May the odds be in your favor

Or the story about the Finnish hockey league play-off odds. (And how one of these days I’ll actually have to read and/or watch The Hunger Games, considering how much I quote them.)

The play-offs are in full swing in Finland, at least if by “full swing” one means the extra “pity play-off” round went as it was supposed to go given the regular season standings, and the next round starts today.

I’ve posted earlier about the play-off probabilities in general, but this time I decided to focus on something slightly different. I though I’d calculate the odds of each match-up, simplifying heavily by considering the regular season win percentages as a proxy for team quality, but by considering home and away win percentages separately. There are two reasons for this:

1) Home advantage is an actual thing. It has been shown to exist in studies, and can be tracked down to small, yet significant, rules favoring the home team. Plus the “intangibles”, such as fan encouragement, and/or the pressure to play well because your mom is watching.

2) The teams in the Finnish league have very different win percentages when broken down to home and away games.

Taking a closer look at this, the win percentage is simply games won over games played. Contrary to the Finnish league’s (and all other leagues’ for that matter, and this is a whole other issue in and of itself) I treated each win as equal, regardless of whether it took place in regular game time or in overtime or shoot-out. A win is a win.

This revealed some rather disturbing issues. For example for Blues, a team that finished fifth in regular season and now faces JYP in the play-offs. Blues won 36 games in regular season. JYP, the team that will have home advantage in the play-off series, won 33 games. In fact, the only team that won more games than Blues, was Kärpät, the team that won the regular season! So now we have a team with win percentage of 60% playing a team with 55% win percentage, and the weaker team starts at home.

win percentages home and away

Once the win percentages are calculated separately for home and away games, the figures prompt some interesting questions. Like stated above, the home advantage is a real thing, largely because of the several points in the rules advantageous to the home team, for example the right to put players on the ice last, and thus making it easier to play specific players against other teams top players. And true to form, the teams making the play-offs had higher win percentages at home than away, except for SaiPa (8th in regular season) who played the same regardless of the arena.

Since the rules are the same for all home teams, one could argue that the differences in home win versus away wins changes according to the non-rules related variables, such as home crowd input (the players often mention an active home crowd is “the extra player on ice” giving them an advantage, and even yours truly isn’t quite cynical enough to think that is simply lip-service to sell tickets) or unintentional bias by the referees in favor of the home team, often credited to a pressure from active crowd.

While the above would feel intuitively pleasing, and is supported by the large differences in the win percentages of famously active and attentive home audience at Kärpät and HIFK games (for Kärpät, the home w% is 76,67 and away w% 56,67, whereas for HIFK they are 66,67% and 43,33% respectively), the theory fails for Blues. Displaying some of the weakest attendance figures in the league, Blues is really rocking it on home ice: their win percentage at home is 76,67%, better than all other teams’ except for Kärpät with whom they tie. When away, however, they tie for the second-to-last place with JYP and HIFK with 43,33%.

Another team that needs to up their away game is KalPa. Second-highest home win percentage (behind only of Kärpät and Blues) of 70% is brought down to a mere 55% overall, when you only win 40% of your away games. That’s the weakest of the Top 8 -teams.

What this means in terms of the play-off match-ups, then?

First I used only the over-all win percentage as a measure of team strength, that is, ignored the home team advantage, and calculated the odds of each team winning their respective best-out-of-seven series. Kärpät-SaiPa series would go to Kärpät with a probability of 51,42%. Tappara would defend their higher-ranking regular season finish, winning the series against HIFK with 50,71% probability. Lukko-KalPa would end up with a surprise victory by KalPa, at least with the likelihood of 51%. And with a probability of 51,46% visiting team Blues would continue to win more games than JYP.

But, since the home ice did seem to influence rather largely to the teams’ win percentage (unless you’re SaiPa), what are the odds of the home-starting teams taking the series? Unlike in the NHL where the team finishing higher in regular season hosts the first two games and then visits for two after which they alternate if needed, in Finland the home team changes after every game. Still, in a full 7-game series that gives 4 home games to the team with higher rank, as opposed to three.

In the first two pairings, regular season winner Kärpät playing SaiPa and second-placer Tappara playing HIFK, the home team (the team starting home) simply increases their odds of winning. Kärpät takes the series with a probability of 62,51% and Tappara with 56,57%. The difference in team strengths is considerable enough, that even if we turn things around and pretend the weaker team gets to start at home (SaiPa and HIFK, respectively), Kärpät would still win with probability of 60,24% and Tappara with 51,86%.

With the Lukko-KalPa match-up the odds are in Lukko’s favor as long as they get to start at home (which they do). The home advantage means they have a 51,44% chance of making it to the next round, whereas if the teams started on the KalPa home ice, KalPa would take the series with the probability of 54,5%. Remember that with the aggregate win percentages the series would also go to KalPa (51%). That’s because KalPa has a higher win percentage than Lukko, 55% to Lukko’s 51,67%, due to actually winning more games in the regular season.

