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Beyond the Numbers: Goals and Success

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Teams need to score to win. But does the type of goal matter? We continue our series looking beyond the numbers to see whether the Vancouver Whitecaps reliance on set-piece goals is a good or bad thing.

MLS: Seattle Sounders FC at Vancouver Whitecaps FC Anne-Marie Sorvin-USA TODAY Sports

To win a game, a team needs to score goals. However, does the type of goal matter? That is, do teams that rely more heavily on certain types of goals (e.g., run-of-play, set pieces, counter-attack, etc.) have greater or less success in Major League Soccer? Today we continue our series on Beyond the Numbers by going in-depth on the types of goals the Vancouver Whitecaps, and other teams, have scored this season and last.

As with the previous entries, I will use points earned as a marker of success. I will also rely on statistics collected my Major League Soccer here and WhoScored.com (2016 & 2017). I am also presenting fairly basic numbers, so if you are curious about specific things, let me know in the comments, and I will let you know what my numbers show, or include it in a future article. One article to come will be looking at some of the statistics we have examined so far, but from a defensive point of view. Finally, each of the statistics I am presenting are correlational and thus do not identify a cause, but rather show potential patterns. As correlational, they look at each statistic in a vacuum, not accounting for a myriad of other influential factors. Thus, these findings should be seen as a good talking point and not a definitive answer.

Proportion of Goals (2017)

