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When Should The Whitecaps Sign a CPL Player?

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CPL: Canadian Championship-HX Wanderers FC at Valour FC James Carey Lauder-USA TODAY Sports for CPL

In 2019, Vancouver Whitecaps academy graduate Jose Hernendez scored his first professional goal for CPL side Pacific F.C. I remember seeing at least a few tweets saying the Whitecaps had been foolish to let him go. At time of writing it is August 15th 2021 and Hernendez has still not scored his second professional goal. Clearly we need some standards.

I set out to try and establish some standards. It turned out to be quite difficult. I recently did an analysis of how USL scoring translated to MLS. That was pretty easy. There has been tons of movement between the two leagues so it’s easy to get a good sense of what you can reasonably expect from a player who makes the jump. That’s not really the case with CPL and MLS. CPL has only played one full season so far and it has had a relatively small number of players leave and go to another league.

By my count there have been 12 players who have played at least 300 minutes in both MLS and CPL. 2 centre midfielders, 5 winger/fullback tweeners, 4 centre backs, and 2 strikers. This is not exactly a helpful sample to be working with. It is small and the players don’t necessarily have a lot in common.

There has, however, been more movement between the CPL and USL. By my count 28 players have played in both leagues. There is a lot more information on how USL production translates to MLS so I thought I might reverse engineer my work on USL to MLS production. This, however, comes with its own problems. USL and CPL are close enough in quality that a player’s role has a big impact on his scoring. For example; David Norman Jr. averaged 0.25 xG+xA per game in USL but so far has only managed 0.07 in the CPL. Aboubackar Sissoko averaged 0.04 xG+xA per game in CPL but has rocketed up to 0.24 in USL. When you dive in to their positional data on Transfermarkt you can see that these changes are down to Norman being played in a more defensive role than he had in USL and Sissoko being deployed further up the pitch than he was in the CPL. But this means that it’s kind of hard to take any hard positions on the relative qualities of the leagues, other than to say they are close enough that you can change a player’s role and his involvement in a team’s scoring chances will go up or down.

All of this is to say, it’s really hard to say for sure how CPL success will translate to MLS. Perhaps if you are stumbling across this article in the year 2024 the picture might be a lot more clear but right now things are very murky. That said, I did the best with what I have.

Scoring

On average players generated 38% less xG+xA per game in MLS than they did in CPL. If you don’t include the centre backs, most of whom averaged a pretty tiny amount of xG in both leagues, the number raises to 51%. Notably, current CPL golden boot leader Mo Babouli has seen his xG+xA triple in the CPL compare to what he was doing in MLS. So I can say pretty confidently that players score more in CPL than they do in MLS but right now there isn’t really enough information to say by how much.

On average players scored more in the USL than they did in CPL but, as I alluded to earlier, this mostly seems to be driven by players having different roles when they moved between the leagues. I tried breaking it down by position and factoring out various players but nothing was very clarifying. Some players saw enormous rises in their production going one way and some saw it going the other way. So, I have no idea how the quality of CPL compares to USL. USL players seem to be paid a little better and the only Voyageur’s Cup matchup between a USL team and a CPL team was one by the USL team. CPL stand outs like Marco Bustos, Terran Campbell, and Ryan Telfer all scored more in CPL than they did in USL. So I am inclined to say the USL is better but I don’t say that with very much confidence.

So, if you’re the Whitecaps and you’re trying to evaluate if a CPL player could translate his scoring success to MLS, what do you do with this scattered information? Well, you know that the player is probably going to see a hefty decrease in his scoring. This decrease is probably somewhere between 30% and 60%. That’s a huge margin! So, due to the lack of information, I would urge caution. You should ask yourself if the player in question would still be interesting to you if his production were to be cut in half. As time passes and we get more information this expectation can be adjusted up or down accordingly.

This brings me nicely to the next thing that should be considered. At what level of scoring does a player become interesting? In general I would say you want players you bring in from outside the club to be at least above the 25th percentile in MLS. if they can’t clear that bar then you might as well just give an academy graduate a chance. So I looked at the most recent full MLS season (2019) and established the 50th and 25th percentile point in scoring for each position amongst players who played at least 450 minutes. It looks like this:

50th/25th Percentiles in 2019 MLS Season By Position

Position 50th Percentile 25th Percentile
Position 50th Percentile 25th Percentile
Striker 0.49 0.42
Winger 0.37 0.29
Attacking Midfielder 0.41 0.31
Centre Midfielder 0.17 0.11
Full Back 0.1 0.07
Centre Back 0.06 0.03
Data Courtesy of American Soccer Analysis

Next I looked at a sample of CPL players and their production in the 2021 season so far. I basically just picked players I had seen people say were good or deserved a shot in MLS. Then I looked at how they would do in MLS if they saw a 38%, 50%, or 65% reduction in their scoring. If they would be between the 25th and 50th percentile in xG+xA with that reduction then they have “pass” written next to their name. If they would be above the 50th percentile they have “super pass” written next to their name. If they wouldn’t crack the 25th percentile then they get “fail” written next to them. Defenders of the CPL will no doubt argue that including the possibility of a 65% reduction in production is excessively harsh. But we have to remember that’s the situation of Mo Babouli who, at the time of writing, is tied for the league lead in goals. Until we have more evidence that Babouli is an outlier I think we have to treat a 65% reduction as a serious possibility.

