Evaluating the Trade Deadline: Who Got Better?

Despite Saskatchewan’s decision to pass on a fire sale, this week’s NLL trade deadline was great. Perhaps to the surprise of some, general managers around the league were active until the final moments, culminating in a series of compelling deals. Whether it was San Diego attempting to bolster its right side with the acquisition of Brett Hickey or New York opting to move on from former #1 overall pick Tyson Gibson, each deal was eyebrow-raising in its own way.

As is always the case with trades, it is both unfair and unreasonable to try to grade winners and losers in the immediate aftermath of a deal’s happening. This is especially true when future draft picks are involved. We’ll resist the urge to pass judgements as we evaluate the happenings of the deadline.

Focusing on the teams that acquired players (as opposed to picks), this post is dedicated to analyzing how the extent to which each individual adds to his new club statistically. On paper, this amounts to evaluating each player and each team on a trio of metrics, two of which will be entirely new to the LaxMetrics lexicon. Primarily, we’ll be guided by Most Outstanding Player Scores (MOPscores). These MOPscores tell us how a player compares to his peers in a collection of different statistical categories. We will use these to estimate how much “better” each player makes his new team in a general sense. Additionally, we’ll employ a pair of new statistics that allow for rough comparisons between forwards, defenders, and transition players.

The first of the two new statistics is what we’ll refer to as “Net Special Teams Goals” (Net STG). If you read our earlier post this week about power plays and penalty killing, you have been introduced to a rough concept that is similar to the Net STG used for this exploration. In a short summary, Net STG is a position-independent measure of how much a player impacts his team via special teams. Among the inputs in Net STG are a player’s penalties drawn, power play goals, penalty minutes, and short-handed goals to name a few. 

The second of the two new metrics is what we’ll refer to as “Goals Added”, which is mostly an offensive statistic. Goals Added will be best used to compare forwards and offensively minded transition players. Think of Goals Added as a measure of how many total goals a player is responsible for creating as both a scorer and a passer relative to forecasts and his peers. 

Let’s begin by looking at the full list of players who changed teams at or around the deadline. Of the 10 in question, we can see each player’s Net STG, Goals Added, and MOPscore. At just a moment’s glance, we can see that Tyler Digby and Shawn Evans have been extremely valuable pieces in helping their teams get to power plays and then executing once on them. On the other hand, Brett Noseworthy struggled staying out of the penalty box while playing for Buffalo, putting more pressure on their penalty kill unit. These are just a couple of examples to keep in mind. We’ll come back to this list later to break down each trade in terms of the three categories in question.

From a big picture vantage point, we can see every team’s collective standing in each of the three values as well. Additionally, we see each team’s average MOPscore per player. There are a few surprises here or there, but none that completely rage against the larger body of pythagorean data and advanced statistics that LaxMetrics uses to project win totals. The only “major” outlier is Panther City’s having the NLL’s second-highest average MOPscore. This can largely be attributed to the fact that PC boasts five of the league’s best individual defense/transition players according to LaxMetrics data. While the Panther City defense may be struggling as a unit, they have produced a series of very impressive individual seasons statistically.

Let’s turn our attention back to the players on the move. Just in terms of MOPscores, we see that Anthony Joaquim was the “best” player to be moved at the deadline, while Noseworthy was the “worst” to change teams. Obviously those labels of “best” and “worst” are used extremely loosely. In this instance, they’re simply a reflection of how the numbers—MOPscore specifically—say each individual has performed to this point in the season. 

Of the 10 players traded, only four would be classified as having “above average” seasons. This is relative to the league’s average MOPscore. Similarly, only five players involved in trades have posted Net STG and Goals Added values that exceed the league average. In other words, at least half of the players changing teams at the deadline are having sub-par campaigns. With all this groundwork finished, we can focus on each team individually.