With home advantage, JYP with over-all win percentage of 55% clinches the series with probability of 50,28%. If they started at Espoo, Blues’ solid performance at home would bring them the series with a probability of 57,64%. As stated above, with aggregate win percentages Blues (with 60% win percentage) would win the series with a probability of 51,46%. So really, the odds are in Lukko and JYP’s favor simply because of the home advantage they got due to the way wins in regular time versus overtime are valued in the league.

What’s going to happen, then?

Well I can say for certain that the following will happen: either the team starting at home or the team starting away will win. It’s the play-offs. Best out of seven games. Anything can happen. The odds above are not a prediction, they are simply what it says on the tin: probabilities of winning the best-out-of-seven series, given regular season win percentages. It doesn’t take into account team-versus-team performance, or game plans, or who’s injured, or who’s having a bad day, or which team’s got their groove on. All of which will play a role in a play-off series.

But the above does tell us something: if we assume the point in hockey is to win games, and thus the team that wins more games is better than the team that wins less games, we are not rewarding the best teams of the regular season with home advantage in the play-offs.

We’re actually leveling the playing field.

Fan demand in hockey: what, where and why? Part 1

Every fall the media in Finland starts drumming up concern over how hockey fans aren’t finding their way to the stands. This time it started already during last season when Jokerit announced they’ll be joining the KHL for the 2014-15 season, and the hockey media in unison declared that to be catastrophic in terms of fan interest in the Finnish league.

I’ve been thinking about that whole thing for a while now, and decided to do some digging. Realizing that my posts in this blog are getting out of hand in terms of length as it is, I also decided to write about this whole thing, fan demand in hockey, in a series of posts. So welcome to the first installment of the Hockey Demand -series!

Is the Finnish media right? Is the fan interest dramatically diminished, compared to last season? Are fans gone from hockey? I thought I’d start the series by looking at the actual data for Finnish league and get to the “real” economic theory and analysis in later posts.

The basic idea in fan demand is simple. If we note ticket demand for a single game with D, we can assume the demand follows

D(ij) = H(i) + V(j) + M(ij).

, where D(ij) is the demand for tickets (i.e. the attendance) for a game between home team i and visiting team j. H(i) is the interest in home team i, defined by several variables such as market size, brand, fan base, local competition in terms of other sports and teams, arena capacity and so on. V(j) is the interest for visiting team j, again a combination of several variables, for example distance from j’s home area, brand, superstar players and so on. Lastly M(ij) is the match-specific interest, such as whether it’s a local rivalry, two teams competing for a playoff place, last season’s finalists, big promotional activities, TV visibility, day of week the match takes place… any and all such variables specific for a particular match.

Because of the different variables relating to home and away teams, it is important to notice that a game between two teams would draw a different attendance depending on which one is the home team. To consider that, I took the attendance in the Finnish league and broke it down by home team and by visiting team. Because the arenas differ considerably when it comes to size, simply comparing attendance figures would be deceptive. 4000 people would be practically full house to JYP (lowest audience capacity at 4365), yet it’s barely one third of seats for TPS (biggest arena with maximum attendance at 11 820). So instead I used relative attendance, or the fulfillment rate of the arena, that is, the attendance as a percentage of capacity.

Attendance during 2014-15 Fall season

During fall 2014 all but 3 match-ups took place, for a total of 228 games. 45 match-ups were placed twice, and 2 three times. For these a simple average was used. Because the data is mainly of single games for majority of home/away team combinations, far reaching conclusions are not advisable. The random match-specific variables, such as season opening, special promotions or simply the day of the week the game was played have too much effect on the attendance. However, certain trends do appear.

It is possible, for example, to identify teams with strong home-team demand. HIFK and Kärpät, for example, draw in good crowds regardless of who they’re playing against on their home ice. Since it could be argued that these two teams also have the strongest hockey brands in Finnish hockey, that comes as little surprise. It also follows that these two teams are interesting as visiting teams as well, an intuitive assumption supported by the attendance figures. For Kärpät, for example, the average attendance rate for home games is 83%, and not one game was played in front of a crowd less than 75% of capacity. As an away team, they attracted an average attendance rate of 73%. The lowest, and only rates below 60%, were against Blues and HPK (55 and 52 respectively), teams with overall very low home game attendance rates.

A similar story can be told about HIFK. With a home game attendance rate average of 79, even their lowest rate is still above 70%. Both teams have 7 match-ups above 80% (HIFK missing a home game against SaiPa). As a visiting team HIFK is also a clear favorite regardless where they go, with attendance rates staying below 60% only against TPS (49) and Ässät (59), and a visit to play against Pelicans still to take place. Four match-ups with HIFK as the away team rate above 90%.