Team Open Play (OVERALL) Counter Attack Set Piece Penalty Own Goal PPG Open Play (HOME) Counter Attack Set Piece Penalty Own Goal PPG Open Play (AWAY) Counter Attack Set Piece Penalty Own Goal PPG
Team Open Play (OVERALL) Counter Attack Set Piece Penalty Own Goal PPG Open Play (HOME) Counter Attack Set Piece Penalty Own Goal PPG Open Play (AWAY) Counter Attack Set Piece Penalty Own Goal PPG
New England Rev. 64.10% 5.10% 20.50% 10.30% 0.00% 1.16 75.90% 3.40% 13.80% 6.90% 0.00% 2.17 30.00% 10.00% 40.00% 20.00% 0.00% 0.23
Colorado Rapids 87.50% 0.00% 8.30% 4.20% 0.00% 0.88 89.50% 0.00% 10.50% 0.00% 0.00% 1.54 80.00% 0.00% 0.00% 20.00% 0.00% 0.17
Sporting Kansas City 71.00% 6.50% 12.90% 6.50% 3.20% 1.6 72.00% 8.00% 12.00% 4.00% 4.00% 2.23 66.70% 0.00% 16.70% 16.70% 0.00% 0.92
Portland Timbers 62.50% 6.30% 14.60% 14.60% 2.10% 1.46 65.50% 6.90% 13.80% 13.80% 0.00% 2 57.90% 5.30% 15.80% 15.80% 5.30% 0.93
Houston Dynamo 50.00% 10.90% 26.10% 10.90% 2.20% 1.46 45.50% 9.10% 33.30% 9.10% 3.00% 2.5 61.50% 15.40% 7.70% 15.40% 0.00% 0.57
Columbus Crew 71.40% 2.40% 16.70% 9.50% 0.00% 1.5 75.00% 0.00% 17.90% 7.10% 0.00% 2.21 64.30% 7.10% 14.30% 14.30% 0.00% 0.79
LA Galaxy 46.90% 6.30% 28.10% 12.50% 6.30% 0.92 40.00% 10.00% 40.00% 10.00% 0.00% 0.54 50.00% 4.50% 22.70% 13.60% 9.10% 1.33
Toronto FC 58.20% 3.60% 23.60% 10.90% 3.60% 2.07 60.60% 3.00% 24.20% 9.10% 3.00% 2.54 54.50% 4.50% 22.70% 13.60% 4.50% 1.64
Vancouver Whitecaps 51.40% 2.70% 35.10% 8.10% 2.70% 1.52 63.20% 0.00% 31.60% 5.30% 0.00% 1.75 38.90% 5.60% 38.90% 11.10% 5.60% 1.31
New York City FC 77.10% 0.00% 14.60% 8.30% 0.00% 1.81 79.30% 0.00% 13.80% 6.90% 0.00% 2.31 73.70% 0.00% 15.80% 10.50% 0.00% 1.31
Seattle Sounders FC 61.00% 0.00% 26.80% 9.80% 2.40% 1.56 52.40% 0.00% 38.10% 9.50% 0.00% 2.15 70.00% 0.00% 15.00% 10.00% 5.00% 1
Real Salt Lake 60.00% 10.00% 20.00% 10.00% 0.00% 1.25 60.00% 15.00% 15.00% 10.00% 0.00% 1.57 60.00% 5.00% 25.00% 10.00% 0.00% 0.93
Philadelphia Union 63.90% 0.00% 22.20% 13.90% 0.00% 1.15 64.00% 0.00% 20.00% 16.00% 0.00% 1.71 63.60% 0.00% 27.30% 9.10% 0.00% 0.54
DC United 59.10% 4.50% 13.60% 9.10% 13.60% 1.04 60.00% 0.00% 20.00% 10.00% 10.00% 1.29 58.30% 8.30% 8.30% 8.30% 16.70% 0.77
Minnesota United 65.60% 3.10% 18.80% 6.30% 6.30% 1 63.20% 5.30% 15.80% 5.30% 10.50% 1.43 69.20% 0.00% 23.10% 7.70% 0.00% 0.45
FC Dallas 86.50% 0.00% 10.80% 2.70% 0.00% 1.44 91.70% 0.00% 8.30% 0.00% 0.00% 1.77 76.90% 0.00% 15.40% 7.70% 0.00% 1.08
New York Red Bulls 71.10% 0.00% 10.50% 10.50% 7.90% 1.56 66.70% 0.00% 12.50% 12.50% 8.30% 2.08 78.60% 0.00% 7.10% 7.10% 7.10% 1
Chicago Fire 78.70% 6.40% 4.30% 8.50% 2.10% 1.58 81.80% 6.10% 3.00% 9.10% 0.00% 2.38 71.40% 7.10% 7.10% 7.10% 7.10% 0.77
Montreal Impact 76.20% 4.80% 7.10% 11.90% 0.00% 1.44 65.40% 7.70% 11.50% 15.40% 0.00% 1.92 93.80% 0.00% 0.00% 6.30% 0.00% 0.92
Orlando City 70.40% 0.00% 29.60% 0.00% 0.00% 1.19 72.20% 0.00% 27.80% 0.00% 0.00% 1.57 66.70% 0.00% 33.30% 0.00% 0.00% 0.75
San Jose Earthquakes 77.40% 0.00% 19.40% 3.20% 0.00% 1.33 81.00% 0.00% 14.30% 4.80% 0.00% 2 70.00% 0.00% 30.00% 0.00% 0.00% 0.71
Atlanta United 84.10% 4.50% 6.80% 2.30% 2.30% 1.5 81.80% 4.50% 4.50% 4.50% 4.50% 2.11 86.40% 4.50% 9.10% 0.00% 0.00% 1.13

The General Numbers

This season, three teams have scored more than 80% of their goals from open play: Colorado Rapids (87.5%), FC Dallas (86.5%), and Atlanta United (84.1%). Across the league, the average is 68% of goals (in 2016 the average was 64%). Of course, it comes as no surprise that Vancouver is 20th out of 22, scoring just 51.4% of their goals from open play. Who is below them? Houston Dynamo (50.0%) and LA Galaxy (46.9%).