Projected Scoring of CPL Stars in MLS

Player Position CPL xG+xA/90 MLS Production at 34% decrease MLS Prodcution at 50% Decrease MLS Production at 65% Decrease
Player Position CPL xG+xA/90 MLS Production at 34% decrease MLS Prodcution at 50% Decrease MLS Production at 65% Decrease
Marco Bustos Winger 0.42 0.26 (fail) 0.21 (fail) 0.14 (fail)
Kadin Chung Fullback 0.1 0.06 (fail) 0.05 (fail) 0.03 (fail)
Joao Morrelli Striker 0.65 0.40 (fail) 0.32 (fail) 0.22 (fail)
Max Ferrari Winger 0.29 0.17 (fail) 0.14 (fail) 0.1 (fail)
Kyle Bekker Centre Mid 0.25 0.15 (pass) 0.12 (pass) 0.08 (fail)
Stefan Karajanovic Winger 0.52 0.32 (pass) 0.26 (fail) 0.18 (fail)
Diyaeddine Abzi (2021) Fullback/Winger 0.31 0.19 (super pass) 0.15 (super pass) 0.1(super pass)
Diyaeddine Abzi (2019) Fullback 0.24 0.15 (super pass) 0.12 (super pass) 0.08 (pass)
Tristan Borges Winger 0.89 0.58 (super pass) 0.44 (super pass) 0.31 (pass)
Tristan Borges (no penalties) Winger 0.63 0.39 (super pass) 0.31 (pass) 0.22 (fail)
Jake Ruby Fullback 0.13 0.08 (pass) 0.06 (fail) 0.04 (fail)
Easton Ongaro Striker 0.56 0.34 (fail) 0.28 (fail) 0.19 (fail)
Sergio Camargo Winger 0.66 0.41 ( super pass) 0.33 (pass) 0.23 (fail)
Lucas McNaughton Centre Back 0.08 0.05 (pass) 0.04 (pass) 0.03 (pass)
Mohamed Farsi Fullback 0.12 0.07 (fail) 0.06 (fail) 0.04 (fail)
Kwame Awuah Fullback 0.09 0.06 (fail) 0.05 (fail) 0.03 (fail)
Alessandro Hojabrapour Defensive Mid 0.1 0.06 (pass) 0.05 (pass) 0.03 (fail)
Olli Basset Centre Mid 0.23 0.14 (pass) 0.12 (pass) 0.08 (fail)
Thomas Gardner Winger 0.09 0.05 (fail) 0.04 (fail) 0.03 (fail)
Lowell Wright Striker 0.36 0.22 (fail) 0.17 (fail) 0.12 (fail)
Terran Campbell Winger 0.51 0.31 (pass) 0.25 (fail) 0.18 (fail)
Austin Ricci Striker 0.32 0.20 (fail) 0.16 (fail) 0.112 (fail)
Noah Verhoven Attacking Mid 0.1 0.06 (fail) 0.05 (fail) 0.03 (fail)
Dominick Zator Centre Back 0.06 0.04 (pass) 0.03 (pass) 0.02 (fail)
Akeem Garcia Striker 0.45 0.27 (fail) 0.22 (fail) 0.15 (fail)
Amir Didic Centre Back 0.11 0.07 (super pass) 0.06 (super pass) 0.04 (pass)
Sean Rea Winger 0.3 0.18 (fail) 0.15 (fail) 0.1 (fail)

As you can see, there’s quite a number of CPL players who could maybe play at an MLS level. however there are only a few slam dunks, players who would be above the 25th percentile in scoring for their position even if the jump to MLS cost them 65% of their xG+xA. Those players are Tristan Borges, Diyaeddine Abzi (I included his 2019 and 2021 totals because his role has been a lot more attacking this season), and Amir Didic. Obviously in the cases of Abzi and Didic, defensive players, you would have to take into account things other than their scoring before deciding to sign them. More on that Later. But Borges, who’s contract with his dutch parent club expires in November, seems like a great candidate for an MLS contract. Granted, his total is boosted by the fact that he takes penalties. But even factoring those out gives him two passes.

In general I would say players who manage to achieve two passes would be worth looking in to more, and possibly even some players who achieve one pass if scoring is not their main role.

Defending:

Defending was a lot more difficult to analyze. The main problem was differences between data sources. It became clear pretty quickly that centre circle has much higher standards for what counts as a successful tackle than who scored. The Statsbomb data on fbref seems more similar but that only goes back to 2018 which means it’s totally useless for evaluating someone like Andrew Jean-Baptiste or Maxim Tissot. Someone with access to data from the same source for both leagues could probably do a better job of looking in to this but SB nation hasn’t given me a raise in three and a half years so there’s not much I can do.

So to at least try and say something about how defensive performance in CPL translates to MLS I went with a case study. Joel Waterman has played significant minutes in both leagues in the past three years. When we look at him we can see that his defensive stats were a lot more stable between leagues than the attacking stats were for the attacking players. His tackle success rate took the biggest hit, falling by 50%. His interceptions fell 20% and his success in aerial duels fell by 6%.

Waterman is, of course, only one guy. But his case makes it pretty clear that you are looking at a drop off, though it’s really hard to say how big that drop off would be. Therefore I would suggest decision makers apply the same logic we discussed earlier and proceed cautiously. Until we know with more certainty the Whitecaps should only consider defenders who are dominant.

Some players who I would say meet that definition include Morey Doner, Amir Didic, and Lukas MacNaughton. Abzi, who you may remember had attacking stats that stood out, has defensive stats that are good but not great. A difficult decision to be made there.

Another noteworthy thing about Waterman’s transition to MLS is that all of his passing numbers are really good. Unfortunately centre circle data doesn’t really track any of the same passing stats that the other data sources available to me do. So I can’t really comment on how passing ability might translate but Waterman provides some evidence it might translate rather well.

Conclusions:

It’s really complicated and there is no clear right answer. Decision makers should proceed with caution and focus their attentions on players who are dominant until there is more evidence of how CPL performance translates to MLS.