Every prominent league in the world has its bevy of big name goal-scorers. La Liga boasts Ronaldo and Lionel Messi. Gonzalo Higuain, Edin Dzeko and Dries Mertens tear up the Serie A. In the Bundesliga, Robert Lewandowski and Pierre-Emerick Aubameyang find the net with regularity. Fans of Ligue 1 saw the emergence of a teenage sensation in Kylian Mbappe along with scoring stalwarts such as Edinson Cavani and Falcao. Harry Kane, Romelu Lukaku, Alexis Sanchez and Diego Costa among others are household names in the Premier League with their ability to find the net.
Likewise, Major League Soccer is awash with dynamic attacking talent. That notion is on full display with the 2017 season nearly halfway complete. Whether it’s players expected to do so or those who’ve suddenly emerged, the goal-scoring acumen in this league is as good as it’s ever been. The combination of established player acquisition mechanisms such as the designated player rule and the onset of targeted allocation money have partly played a role.
Having said all this, is there a way to measure MLS attacking efficiency relative to other leagues? And within the league itself, which players find net or help their teammates do so in the most efficacious manner? Furthermore, is there a correlation between how much a player accounts for a team’s total scoring output while on the field and frequency of appearing on the score sheet?
We will explore all these topics below.
A Statistical Breakdown of MLS Attacking Efficiency in 2017
Evaluating Goal Frequency and Team Balance of Scoring in Major League Soccer
There’s no doubting that the talent level in Major League Soccer is at an all-time high in league history. That said, it still has a ways to go before fans can mention it in the same breath as the big five European leagues. But that’s not to say that MLS is lacking goal-scoring excitement. And there are qualities from an attacking standpoint which set it apart in a positive light from those star-studded competitions across the pond.
A comparison between MLS and a variety of leagues around the world indicates that it’s relatively high scoring. Not only that, but the scoring is fairly evenly distributed among participating teams. Two metrics help determine this: the league average in terms of goals per game and the median number for the league. Both are fairly simple to calculate. For average, take total goals scored and divide by games played for each team and average those numbers out. The median in this case includes two numbers in the middle of each data set since every league includes an even number of teams.
The more leagues we can use to paint a broader picture, the better. For that reason, 20 leagues are a part of this evaluation, including MLS. 18 comprise that particular nation’s top tier, with England and Germany’s second division also a part of this study. Those two, the English Championship and Bündesliga II, generally receive recognition as the top non-first division leagues in the world. With the exception of the current MLS season, this analysis will use the most recent fully completed campaign for each league.
A Look at the Numbers and What They All Mean
After crunching the numbers for 358 teams across these leagues, the following two charts sorted by average goals per game and median-average difference emerge.
(Note: Those interested in team-by-team data for each league can scroll to the bottom of this article. There, you’ll find the original spreadsheet embedded for your perusal.)
As is evident, MLS rates fairly highly in both categories. The former is pretty self-explanatory. MLS ranks seventh in the average number of team goals per game. But what’s so important about the latter metric? What can observers infer from the fact that MLS boasts the most positive difference between the median and average along with Sweden’s Allsvenskan?
Leagues with a high median-average difference appear to exhibit more balance in terms of overall scoring distribution. Take France’s Ligue 1 for example. The highest scoring team, AS Monaco, scored 2.82 goals per game in 2016/17. The ten teams below the median in France averaged 34.4 percent of that total. Contrast that with MLS where teams below the median average 52.2 percent of Atlanta United’s league high of 2.0 goals per contest.
From a talent standpoint, MLS remains behind the Ligue 1s, La Ligas, Serie As and Premier Leagues of the sport. There’s no doubting that. But it’s among the most egalitarian in world soccer in terms of raw scoring. So when it comes to that intensely emotive joy which cascades after the buildup and crescendo of a goal, MLS has it and then some.
Breaking Down Major League Soccer’s Most Efficient Attacking Players of 2017
The next step in this analysis of MLS attacking efficiency is evaluating the players themselves. It’s their finishing and overall playmaking quality which enthralls fans and puts their teams in position to win. Whether it’s established stars like NYCFC’s David Villa or newcomers like Chicago’s Nemanja Nikolic, MLS boasts players who can find the net in a variety of ways.
How to Quantify Goal/Assist Frequency
Goals and assists are obviously the easiest way to track the most dynamic attacking players in any league. But that doesn’t mean there aren’t more statistically robust means of analyzing goal-scoring/providing frequency. Two metrics take on particular importance for this discussion. And as shall become evident, there’s a fairly distinct correlation between the pair.
