The Vancouver Whitecaps get Worse With This Player on the Field!!! (Not Clickbait, Gone Wrong)

The other day my eye was caught by this tweet from @lojdvancouver

This was an interesting concept to me so I thought why not take it further and calculate every player’s personal goal difference. But then it occurred to me that I had read this article from statsbomb.com which pointed out that shots and key passes are more predictive of future goals and assists than a players past goals and assists. So for this to be really meaningful I'd have to figure out every player’s shot differential as well. So over the last two days I went over every Vancouver Whitecaps game of 2019 and counted how many shots for/against and goals for/against each player was on the field for.

What, if anything, did I learn from this exercise? Read on to find out!

Oh God, things are so bad:

The Vancouver Whitecaps get out shot at a staggering rate. This isn’t news. But you really feel it when you’re going through and counting every shot. As a team the Whitecaps have a shot differential of -130. Now keep in mind that the Whitecaps have been very good at limiting the opposition to shots from bad areas, so most of those shots are low quality. But, let’s say they limit the opposition to shots that have a 5% chance of going in, that’s 6 or 7 extra goals the opponents have scored up to this point in the season because of how many shots the ‘Caps give up. How many of Vancouver’s league leading 8 ties turn into wins if you’re not conceding those extra 6 goals?

But enough about systemic problems, which individuals should we put under the microscope?

Well the 5 players with the best goal differential are Fredy Montero (+1), Lass Bangoura (even), Russel Teibert (even), Brett Levis (even), and Ali Adnan (even).

Adnan is notable because when you compare him to other defenders you can see just how much of a difference having him in makes. The next best defender is Derek Cornelius (-2), followed by Scott Sutter and Jake Nerwinski (-3), Erik Godoy (-4) and Doneil Henry (-5).

The players with the worst goal differentials are

Felipe (-10!) and the defenders mentioned above. The team collectively has a -4 goal differential so it’s to be expected that defenders who play most of the minutes would have negative differentials but Felipe being -10 beggars belief. I do want to correct one error from the tweet above though. It is not true that the Whitecaps have never been leading with Felipe on the field. For 31 minutes against the Chicago Fire they had a 1-0 lead with Felipe on the pitch. A -10 differential seems to suggest, to be blunt, that Felipe sucks. But maybe Felipe has just gotten very unlucky. To get a better idea of things we need to look at shots against.

But First...

Is there a correlation between being on the field for lots of shots against and being on the field for lots of goals against? The answer is yes, just barely. Goal differential and shot differential in this data set have an R value of 0.116. Which is not very high but it is a weak positive correlation.

Ok on to the numbers

I quickly realized that the Whitecaps get outshot to such a ridiculous degree, no matter who is on the field, that just going with the raw numbers punished players who had played the most minutes. So I calculated the players shot differential per 96 minutes (the average length of a game including stoppage time). I also took Theo Bair and Branden McDonough out of the data because they’ve played so few minutes: they’re something ridiculous like -50.

The players with the best shot differential per 96 minutes are Joaquin Ardaiz (0.65), Andy Rose (-5.4), Lucas Venuto (-6.04), Yordy Reyna (-6.65), and Jake Nerwinski (-6.22).

Ardaiz’s differential is almost certainly due to game state. He is often subbed on when the other team is sitting back and defending.

I’m impressed that Andy Rose seems to have such a positive impact (he also has the 6th best goal difference at -1). Honestly most stats seem to suggest he does basically nothing. He averages less than one tackle, interception, foul, dribble, block, shot, and key pass per game. Yet for some reason when he’s on the field it seems things go well, or at least better. Maybe his height intimidates the other team. Maybe he’s such a good communicator that he generals the team into playing well around him despite physically doing very little. Maybe he’s just gotten insanely lucky. Someone who’s better at math can figure that out.

The team is overrun considerably less with Yordy Reyna and Lucas Venuto on the field compared to Lass Bangoura (-7.9) and PC (-8.4). PC and Venuto have actually been on the field for the same number of shots against despite Venuto playing 268 more minutes.

Jake Nerwinski looks significantly better at -6.22 than Scott Sutter -8.86.

If we decided we were all in on these stats then these would be some lineups we could go with:

The goal difference lineup:

The shot difference lineup:

I’d say that the shot differential lineup looks a lot more reasonable, but both have some weird ones in them. Starting Levis over Reyna and Venuto seems pretty ridiculous. The goal difference lineup also includes guys like Bangoura and PC who are some of the worst shot differential players. The goal difference team would also require you to drop Erik Godoy and Doneil Henry to the bench which seems...stupid.

The shot differential team looks pretty close to what I'd consider the Whitecaps’ best lineup, but features the worst goal difference player in Felipe, 0 goal striker Joaquin Ardaiz, and statistical ghost Andy Rose so I’m not sure we can definitively say it means anything either.

What did we learn?

Did we learn anything with this exercise? If nothing else we learned the sheer magnitude by which the Whitecaps are out shot and why that’s a big problem. I’d say it seems that a player’s individual goal difference is basically random and that shot differential might have some value, but is imperfect when judging what a player brings to the table. To say anything definitive about these stats you’d have to repeat this exercise with every team in the league over multiple seasons and perhaps figure out how stats like PDO and xG might effect these numbers. But SB Nation is going to have to seriously up my stipend if they want me to do that much work.

Below I’ve included a table that I created while making this project. I’ve also added a “shot contributions” stat which is just the sum of a player’s shots and shot assists per game. I figure this will give you some idea who is putting in the work to counterbalance their terrible shot differentials. Obviously this is a bit unfair to defenders but I thought it would add some useful context.