On the other end of the spectrum, there are teams that cannot draw in the fans home or away. Blues is averaging at 56%, with 9 different match-ups below 60%. As an away team, they only break 80% against HIFK (85, a team with very strong home team demand and a local rival), JYP (84, another team with strong home demand) and SaiPa (86, solid demand at home with 6 match-ups above 80%). Another weak performer is KalPa, although the other way round. Where Blues couldn’t get the demand up at home, KalPa only dropped below 60% in 6 match-ups out of all 13, and even broke 80% in one. But that was against Kärpät. The average attendance rate for KalPa at home was 65%. As an away team, they managed to keep the average practically the same, at 64%, but that was helped by the strong home crowds when visiting HIFK (83), JYP (84) and Kärpät (89). In 7 match-ups the attendance rate remained below 60%.

I do want to bring up TPS, although it seems the club has taken enough of a beating both on and off the ice this season. They do start at a disadvantage when talking simply in terms of attendance rate, by playing in the biggest arena this season. The abysmal performance on the ice isn’t exactly helping. The fall season average attendance rate for TPS at home is 50%, and even that is helped by the sole out-of-pattern attendance for the season opener against Kärpät. That game was attended by 10 362 people. To put it in perspective, the average attendance without that game against Kärpät is 5570 people. In 11 out of the 13 possible match-ups TPS has remained under 60%, with the lowest being 34% against KalPa (disclaimer: only one game).

But here’s the truly interesting thing about TPS: they attract people when playing outside of their home town. Having visited all the other teams in the league during the fall, not one of those match-ups drop under the 60% attendance rate. In fact, they have an average of 73%, which is second highest in the league, tied with Kärpät and Sport, and only behind HIFK. Out of these three teams, HIFK and Kärpät have strong pull both home and away as discussed above, and Sport is the new team added to the league for this season and thus expected to stir up interest.

What about last year then: was it so much better?

As mentioned above, many of these figures are from single games, so too far-reaching analysis is strongly discouraged. However, if compared to similarly calculated attendance rates from last season, something interesting again occurs. HIFK and Kärpät displayed similar figures in 2013, no doubt boosted by their strong brands. Another solid performer was Jokerit, attracting an average of 80% attendance rate as a visiting team and 65% at home (notably their home arena capacity was 13 349).

As for aforementioned TPS, already in 2013 they drew in the crowd as a visiting team. But they performed poorly in terms of home game attendance with an average of 44%, with 61% the highest. It is intuitively pleasing to claim this is due to their large home arena, as that is bound to bring down the relative attendance. And there is no doubt some truth to that, as their average attendance is 5150. That’s more than full capacity for 4 teams in the league at the moment, three last season. So maybe TPS is simply playing in an arena far too big for them?

Both last season and this, the average attendance rates varied more when considering home team averages than with visiting team averages. This would suggest that home team demand variables have larger impact on the attendance than visiting team, which is not surprising. How much that is the case will be returned to later.

Overall it would seem the media outcry has been correct: the attendance has fallen in terms of attendance rate. Fall 2013 saw a league average attendance of 72% whereas this season the fall attendance stayed at 68%. This despite the fact that the team with the largest home arena, Jokerit, left to play in the KHL, and was replaced by Sport, a team with a capacity one third of that. But on the other hand, a team with an average home attendance of 9252 was replaced by a team with home attendance average of 3370. League-wide, the attendance average dropped from 4974 to 4295. Which leads to only one more conclusion: someone is picking up the slack.

Feb. 10: Edited to clear up some bad wording.

Shooting down the Shootout

The NHL is considering getting rid of the shootout. They’re currently testing the effects of playing overtime as 3 vs 3 (as opposed to the 4 vs 4 currently in use), hoping it’ll lead to more games getting solved in the overtime instead of the shootout. The Swedish league is moving to that format over the Christmas break, or so I heard.

Now, I get the desire to get rid of the shootout. I’ve never been a fan of the format. It seems incongruous to find a solution to a team sport in singularly individual contest. And that’s why I’m not particularly fond of the 3 vs 3 format, either. It’s not really that much of a step away from individualism. I’m not saying individual skill cannot solve the game, or that there is something wrong if such a thing happens. As long as it happens in the game. We don’t have to change the game into a measure of individual performance and luck.

Besides, it’s boring. The time it takes to prep the ice, and the teams and referees to get everything ready, the flow of the game is gone. The audience is already pulling on their coats, thinking of the fastest route home. I saw that first hand in the last game I went to, Espoo Blues hosting SaiPa: the overtime was fun and thrilling, but the shootout just killed the buzz.