The first of these is minutes per goal or assist (Mins/G+A). If ever there was a stat that linked soccer and golf together, this is it. A lower number from a given player means that they contribute to the score sheet more frequently. And that, in and of itself, is a telling mark of efficiency in the final third.
The following chart lists all MLS players who’ve appeared in at least 750 minutes to this point and are averaging a goal or assist in under two hours of game play.
The usual suspects clearly stand out. David Villa remains a talismanic presence in NYCFC’s attack during his third season with the club. Diego Valeri and Fanendo Adi continue to be indispensable cogs in the Portland Timbers attack. Sebastian Giovinco has seen limited minutes for TFC due to injury but, when on the field, he’s clearly effective. And though Columbus Crew SC’s defensive issues are well-documented, Justin Meram and Federico Higuain are both enjoying standout campaigns in 2017, contributing a combined 14 goals and 11 assists in 16 games.
But what’s also clearly evident from the above graphic is the importance of a number of newcomers. Victor Vazquez’s ability to provide for his teammates is a major reason Toronto’s on top of the Supporters’ Shield standings. Nemanja Nikolic’s transition to MLS has been as seamless as it gets considering he’s leading the Golden Boot race. Him and a resurgent David Accam are major factors in Chicago’s return to relevance.
Miguel Almirón came into this league with a bunch of hype and he’s clearly delivering. Yamil Asad is providing a dangerous presence in the final third as well. And Josef Martinez would likely make this list if not for missing so much time due to injury. When not taking into account minutes played, his 57.6 minutes per goal/assist leads the league. Other players with impressive numbers despite limited minutes are Montreal’s Anthony Jackson Hamel (59 minutes/goal+assist) and Orlando City SC’s Kaka (86.5 mins/G+A).
Adding Percentage of Team Total Goals/Assists While on the Pitch to the Equation
The final piece to this puzzle related to measuring MLS attacking efficiency concerns effectiveness at registering a goal/assist while on the pitch relative to the team’s total as a whole. In order to come up with this number, we take the player’s goal/assist total and divide it by the team’s, with one caveat. Any goal or assist tallied while said player sits on the bench or doesn’t make the squad altogether doesn’t factor into his percentage.
The above graphic with the names of all players averaging a score or helper in under 120 minutes (minimum 750 minutes played) looks a little different when sorted by this percentage.
A few names pop out when adding percentage of team total goals/assists while on the field to this analysis. Romain Alessandrini has been as good as advertised for the LA Galaxy. And C.J. Sapong’s play for Philadelphia is a huge factor in him making the USMNT’s 40-man preliminary roster for the Gold Cup. The one drawback to their percentage skewing so high, though, is that it indicates that their teammates who are tasked with contributing to the attack need to step up more.
That’s certainly the case in Philly. Sapong’s haul of eight goals is certainly impressive. But only one other player, Fafa Picault, has more than two goals at this point. In LA, the problem is less pronounced now than it was earlier in the year. That’s because Giovani Dos Santos is finally finding the net with regularity, tallying five goals in the last five games.
One player in particular features more prominently from a percentage standpoint than by singling out how often he appears on the scoresheet. And that’s Sebastian Giovinco. The 2015 league MVP leads TFC with his goals and assists while on the field accounting for over 30 percent the current MLS leaders’ total. Injuries have limited his minutes, but when playing he remains among the most efficient attack-oriented players in the league.
Correlation Between the Two?
Both of the above metrics are solid indicators of attacking efficiency. The fact that the league’s top goal-scorers and assist providers are front and center when discussing them attests to that. But are the two directly related? Is there a correlation between goal/assist frequency and how often players register either as a percentage of the team total?
Finding out requires a little two-dimensional graph with minutes per goal/assist on the x-axis and percentage of team total while on the pitch on the y-axis. Plotting each data point on the graph results in the following scatter chart. It includes an expanded group of players (60 to be exact) beyond those averaging below 120 minutes per goal/assist. And keep in mind that the x-axis is inverted, so the closer to the upper left hand corner, the better.
As the old cliché goes, correlation doesn’t necessarily imply causality. But that trendline is fairly telling. It shows that attacking players who regularly find the net, help their teammates find the net, or do a little of both, are also expected to take on the lion’s share of their respective team’s offensive burden.
And that, my friends, is a major part of what this beautiful game of ours is all about. The personalities who live for the spotlight, make the headlines, and get the supporters excited are those whose scoring exploits help lead their team to glory. Every league has them. And as one of the highest scoring leagues in the world, MLS is no different.
As promised, my spreadsheet with team-by-team goals per game data for all the 20 leagues I analyzed for this article.