Since the very first 2019-20 KHL game, the League is using smart technology to bring the audience a vast new range of stats. The fans already know the microchips in pucks and jerseys, and now it's time to show what this technology can do. KHL.ru illustrates the most exciting data on teams and players gathered by the new technology after the first 54 days of the regular season.

Let's start with something that most of the fans already know - starting from the 2019-20 season, data gathered from smart microchips are viewable during the text broadcasts on the KHL.ru website. Fans can now get information in real-time, for example, about the players' top speed and distance run, or the teams' puck control duration. Soon, there will be new stats available. The most attentive fans, however, may have noticed them already during the TV broadcasts.

So, what did the smart pucks tell about the players and teams?

Puck control

One of the most intriguing stat is how much time players spend with the puck. As you can see from the top-5, the players who most often play the puck are playmakers like SKA's Vladimir Tkachyov or Salavat Yulaev's Linus Omark, or offensive defensemen whose task is to bring the puck forward.

 

Player

Club

Time

1

Vladimir Tkachyov

SKA

43:45

2

Charles Genoway

Torpedo

42:44

3

Marc-Andre Gragnani

Dinamo Minsk

42:37

4

Linus Omark

Salavat Yulaev

41:36

5

Mikko Lehtonen

Jokerit

36:49

Not surprisingly, the same five players are the top-5 ranked in another stat, the distance run with the puck. But if Tkachyov was the first listed in puck control time, a defenseman leads the puck here – Charles Genoway, the only player in the League to have surpassed the 15 km mark.

 

Player

Club

Distance with a puck, m

1

Charles Genoway

Torpedo

15214

2

Vladimir Tkachyov

SKA

14791

3

Marc-Andre Gragnani

Dinamo Minsk

13860

4

Linus Omark

Salavat Yulaev

13531

5

Mikko Lehtonen

Jokerit

11873

Average distance run

Having run more than 15 km with the puck is a fantastic feat, but a player spends most of the game without it. To date, more than a dozen players have surpassed the 100 km mark, but comparing total figures would be inaccurate due to the different numbers of played games.

However, average distance run is an appropriate measuring stick, and here Dinamo Minsk's blueliner Marc-Andre Gragnani takes the lead. By the way, in the recent game against Barys, he hit a record-breaking 6,584 meters.

 

Player

Club

Avg distance per game, m

1

Marc-Andre Gragnani

Dinamo Minsk

5684,3

2

Drew Shore

Dinamo Minsk

5381,7

3

Vyacheslav Voynov

Avangard

5168,5

4

Kirill Semyonov

Avangard

5065,9

5

Charles Genoway

Torpedo

5061,5

Average speed

High speed is a crucial ingredient for success for both teams and players. That's why it's important to check who has the most impressive figures in this stat. Here, rather than the peak value, it's fundamental to track the average speed recorded along the whole first portion of the regular season. The new technology can track this data. Quite surprisingly, the fastest player in the League so far is Vityaz's Evgeny Mons, who got on top of the rankings only by a hair over last week's best rookie, Torpedo's Sergei Goncharuk.

 

Player

Club

Avg speed, km/h

1

Evgeny Mons

Vityaz

16,6

2

Sergei Goncharuk

Torpedo

16,5

3

Saku Maenalanen

Jokerit

16,4

4

Svyatoslav Grebenshchikov

Vityaz

16,4

5

Georgy Belousov

Avtomobilist

16,2

Passing accuracy

The last category concerns the most accurate passes. Only players with at least 400 pass attempts were taken into consideration to determine the ultimate champion. After the counting, SKA's Swedish defenseman David Rundblad was crowned, with a passing accuracy of 88,6%.

 

Player

Club

Passes

% accuracy

1

David Rundblad

SKA

723/816

88,6

2

Marc-Andre Gragnani

Dinamo Minsk

840/953

88,1

3

Philip Larsen

Salavat Yulaev

644/732

88,0

4

Jakub Nakladal

Lokomotiv

426/502

84,9

5

Mikko Lehtonen

Jokerit

558/658

84,8

The best playmakers in the League, Tkachyov and Omark, can boast a passing accuracy of 80,3% (633/788) and 77,8% (551/708), respectively.

The data discussed in this article is just a small portion of what the new smart pucks technology can show the public. This data not only allows the fans to gather more information on their favorite players. Teams can also leverage the system for free.

KHL.ru will keep on presenting its fans with new and exciting data.

Alessandro Seren Rosso Alessandro Seren Rosso
KHL press office KHL press office
exclusive for khl.ru

Related clubs

Avangard (Omsk) Avangard (Omsk)
Vityaz (Moscow Region) Vityaz (Moscow Region)
Dinamo (Minsk) Dinamo (Minsk)
Dinamo (Riga) Dinamo (Riga)
Jokerit (Helsinki) Jokerit (Helsinki)
Lokomotiv (Yaroslavl) Lokomotiv (Yaroslavl)
Salavat Yulaev (Ufa) Salavat Yulaev (Ufa)
SKA (Saint Petersburg) SKA (Saint Petersburg)
Torpedo (Nizhny Novgorod Region) Torpedo (Nizhny Novgorod Region)

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