IN: None (draft compensation)

OUT: Brett Noseworthy (-4.35 / 0.58 / 18.01)


IN: Tyson Gibson (1.44 / -5.61 / 38.20), Anthony Joaquim (-0.25 / 1.94 / 70.07)

OUT: Sam LeClair (-0.13 / -4.33 / 45.50), Ron John (-0.13 / 1.03 / 53.14), Tyler Digby (5.18 / 0.81 / 37.62)


IN: None (draft compensation)

OUT: Dawson Theede (0.75 / -2.05 / 37.58)


IN: Sam LeClair (-0.13 / -4.33 / 45.50)

OUT: Anthony Joaquim (-0.25 / 1.94 / 70.07), Brett Hickey


IN: None (draft compensation)

OUT: Shawn Evans (4.95 / 2.80 / 52.58)


IN: Brett Hickey (-1.33 / -3.74 / 41.50)

OUT: none (draft compensation)

As the table above illustrates, New York was the LaxMetrics “winner” of the trade deadline, meaning they improved the most statistically. Through making significant moves, the Riptide added 10.61% to their overall MOPscore, while also picking up a total of 6.19 Goals Added. All of this is despite trading away 2019 #1 overall pick and reigning Rookie of the Year Tyson Gibson. While New York takes a significant hit to their Net STG by adding Noseworthy, they still are positioned among the league’s best in Net STG. If anyone was equipped to handle the dent brought on by Noseworthy’s Net STG numbers, it was the Riptide.

Georgia would likely be second in the pecking order of “winners”, who facilitated net improvements to their teams via trade movement. Their added MOPscore of 5.66% is second to only New York. Leblanc’s MOPscore over 59 also improves the Swarm’s MOPscore average. Furthermore, Georgia’s acquisition of Leblanc brings them a Net STG addition of 0.44, which is a better number by itself than six teams’ season marks in the category. Overall, adding Stephen Leblanc was a modest, shrewd move that made the Swarm noticeably better mathematically.

With Saskatchewan standing on the sidelines, Philadelphia took charge as the most aggressive deadline seller. As a result, the Wings walk away with the largest net loss in MOPscore points, swapping Joaquim and Hickey for LeClair. But at the end of the day, Philly’s moves were made with the future in mind, less so the present. Grading and analyzing their two deals will likely have to wait for a couple years.

For San Diego, their addition of Brett Hickey makes for an interesting dynamic on their right side that Patrick Merrill and Josh Sanderson will have to sort through. By the numbers, Hickey brings down the Seals’ average MOPscore, while also carrying negative Net STG and Goals Added numbers. From a raw “total MOPscore” standpoint, Hickey makes the Seals better, but that’s the only numerical area in which he does so. In the the other two categories of consideration (plus Average MOPscore), there’s a case to be made that he actually makes them worse statistically.

Lastly, LaxMetrics is unconvinced that Halifax did anything to substantively make themselves a better team. Perhaps it’s a coincidence, but the T-birds lost twice last weekend with Evans in the fold for the first time. Subtracting Leblanc from Halifax’s numbers actually creates a fairly significant loss. While Evans dwarfs Leblanc in Net STG and Goals Added, Leblanc’s usage rate under 7% makes his performance more value-driven on far fewer touches. For comparison, Evans has one of the league’s highest usage rates at over 22%. In other words, Halifax traded value for volume. Given that their offense is loaded with other quality players, LaxMetrics is skeptical that a value-for-volume swap actually makes the team better. Despite being one of the most aggressive buyers at the deadline, Halifax added only a net 3% to their MOPscore point total, and actually saw a small decrease in their Average MOPscore per player. Given that Theede might not even see the floor for them this year, that mark of 3% improvement might even be inflated.

The rest of the major moves come with ample questions that we won’t be able to answer until later. Rochester obviously takes a step back statistically without Evans. Panther City had all but moved on from Theede making his departure a largely moot point. How will things work out for Colorado giving up as much as they did? The numbers suggest a small step back for Colorado, but that is without adjusting for new roles enjoyed by Gibson and Joaquim. Anything is possible for the Mammoth.

It’s impossible to know how these trades play out over the season’s final two months. Often winners and losers are quite different with the benefit of hindsight. The LaxMetrics numbers can give us an idea of what net changes look like on paper. But surely, there will be developments that the numbers can’t quite see in advance. Predicting the future is hard, so we’ll have to settle for the next-best thing: being patient and waiting to see how each deal matures.

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