The simple solution would be to double the overtime. Play 10 minutes as opposed to 5. And if played with second period ends (that is, with the longer distance to the bench), I’m guessing we’d have more games ending in overtime. But it would be a played solution, unlike in the shootout.

But here’s the thing: why do we need to find out the winner? I looked at the regular season standings in the NHL, and there’s teams with equal winning percentages. If we take winning percentage as the measure of team quality (ignoring the unbalanced schedule here for convenience), wouldn’t it be that two teams with equal winning percentage should result in a draw? Because they’re of equal quality. Why do we need to find out a winner?

This has been bugging me for quite some time. So I decided to have some fun with the regular season standings in the NHL for the last 9 seasons, that is, from 2005-06 to 2013-14.

The Era of the Shootoutgames OT SO

In the 9 seasons a total of 10560 games were played. (The 2012-13 season was of course shorter due to the lockout.) The chart on the left shows the shares of different solutions over the total games of the 9 season period. 60 meaning regular game time, OT for overtime and SO for shootout. Out of the total games played 23.51% (2483 games) went on overtime.

As can be seen, however, the overtime isn’t very effective. On average, only 43% of games that went on overtime were actually solved on overtime. (The seasonal figures range from 38.9% to 49.9%.)

It would seem, then, that the NHL is on the right track. The overtime as it is, is a rather inefficient way to find out which team is better. But I must ask again, if the two teams can’t find out who’s better in 65 minutes of active game time, is there a significant enough difference? Or could we just agree that they’re of equal strengths?

Three alternatives

I decided to compare three alternative policies, and see how the competitive balance in the league and the teams making the playoffs would differ.

Alternative 1: the status quo. That is, all games are played till we have a winner. The regular game time is followed by a 5 minute overtime, played 4 vs 4, with sudden death. If there’s no solution on overtime, a shootout is played. The winner gets 2 points, the losing team none, unless there’s overtime/shootout, in which case he losing team gets 1 point.

Alternative 2: the no-overtime policy. All games are 60 minutes, and it the score is tied, the game is a draw. Winner gets 2 points, losing team none, and in the case of a draw, both teams get 1 point each.

Alternative 3: the overtime policy. If the game is tied at the end of third period, an overtime is played. If the game is tied at the end of the overtime, the game is a draw. Points as above.

I didn’t control for the strength of schedule when calculating the winning percentage, for the sake of simplicity in calculations (which, of course, is the academic speak for “couldn’t be bothered”). And of course there is the possible moral hazard bias in assuming the games that went on overtime would have ended as a draw under alternatives 2 and 3, as some teams in some games might have less desire to fight for the second point  at the risk of losing the game, preferring to secure the point from making it to the overtime, or playing it safe on overtime thinking they are going to be stronger in the shootout. Again, simplicity of calculations ruled that out. And this time I actually mean it, it would had been rather cumbersome to approximate for that.

The measure of competitive balance I used is the simplest version, that is, the basic standard deviation of the winning percentages. I did considered using the ordered probit model of Ruud H. Koning (Balance in competition in Dutch soccer, The Statistician, 2000, 49, Part 3, pp. 419-431) to estimate the competitive balance measures in a league that allows for draws, but decided to save that for another day, another blog post. If nothing else, it’ll give us something to look forward to. (No? Just me then.)

The Noll-Scully approach

The argument presented by Roger Noll (Professional Basketball, Stanford University Studies in Industrial Economics Paper no. 144, 1988) and Gerald Scully (The Business of Major League Baseball. Chicago: University of Chicago Press, 1989) was that “a natural way to measure the degree of competitive balance in a league is to compare the actual performance of a league to the performance that would have occurred if the league had the maximum degree of competitive balance in the sense that all teams were equal in playing strengths” (James Quirk and Rodney D. Fort, Pay Dirt. Princeton University Press, 1992, p.244). The following definitions and explanations for the actual and ideal competitive balance are also from Quick and Fort.

The actual standard deviation (ASD) is calculated as follows: The difference between actual winning percentage and the league average (=0.500) is calculated for each team within season. The difference is squared. The squared differences are then summed over all teams, and divided by the total number of teams in the league. The square root is taken to get the standard deviation of the league winning percentages for the season.

For alternatives 2 and 3 the winning percentage considers a draw as “half a win”, so it’s (wins + 0.5 x draws) / games played. While this is a crude simplification, it has been used in sports economics literature. As mentioned above, a more sophisticated method of measuring competitive balance in a league with draws will be returned upon in a later post. For the time being, draws as a half a win shall suffice.

The idealized standard deviation (ISD) is simply the standard deviation of a league where all teams have the winning percentage of 0.5. The value of ISD depends on the number of games in the league, and can be defined as 0.5 divided by the square of games per team. For the seasons under study here, that’s 82 games, except for the 2012-13 season when each team played only 48 games.

