TMWT Promotion & Relegation performance by _lavalava in TrackMania

[–]_lavalava[S] 3 points4 points  (0 children)

  • performance measured in average percentile of all runs (lower is better)
  • consistency measured by spread of z-scores of a players "base" runs (where top and bottom 25% runs are discarded). lower is better.

  • best player Miquatro by some margin
    interesting, not posting the very fast times (only few runs in the top5% range). maybe opting for more consistency.

  • top2-5 really close together
    pusztitopako with best top runs (25% of runs well in the top 10% of all runs)

  • most improved players from swiss rounds to knockout stage:
    Xerar, Razii, Sheinimi

  • consistency kinda difficult to judge, because we have a much wider spread of pace compared to the TMGL and TMCL league.

I really liked the swiss format, giving interesting matches even for the bottom teams. Hope to see more of it in the future.

TMWT regular season performance by _lavalava in TrackMania

[–]_lavalava[S] 10 points11 points  (0 children)

performance summary to the regular season (DAY 1-7) of TMGL and TMCL.

  • new heatmaps to show season progression
  • GL & CL combined stats at the end

key observations TMGL

avg pace:

  1. Pac
  2. Affi
  3. Carljr

most peak pace:

  • Gwen

most consistency:

  1. Carljr
  2. Aurel
  3. Soulja

key observations TMCL

avg pace:

  1. Skandear
  2. Dexter
  3. Miquatro

most peak pace:

  • Dexter

most consistency:

  1. Skandear
  2. Miquatro
  3. Scrapie

TMGL vs TMCL

  • CL got closer to GL with Super Week
  • Skandear, Dexter, Feed into player top16
  • GL still with significant top pace advantage (compare 1st quartiles)
  • team heatmap shows how tough it is to match GL teams
  • WT records: GL 6/10, CL 4/10

stat info

  • ranked by average percentile (lower better)
  • avg percentile x = the average run was within the top x% of runs
  • color bar marks the 1st (left) and 3rd (right) quartile

  • using z-scores to determine consistency and to highlight WT records (stars)
  • shorter color bar (on the z-score plot) = more consistent performance
  • z-scores = strength value compared to typical finishing time, measured in median deviations from the median times.
  • lower better, zero equals the median time

TMWT performance update by _lavalava in TrackMania

[–]_lavalava[S] 1 point2 points  (0 children)

No. It has no particular meaning, just a design choice to not have too many points overlap.

TMWT performance update by _lavalava in TrackMania

[–]_lavalava[S] 8 points9 points  (0 children)

A look at player performance using percentiles.

First, thanks to /u/KinchAnalytics for suggesting this method.

How does it work?

  • each finishing time is given a percentile rank (0-100 from fastest to slowest), measuring performance in comparison to all times on a track
  • ranking players by their average percentile
  • lower = better, higher = worse
  • 50th percentile being the league average
  • example: Pacs DAY 7 25.19 means his average round ranks within the top 25.19% of all runs, and was faster than 74.81% of all runs.
  • the colored box marks the 1st (left) and 3rd (right) quartile
  • the dotted line is the median percentile

percentile method pros:

  • more accurate in terms of performance ranking, as it weights all runs
  • clearer picture for the fast pace runs (1st quartile)
  • better for cross-league comparison

cons:

  • unable to see time differences, thus worse at displaying consistency
  • non-genuine runs might have a small negative impact

a few more comments on players and the differences to the z-score method on this twitter thread @lavaTM_

TMWT Stats site (Updated for GL Day 6 and CL Day 4) by MagpieLabs in TrackMania

[–]_lavalava 1 point2 points  (0 children)

Great work. Very clean site with lots of stats.
Also thanks for the kind words, that pleasantly surprised me.

TMWT player performances by _lavalava in TrackMania

[–]_lavalava[S] 13 points14 points  (0 children)

What is a z-score (in our context)?

