Do NHL trade deadline deals actually work?

It’s trade deadline time, and fans of middling teams are no doubt dreaming of a shining knight who will ride into town and inspire the team President to dust off his long abandoned Stanley Cup parade map.


But do deadline acquisitions actually work, or is adding a key part now like trying to fix a plane mid flight?


Or maybe athletes are like old houses, where the seller knows about the leaky roof, and the buyer’s going to find out soon enough.


The Department of Hockey Analytics decided to answer this question the only way we know how – by digging up the facts.


We started by looking at every significant deadline acquisition over the past 15 seasons. We considered a deal significant if it involved someone who was in the top 100 in scoring or average ice time.


We ended up with 90 trades in total, 70 of which involved teams that made the playoffs.


We tallied up each player’s offensive production and compared how he did with his old team vs. his new team, both during the regular season and playoffs.


The results were a little surprising.


As the table shows, on average players performed identically with their new teams for the rest of the regular season and then became less productive in the playoffs. Because playoffs tend to be lower scoring, the drop off there is about what you’d expect.


Old Team

New Team


Goals Per Game




Assists Per Game




Points Per Game




*Goals, Assists and Points are averaged across all players (90 for regular season and 70 for playoffs)


In other words, trades don’t seem to have any impact on production.


This is comforting to GMs because it means they generally get what they’re paying for.


So trade away, right?


Well, not so fast. Remember – we got here by looking at a lot of trades, 90 of them to be precise.


But if you’re looking for that white knight, you’re getting one player, not 90. Although production stays constant on average, there’s a huge range of possible outcomes for each guy.


In the chart below, each of our 90 players is a single dot. On the horizontal axis, we have his points per game with the old team, while the vertical axis is points per game after the trade. The diagonal line represents identical production with each team.


Anybody who is above the line did better after being moved; anyone below did worse.



So, for example, when Theo Fleury went from Calgary to Colorado in 1998-99, his production soared from a solid 69 points in 60 games (1.15 points per game) to a walloping 24 in 15 (1.6 points per game).


But for every Fleury, there are just as many guys who stiff, like Keith Tkachuk, who tallied 71 points in 64 games with Phoenix in 2000-01 (1.109 points per game), before dropping to 8 in 12 (0.667 points per game) with St. Louis.


The range of outcomes gets particularly wide for the biggest scorers – precisely the ingredients teams hope will put them over the top.


If you think about it, this isn’t all that surprising. All players are prone to streaks and slumps, and scorers are often the worst offenders. Over an entire season it all evens out, but deadline acquisitions happen when there are very few games left, meaning chances are all the new team will get is a single streak or slump.


Which leaves us with a cautionary message for GMs for the coming week: if you’re looking to add that final piece and go for it all now, it may work out. But it’s also pretty likely that instead of getting the high scoring prince, you’ll wind up overpaying for the frog.


Maybe keep that parade route in a drawer until June after all.


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