Using then the Noll-Scully approach, the degree of competitive balance in a league for each season can be evaluated by comparing the actual and ideal standard deviations. This gives us the ratio of standard deviation (RSD): the actual divided by the ideal. The closer the ratio is to 1, the more competitively balanced the league.

The ASD and RSD for the NHL in the nine season under study are as below, calculated for all three alternatives.

competitive balance wins

Unsurprisingly, alternative 2 (without overtime) has the lowest standard deviations (that is, RSD’s closest  to one) in majority of cases. This follows from the largest number of draws. Notably there is not much difference between the RSD’s for alternatives 1 and 3, that is, the status quo and the plan without the shootout. Eliminating the shootout would, it seems, level the competition, but only slightly. It would not hide the differences in strength between the teams.

.. and the points don’t matter?

Because the ranking of the teams is ultimately not done by the winning percentages but by points, I also calculated the actual standard deviations of points.

competitive balance points

The problem here is that the total number of points in a season varies under the current system. In any game, either two or three points are rewarded to the teams, depending on the game outcome. Thus the total points in a league can be anywhere between 2460 (all games 2-point games, that is, ending on regular time) to 3690 (all games 3-point games by going on overtime) points. Across the 8 full seasons the average number of total points was 2750.

In terms of points, the alternative 3 provides less competitive balanced league than the current system of alternative 1. However, the differences in RDS’s are small. It could therefore be argued, that even with games resulting in draws, we can rank the teams by competitive strength.

Do we need to win every game?

It would seem, given the above, that there really is no reason for the shootout. The league would not suffer in terms of competitive balance if we allow for games to end in draws. In fact, the season would be more balanced, and thus probably more exciting to watch. The ease of ranking the teams would not be affected, as the differences in points still occurred, and to a very similar degree. But we wouldn’t have to sit through lukewarm endings of watching the zamboni make its rounds and the referees having a chat, all for a blink-and-you-miss-it stroke of individual luck.

Sports and women, do they mix after all?

A quick reply to a tweet yesterday led to a lively discussion and got me thinking about women and sports and the relevant stereotypes such as:

  • Women aren’t interested in sports.
  • Women don’t understand sports.
  • Women aren’t welcome in sports audiences, at least to “real” sports like football and ice hockey.

Just as I was calling people out on one stereotype, I was called out on another. And it got me thinking, are these true? Any of them? And if so, which ones?

I know plenty of women who are interested in and have extensive knowledge of sports, even the traditionally “guy” sports. I even shamelessly use the division between “girl” and “guy” sports, both by the gender of those doing them and those watching them, to my own advantage should the occasion arise. But I’ve always considered us a bit of an anomaly. And I’ve always viewed us, egotistically perhaps, as fighting the establishment, going against the general prejudice. Braking the stereotype and pointing out the narrow-mindedness of people.

Have I been wrong?

Fight! Fight! Fight!

Last weekend I finally got around to watching The Last Gladiators, a documentary about the enforcers, “goons”, in ice hockey. The story follows that of Chris Nilan, and showcases the sometimes devastating price of being a “tough guy”. If you’re interested, and I really think you should be, the documentary is available on Netflix.

I’m not going to analyze the content, partly because it’s already been done so well: Jouni Nieminen wrote about the documentary for Helsingin Sanomat (unfortunately in Finnish, but scroll down for links for English coverage). But the documentary got me thinking. Fighting is one of those topics that pop up every season, at least once a season. And it’s one of those things that almost everyone who has an opinion feels strongly about, one way or the other. There’s sites and blogs promoting fighting, such as hockeyfights.com where you even get to vote on the winner of the fight. And there’s sites and blogs against fights, such as It’s Not Part Of The Game which tries to rid the game of fighting, arguing that, well, it’s not part of the game.

I have to insert a disclaimer here: While I’m the last person to be called “a flower-hat lady” (from the Finnish word “kukkahattutäti”, meaning a schoolmarmish Miss Judy goody two shoes) I am against fighting when it’s just for the sake of fighting. Because why would you fight? There’s no point!

And I can just hear the uproar… The arguments for fighting are seeded deep in hockey tradition. “Fighting helps the team win more; it motivates the team.” “Fighting cleans the game by policing out the dirty play.” The two most common arguments heard in favor of the fights. Too bad they’re not true.

How much are we fighting, then?

The lovely people at hockeyfight.com keep good statistics on fights in the National Hockey League. So let’s see how much fighting happens in the NHL. The following figures are based on the data from the 2000-2001 up to and including the current season, unless otherwise stated.

  • Were you to watch every game in a single season, you’d see, on average, 640 fights. (This average excludes the shortened 2012-13 and current season.)
  • On average, 39% of games in a season have at least one fight.
  • 132 games, on average, in a season, have more than one fight. That’s approximately 10% of the games. (Excluding both the 12-13 and current season.)
  • The average number of fights per game range from 0.35 (current season) to 0.65 (2001-2002). There seems to be a declining trend:

Fights in the NHL graph

* The current season, 2014-15, statistics are recorded at 231 games played.