Types of Goals (2017)

Team Open Play (OVERALL) Counter Attack Set Piece Penalty Own Goal Open Play (HOME) Counter Attack Set Piece Penalty Own Goal Open Play (AWAY) Counter Attack Set Piece Penalty Own Goal
Team Open Play (OVERALL) Counter Attack Set Piece Penalty Own Goal Open Play (HOME) Counter Attack Set Piece Penalty Own Goal Open Play (AWAY) Counter Attack Set Piece Penalty Own Goal
Toronto FC 32 2 13 6 2 20 1 8 3 1 12 1 5 3 1
Houston Dynamo 23 5 12 5 1 15 3 11 3 1 8 2 1 2 0
Chicago Fire 37 3 2 4 1 27 2 1 3 0 10 1 1 1 1
New York City FC 37 0 7 4 0 23 0 4 2 0 14 0 3 2 0
Sporting Kansas City 22 2 4 2 1 18 2 3 1 1 4 0 1 1 0
Columbus Crew 30 1 7 4 0 21 0 5 2 0 9 1 2 2 0
New England Rev. 25 2 8 4 0 22 1 4 2 0 3 1 4 2 0
Seattle Sounders FC 25 0 11 4 1 11 0 8 2 0 14 0 3 2 1
Atlanta United 37 2 3 1 1 18 1 1 1 1 19 1 2 0 0
New York Red Bulls 27 0 4 4 3 16 0 3 3 2 11 0 1 1 1
Portland Timbers 30 3 7 7 1 19 2 4 4 0 11 1 3 3 1
San Jose Earthquakes 24 0 6 1 0 17 0 3 1 0 7 0 3 0 0
Montreal Impact 32 2 3 5 0 17 2 3 4 0 15 0 0 1 0
FC Dallas 32 0 4 1 0 22 0 2 0 0 10 0 2 1 0
Vancouver Whitecaps 19 1 13 3 1 12 0 6 1 0 7 1 7 2 1
Philadelphia Union 23 0 8 5 0 16 0 5 4 0 7 0 3 1 0
Orlando City 19 0 8 0 0 13 0 5 0 0 6 0 3 0 0
Real Salt Lake 24 4 8 4 0 12 3 3 2 0 12 1 5 2 0
Colorado Rapids 21 0 2 1 0 17 0 2 0 0 4 0 0 1 0
Minnesota United 21 1 6 2 2 12 1 3 1 2 9 0 3 1 0
DC United 13 1 3 2 3 6 0 2 1 1 7 1 1 1 2
LA Galaxy 15 2 9 4 2 4 1 4 1 0 11 1 5 3 2

In the past, Vancouver Whitecaps have characterized themselves as a counter-attack team. However, in 2017 the Whitecaps are currently 13th in reliance on counter-attacking goals, with only 14 teams having at least 1 counter-attack goal. In other words, of the 14 teams in MLS that have scored counter-attacking goals this season, the Whitecaps are 13th. How does this compare to last season? The numbers are about the same. The Whitecaps were 15th out of 18 teams that had at least 1 counter-attack goal. In other words, despite the constant claim that the Whitecaps are a counter-attack team and thus concede possession (and everything else) to get that fast-break goal is not supported by the numbers, in relation to the rest of the league.

So where do all the Whitecaps goals come from? I am sure you all know the answer to this already, but it is from set-pieces. Overall, 35.1% of Vancouver’s goals this season have come from set-pieces. The next closest is Orlando City (29.6%) and LA Galaxy (28.1%). This pattern was evident last season as well, with Vancouver being the 3rd most reliant on set-piece goals in 2016, with them accounting for 28.9%. Only New York Red Bulls (32.3%) and Sporting Kansas City (31.0%) were more reliant. There are plenty of ways to interpret this finding, so I am curious what you all think.

When broken down into home and away, a slightly different pattern emerges for the Whitecaps. At home, it is no surprise that they score more goals from open play (63.2% to 38.9%), however, they are equally reliant on set-piece goals whether at BC Place or on the road (31.6% to 38.9%). This is not surprising, as most teams rely on open play goals more at home than on the road. One extreme outlier though, worth noting, is Montreal Impact. At home open play goals account for 65.4%, but on the road, that number jumps to 93.8%.

