Goals 6 Consecutive 50+ Point Seasons, 7 Total
Quote:"idc if ur naked if ur holding that cup" -Jenny
Quote:Originally posted by ArGarBarGar@Mar 31 2017, 09:28 AM
I'm not so sure I agree 100% with your policework there, Lou.
Well... relative to your performance in normal games, which is pretty weak.
Player Page --- Update Page Picture credit to Allen, Jenny, enigmatic, Wasty, ckroyal92, 701, and EJ
300+ Career Goals, 750+ Career Points
5th All-Time Goals Scored for WKP,8th All-Time Goals Scored for SEA/TBB
3rd All-Time in Playoff Points
17th All-Time in Goals 6 Consecutive 50+ Point Seasons, 7 Total
Quote:"idc if ur naked if ur holding that cup" -Jenny
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