Do fights win games?

In their study The effect of Home Advantage, Momentum, and Fighting on Winning in the National Hockey League (Journal of Sports Economics, 12, 5, 2011) Benjamin Leard and Joanne M. Doyle used data for fights in the 2007-2008 season. (Leard and Doyle used dropyourgloves.com for their data, another fan-based site like hockeyfights.com. The numbers are slightly different between the sites. Hockeyfights.com counts fights where at least one player involved receives a fighting major. I couldn’t find a definition for a fight at dropyourgloves.com.) During that season 41% of games had at least one fight taking place. Out of the total of 722 fights, almost half took place in the first period.

fights per period

This means, should this distribution between periods hold for other seasons as well and there’s really no reason to assume otherwise, that approximately 44% of fights happen in the first period. And around 70% of fights take place in the first two periods combined.

Leard and Doyle studied the effect of a won fight on the outcome of the game using game-level data. They acknowledged the possible endogeneity bias between fighting an game success as doing poorly in the game could trigger a fight. Of course, given the fact that only 25% of the fights took place after the second period, that doesn’t seem a very prominent reason for fighting.

To minimize the possible bias Leard and Doyle used only the games where there had been fights only in the first period. Turns out, there is “no evidence of the motivational effect of winning fights”. They also experimented with different slices of the data; using both first and second period fights made very little difference. Overall, they conclude, there is “no significant evidence, positive or negative, of winning fights on the likelihood of winning the game”. (Emphasis mine.)

So, fighting makes no difference to the outcome of the game. Why do it then? As The Last Gladiators made so plain, it’s hardly a healthy way to play hockey.

Does fighting clean up the game?

If fighting doesn’t help us win, then it must at the very least help us protect our players, right? If we put a known enforcer, a bad-ass fighter on the ice, the other team will think twice before landing a dirty hit on our superstar. Right?

Well, it doesn’t look like it. Adam Gretz at Regressing wrote about this a year ago. Going over two seasons worth of games he looked at hits that “resulted in a suspension, fine, or match penalty” and compared that with whether or not the team taking the hit had an enforcer in the lineup that night. Out of the 106 incidents, Gretz found that 52 of the teams did not have a fighter in the lineup. That means 54 teams did, and the hit still took place.

SkinnyFish (really? Okay.) over at Pension Plan Puppets studied the number of “non-obstruction penalties”, or “naughty behavior” as he calls it, drawn by a team with respect to fighting majors taken. His argument was, that a team that fights a lot would draw less penalties, that is, other teams would play cleaner hockey against them than against teams that don’t fight. He found out there’s no correlation between fights and the level of “naughtiness” that goes on on the ice. (Nice jab at Toronto in the graph, though.) Having a fighter present doesn’t influence the level of dirty play you get from the other team.

So we’re not winning more games with fights, nor can we use them as a deterrent to foul play. And I ask again: why bother?

Are fights untouchable?

I’m beginning to wonder, are fights an isolated aspect of hockey, something that isn’t affecting much anything, but also something that isn’t affected by much anything. Jac C. Heckelman and Andrew J. Yates, in their ingeniously titled study And a Hockey Game Broke Out: Crime and Punishment in the NHL (Economic Inquiry, Oct 2003, 41, 4), used the natural experiment of NHL exploring the possibilities of using two referees in 1999-2000 seasons to study how the number of referees effects both the number of penalties called and the number of rules infractions committed by players.

Borrowing from the economic theory of crime, they isolate two different mechanisms: the monitoring effect and the deterrent effect. Monitoring effect would simply mean that two referees catch more infractions than one, while the actual number of infractions is the same. Deterrent effect on the other hand suggests that the increased risk of getting caught keeps players from committing the infraction in the first place.

The theory suggests, that “when the number of referees is increased, there are differential effects on major and minor infractions. … For major infractions, there is only a reaction effect to the other teams committing fewer minor infractions (due to the other team’s own deterrent effect).”

85% of the total number of penalties were minor. And as was to be expected, a significant monitoring effect was found. Adding a second referee means more infractions are caught. However, no deterrent effect was found for minor, nor major, infractions. Fights aren’t the type of infractions one usually tries to hide, quite contrary, so the monitoring effect doesn’t apply to them. But there was no deterrent effect found either. What does affect them?