Comparing the Whitecaps 2017 numbers to 2016, there is a slightly different pattern. In 2016, the Whitecaps were equally reliant on open play goals home and away (46.4% to 47.1%) but less reliant on set-piece goals away (17.6% to 35.7% at home). I was surprised to learn this, but almost a quarter (23.5%) of all Whitecaps away goals last season were the result of penalty. Add in 1 own-goal, and just under 30% of Vancouver’s 2016 away goals were from the penalty spot or an own-goal from the opponent. SCARY!

What Types of Goals Lead to Success?

2017 Correlates of Goals

. Open Counter Set Penalty Own
. Open Counter Set Penalty Own
Overall 0.07 -0.01 -0.07 0.11 -0.17
Home 0.28 -0.12 -0.30 0.06 -0.10
Away -0.01 -0.12 0.04 -0.20 0.28

For teams that have been successful this season, what types of goals do they rely on most? Overall, no type of goal seems to translate to success at a significant level. Although, goals from open play are positively correlated (0.07) with success while set-piece goals are negatively correlated (-0.07). For home matches, we see this pattern exaggerated. Reliance on open play goals is correlated with points per game at 0.28 while set-piece goals is at -0.30. Away, again, no major patterns emerge. Relying on penalty kicks is negatively correlated with points per game (-0.20) while own-goals is positive (0.28). However, these numbers are quite small, so it is hard to take anything from the results.

For the Vancouver Whitecaps in 2017, these findings are….less than ideal. The Whitecaps are middle to lower end of the pack when it comes to reliance on open play goals at home and 4th in reliance on set-piece goals at home.

Is There Still Hope for the 2017 Whitecaps?

Do the numbers suggest that the Whitecaps will not be successful at the end of the 2017 season? Perhaps, but it is worth noting that many teams still have 20% of their season left. In the end, these numbers could look very different. For example, in 2016, set-piece goals were correlated with points (0.35) while open play goals were correlated with less points (-0.12). At home, again set-piece goals were correlated higher with points than open play goals (0.18 to 0.10). Maybe we will see this pattern emerge again by the end of the 2017 season. What does appear consistent though is on the road, go for those penalty kicks and own goals. They seem to be important!

2016 Correlates of Goals

. Open Counter Set Penalty Own
. Open Counter Set Penalty Own
Overall -0.12 -0.40 0.35 0.16 -0.20
Home 0.10 -0.13 0.18 -0.13 -0.31
Away -0.10 -0.14 -0.15 0.38 0.35

What is Correlation?

Since I know that some people are not that familiar with statistics, I thought I would conclude with a brief definition/explanation of correlation. For those that are familiar with correlation, you can skip this section.

Correlation is a statistical measure that attempts to show a mutual relationship between two (or more) things. The most common measure of correlation is Pearson’s coefficient. This measure ranges from -1 to +1. If there is no relationship between the two variables (e.g., shots per game and points per game) then the correlation will be ‘0’. It is important to note that a negative correlation is just as important as a positive correlation. A positive correlation simply means that when one measure increases, the other measure also increases. In our study, a positive correlation would mean that as a team takes more shots their points per game increases. However, a negative correlation means that as one measure increases, the other decreases. In our study, this would mean that as a team takes more shots, their points per game decreases. As you can see, a negative correlation can be very important.

The final, general, question I will answer here is ‘What is a good/high correlation?’. However, if you have more questions, do not hesitate to ask them below and I will answer them and add them to future articles. Back to the question. A good/high correlation is hard to answer. For example, the correlation between lung cancer and smoking is something like 0.20 to 0.40. However, we are confident that smoking is related to lung cancer. In general, for the articles that I will be posting, I would consider above 0.30 to be good with above 0.60 to be great!