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THN Analytics: Visualizing the Trade

Benjamin Wendorf
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Johnny Boychuk, Kyle Okposo and John Tavares (Getty Images) Author: The Hockey News

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THN Analytics: Visualizing the Trade

Benjamin Wendorf
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Midseason trades are a bit of a curiosity in the NHL; they’re usually, at least on one side, expressions of immediate purpose – though intuitively both teams are getting someone they want. From a player’s perspective, it’s revolutionary, even if the results don’t show it: a new home, new fan base, new teammates.

Midseason trades are a bit of a curiosity in the NHL; they’re usually, at least on one side, expressions of immediate purpose – though intuitively both teams are getting someone they want. From a player’s perspective, it’s revolutionary, even if the results don’t show it: a new home, new fan base, new teammates. Analytically, a trade is an immediate sliding of variables for both teams, as all at once depth and deployment are affected. In the past, a player trade was often discussed as a matter of whether a player “catches on” with their new team, the idea being that when a player catches on, they score more points. Think of how successful the Minnesota Wild’s trade for Guillaume Latendresse looked in 2009-10, when he put up 37 points in 55 games, or Colorado’s 2010-11 acquisition of Tomas Fleischmann that yielded 21 points in 22 games. Compiling all the midseason trades from 1997-98 to the present, and focusing on the 106 players that played 20+ GP for both teams in a single season, I began to notice the impact a coach’s player usage had on whether the player “caught on.” One way to show this is by expressing a player’s ice time as a percentage of a team’s total ice time in the games they participated (TOI%), pre and post-trade. TOI% is a valuable statistic overall because it’s more truly reflective of contribution. An example: last season, Sidney Crosby was on the ice for approximately 36% of his team’s even-strength minutes. Since you cannot hide on a hockey rink, it’s reasonable to say he played an important role in 36% of his team’s even-strength play. In terms of trades, TOI% can tell us whether traded players tend to be given more substantial roles in their new homes:

Getting Traded, In Pictures Fig 1 Getting Traded, In Pictures Fig 2

I included markers in the charts to indicate the average TOI% your typical NHL forward lines and defensive pairs receive. As you can see, players tend to get used more after their trade; in the case of forwards that meant breaking into the top 6 and an increase in powerplay responsibilities. For defensemen, it meant jumping nearly to the top pairing and an across-the-board special teams increase. Once again, this should make sense; teams don’t make a habit of acquiring players they don’t want. The result in production (“catching on”) for all players was about .08 more points per game, or going from 42 points to 49 points in 82 games – the difference between Kyle Okposo and Tyler Seguin last season. Another way to visualize the change in ice time is through using what are called “TOI Charts.” TOI charts show a player’s TOI% progression over the course of a season. Using the examples from the beginning (and keeping in mind top-line forwards hover around 30% even-strength and 55% powerplay minutes): Guillaume Latendresse, 2009-10 – Montreal Canadiens to Minnesota Wild When Jacques Martin took over the Habs in fall of 2009, Latendresse’s polarizing skill set put him on the wrong side of the coach. The Wild, similarly disaffected with 2005 1st-round pick Benoit Pouliot, made a one-for-one trade.

Getting Traded, In Pictures Fig 3

While Pouliot has likely been an underappreciated talent, Latendresse revived his career – though the injury bug has robbed him of a complete revival. Tomas Fleischmann, 2010-11 – Washington Capitals to Colorado Avalanche Like Latendresse, Tomas Fleischmann’s potential vs. results were maddening for Capitals’ management, and after a rough start to 2010-11 they sent him along in exchange for defensive defenseman Scott Hannan.

Getting Traded, In Pictures Fig 4

“Flash” took off in Colorado, and netted a big contract with the Florida Panthers the following summer. After a couple years as one of their most dangerous forwards, his performance has cooled of late. These charts really bring out a big driver in Latendresse and Fleischmann’s success: increased usage, especially in terms of offense, by their coaches.

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TOI charts can also show the impact of a trade on the depth of a team’s forward lines and defense pairings. By comparing the progression of TOI% for all the defensemen on the 2010-11 Toronto Maple Leafs, for instance, we can see who was used to “replace” Tomas Kaberle when he was swapped for Boston’s Joe Colborne and a 1st and 2nd round pick in 2011:

Figure 6 THN Trades Figure 5 THN Trades

As you might have noticed, the TOI% is expressed a little differently here. The Latendresse and Fleischmann TOI charts are expressed as a percentage of team ice-time, to demonstrate a player’s contribution to team results; the Leafs’ TOI charts are expressed as a percentage of the top defenseman’s ice-time, to give a clearer sense of the changes in team depth. The Leafs’ chart demonstrates Kaberle and fellow traded Leaf Francois Beauchemin left a large gap in the team’s even-strength and powerplay minutes. While the even-strength time was transferred over to Carl Gunnarsson and Keith Aulie fairly quickly, a variety of players (including Gunnarsson, Matt Lashoff, and Luke Schenn) were tried in place of Kaberle and Beauchemin on the powerplay.

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NHL trades frequently involve a shake-up as teams try to fix or fill issues they see in their roster. While it’s interesting to examine the asset-for-asset element of the midseason swap, using devices like TOI% and TOI charts can give us an interesting, multi-layered picture of how the trade affects the player and both teams, short and long-term.
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THN Analytics: Visualizing the Trade