Heckelman and Yates argue that infractions are more “crimes of passion” than conscious decisions, and as such are born out of the heat of the game, which would account for the lack of deterrent effect. Either way, it doesn’t seem like fights are motivated by many the variables they studied: offensive and defensive prowess, relative physical size of the teams, power play track records of the teams to account for the costs of getting a penalty..? Only opponent shooting percentage was significant (positive effect), own team power play defense had a significant and negative effect, presence of goons in teams was significant and positive, as was the age difference (teams with relatively older players fought more), number of times the own team had been shorthanded in the past 15 games had a positive and significant effect (implies a track record of rough game). Looking at the results, and besides that fact that if you put fighters on the ice, they’re going to fight, none of the above really explains fighting.

It won’t clean up the game. It won’t help you win more games.

So why fight?

Play off or play on?

Playoffs. Love them or hate them, they sure are entertaining. Which makes you think, the more the better, right?

Talking about playoffs when the regular season is barely underway would seem ridiculous, if it wasn’t for a piece of news that surfaced few weeks back here in Finland: the Finnish league is looking into expanding the playoffs in hockey. After all, the league itself is expanding next year. So it only makes sense.

More teams making playoffs, or at least staying in the run for longer, can only be a good thing, right? It’s more exciting so people tune in more and the game gets a boost in fan demand. That is the argument presented by the league, as expressed by the Finnish league’s board chairman Vesa Puttonen. Everybody wins, right?

Right?

Major League Baseball and the -69 and -95 playoff expansions

In his 2009 paper The impact of post-season restructuring on the competitive balance and fan demand in Major League Baseball (Journal of Sports Economics, 11, 136-156) Young Hoon Lee studied the playoff uncertainty and its link to attendance and found empirical evidence that the post-season restructurings of -69 and -95 improved the playoff uncertainty and had positive effects on fan demand. This seems to confirm the expectations of the Finnish hockey league. However…

What happened in MLB in the 1969 and 1995 was, that due to league expansions the old playoff system was no longer sufficient. In -69 both leagues (NL and AL) had 12 teams each. Before -69 the playoffs were basically just the championship series, only the winners of each league had a post-season. After -69, a second round was added to the playoffs, resulting in 2 teams our of 12 making the playoffs in each league, 4 out of 24 in total.

A similar expansion took place in 1995. Due to larger number of teams, another round of playoffs was added. Now 4 teams out of 14 in each league made the playoffs, a total of 8 out of 28 teams.

There’s expansion and there’s “expansion”

The key thing is to look at the number of teams making the post-season out of all possible. After the first structural expansion, 4 out of 24 teams had a post-season in baseball. That’s 17%. After the third round was added, the percentage goes up, to 29%.

Right now, before the proposed expansion, the Finnish hockey league has 71% of its teams making the playoffs. Even with the added team next season, we’d still have 67% of the teams playing for the championship after the regular season.

I highly doubt the fan demand is linear in this regard. Going from 17% to 29% making the playoffs may have had significant impact on fan demand. Going up from 71%? I’m doubtful.

The Swedish study in equal opportunity

Has anyone looked at the Swedish hockey league? They introduced the “pity playoffs”, the “pre-round” for last season*. What happened there? How did the demand react? ‘Cause they’re really getting all in with the playoffs, almost literally: 83% of the teams made playoffs last season. The league expansion to 14 teams isn’t going to bring the percentage down much, only to par with Finland: 71%.

The North American leagues are much more ruthless. Both NHL and NBA qualify slightly over half of their teams to post-season, with 53% both. NFL has probably the most confusing season schedule I’ve ever seen, but they mean serious business with the post-season: 38% of teams get a chance to go all the way to championship.

And what about baseball? It’s grown since we last spoke of it, the league now consists of 30 teams. Still only 10 make the post-season. That’s 33%.

Oh, and in case you were wondering about the KHL? 16 out of 28 teams. That’s 57%.

The percentages of teams making the playoffs in different leagues:

Playoff teams

Pointless games, at the beginning and the end

What would it mean, in reality, if we let more teams into the playoffs? It would mean weaker, lower quality teams getting a change at upsetting the, at least according to a lengthy regular season, stronger teams. I borrowed from a study The “Second” Season: The Effects of Playoff Tournaments on Competitive Balance Outcomes in the NHL and NBA by Neil Longley and Nelson J. Lacey (Journal of Sports Economics, 13, 5, 2012) and calculated the probabilities of each seed winning three rounds of playoffs. Like them, I used the average winning percentages for each seed over several seasons. Unlike them, I didn’t take into consideration the home advantage. I also assumed the “pity playoffs” are played as best-out-of-7, to simplify calculations.

Using the average winning percentage of each seed over 11 seasons (2003-04 to 2013-14) in the Finnish hockey league, I calculated the probability of each seed winning the championship, when weighted by the probability of each possible match-up.

The first seed, the team winning the regular season, wins the championship with 38,6% probability. The 10th placed team has a probability of 1,2%. Here’s the whole list:

Seed Prob.
1 38.6
2 25.4
3 23.0
4 22.0
5 17.7
6 14.2
7 5.3
8 2.8
9 2.1
10 1.2

Why include teams with very small probabilities of actually winning the championship? Besides, the extra round for seed 7 through 10 is what really diminishes their chances. So why increase their number? Are match-ups between the first and 10th placed (40% probability of that happening) really interesting to anyone, when the probability of the regular season winner winning is 72,1%? Against the 8th placed team seed 1 would have a winning probability of 67,2%. I’d prefer to go to the second game, if you ask me.

But because it’s not all math and probabilities, things happen. Weaker teams win. That’s why playoffs are so exciting. Longley and Lacey found, in their study, that the playoffs in the NHL had “considerable reranking effects” when compared to the regular season standings. Which begs to question: isn’t the whole point finding out who’s the best?

While increased playoff uncertainty may increase fan demand, it’s not always so straightforward. In their study “Playoff Uncertainty and Pennant Races” (Journal of Sports Economics, 12, 5, 2011) Anthony C. Krautmann et al. used monthly attendance data from MLB for the 1957-2006 period to better capture the effect increased playoff uncertainty would have on fan demand. They found that “the only month in which attendance is affected by [playoff uncertainty] is the month of September”, that is, right at the end of the regular season.

If it takes, on average, 1,3 points per game to make the playoffs in the Finnish hockey league (using the same data as before), can we really afford to bring that any lower? To make more early-season games relatively insignificant and thus more uninteresting to fans?

Can we really?

 

* The seeds through 7 to 10 play a round, usually best-out-of-3 or 5, to determine which two teams play against seeds 1 and 2.

Edit: Edited to add graphics on the number of teams making the post-season in each league at the reguest of my good friend and self-appointed social media consultant H, who doesn’t like to read too many numbers in a row. -Nov 10, 2014

I get the economics, but why sports?

I don’t look like I like sports.

I most certainly don’t look like I know about sports.

And I definitely don’t look like an expert on theories of sports economics.

Here’s the deal: I’m a woman. There, I said it. I’m also about 5’4 (and I think at least an inch of that is just hair), I like dresses and lipstick and ballet flats. I love to bake. And I read Jane Austen for comfort.

That’s all true.

None of that, however, prevents me from being a good economist or loving and knowing about sports. From running statistics for fun, from reading econometrics for entertainment, or from researching the latest developments in sports economics theory. Getting a Master’s Degree in economics. It’s most certainly not preventing me from enjoying a good game of tennis or football, from getting excited when I get my hands on a new set of baseball stats, appreciating an effective Formula 1 team strategy, or loving ice hockey. If anything, it’s giving me a new angle on these things.

I’ve done sports in my life, all of which required wearing a skirt and most involved sequins. Ballet, figure skating, cheerleading… And no, they don’t boost my credibility in analyzing soccer team building strategies. But they did give me an undying love for playing, the experience of dedication and team loyalty. And they gave me The Moment.

Sometimes, if you’re lucky, you get a moment of clarity, a moment that just makes the world around you make sense. You may not know it at the time, but looking back to it, you recognize it as the one defining moment in your life that ended up setting the course for you. For me that was a moment that repeated itself over and over again (ironic, really, given that I’m usually a pretty fast learner).

When I was cheerleading for HIFK during high school, before the game started we’d make this alley for the players to skate through. And since we were lined up by height and I was the shortest girl in the team, I’d be right by the rink waiting to go on ice. The arena was dim, the lights out in the stands. It only served to enhance your other senses. You heard people shuffling to their seats, greeting each other, and the occasional cry of support for the home team. You smelled the ice, that particular scent of the chemicals they use that seeps into your gear and hair and makes you think of the game when you’re back home taking a shower. You felt the energy and anticipation, the excitement and fear. Maybe tonight is going to be spectacular. Maybe it’ll be just another run-off-the-mill game. Maybe we’ll win big. Maybe we’ll crash and burn. Maybe…

It was only a short moment. We waited for the referees to step on the ice and we’d follow. The team would skate out, the puck would drop and the game would be on its way. Going the way it was going to go, and over far too quickly. Then we’d know. We’d know if we won or lost, if it was a tired mid-season game of two teams desperately waiting for the Christmas break, or if it was something we’d speak of for days and weeks to come. We’d know.

But in that short moment, before it was all set in motion, everything was still possible. In that short moment time stood still, and all you could do was feel.

Looking back at those days and years I spent with the HIFK, those were the moments when I knew I wanted to work in sports. I wanted to be part of that, to give people those seconds frozen in time at the top of the two-and-a-half-hour emotional roller coaster we call a game of ice hockey.

And for a statistically minded fixer-upper like myself, in my pretty heels and polka-dot dresses, learning about sports economics was like coming home. I finally found my place in the world.