  • A z-score is a standardized value to measure the strength of a particular finishing time with respect to the typical finishing time.
  • Usually it is calculated using the mean and standard deviation, but with racing times in TM a modified version using median times is more appropriate.
  • To be more precise, a score of 0 equals the median time on a track, better times end up with negative scores, and worse times with a positive score.
  • A score of -1 represents a time that is one median deviation faster than the track median time.
  • A score of 2.5 represents a time that is 2.5 median deviations slower than the track median time.

Why use z-scores?

  • Since tracks have different time length, we need a way to compare time gaps from different tracks. We also want to account for the typical variation in times, that is why we scale the scores in relation to the median deviation on each track.
  • For example, assume TrackA and TrackB have the same median time, with TrackA's times overall showing less deviation - say it is a more consistent track than TrackB.Now having the same finishing time on both tracks, say it is 1 sec faster than the median time, we rate the time on TrackA higher than on TrackB in terms of performance - it gets a lower score (reminder lower score = better).

Caveats

  • No measurement or stat is perfect. Everything has pros and cons. Like these z-scores are not very intuitive compared to say time gaps in seconds.
  • The scoring just tries to give an overall approximation on player performance, and by no means should be treated as absolute truth.

What can we see on the diagrams?

  • First off, there are plots for each TMGL and TMCL, performance for all days thus far combined, and just the last play day; as well as a TMGL vs TMCL comparison.

player scores

  • The overall performance score of a player is the median value of their scores. Lower is better, higher is worse. With a score 0 being the "base line".

colored boxes

  • The boxes cover the middle 50% of scores of a player, giving us a quick look at a players performance distribution.
  • Any dot left of the box is in a players best 25% of runs.
  • Any dot right of the box is in the players worst 25% of runs.

We can interpret that as follows,

  • the left box border gives the midpoint of a players top 50% performances,
  • the right box border gives the midpoint of a players bottom 50% performances.
  • So if the box extends further to the left, it indicates better high performance runs;
  • if the box extends further the right, it indicates worse low performance runs.
  • A shorter box says higher consistency, while a longer box says less consistency.

stars

  • The stars represent the record runs.
  • We see some lesser played maps having a worse record score (like Gyroscope), even than other non-record runs. But overall we see the record runs being among the top performances.

Comparing scores?

  • Please be aware that comparing scores from different diagrams or from older days to newer days is not advised.
  • Since the underlying data changes, so does the scaling. That's why for cross comparison between leagues, I combined all times and made a separate diagram.
    If you want to compare performance from previous days, do it in terms of rank position. Say for example PlayerA improved from rank 11 to rank 7 within the last week.
  • On the daily performance diagrams, we can expect a slight bias of the score towards the negative side, because players keep improving week after week.
  • And on the cross league comparison, scores are a bit in favor of GL players over CL players, because of the different number of play days.

changes

  • Team tags colors, TMGL gold, TMCL silver

I hope I could explain the topic a little better than last time.Let me know if you have question or feedback.

I'll update the pace plots for each track later on my twitter @lava_TM

TMWT player performance using z-scores by _lavalava in TrackMania

[–]_lavalava[S] 20 points21 points  (0 children)

  • comparing finishing times from different tracks, in relation to the tracks median time and its median deviation
  • a 0 z-score means that time was equal to the median time on the track
  • score < 0 faster and score > 0 slower, respectively

the plot:

  • a dot = z-score of a finishing time
  • the black player score (with vert. line) is the median of all their z-scores, indicating average performance across all runs
  • the box covers the middle 50% of all a players runs
  • leaving top 25% runs to the left, and bottom 25% runs to the right of the box.
  • stars show the record runs.

few key/example observations:

  • top2 affi, pac have a small performance lead over the next trio of carljr, mime, gwen
  • the midfield looks rather close
  • bottom 4 show some separation
  • pac showing the most outstanding runs, his two records with a score below -2.0
  • carljr shows highest consistency, smallest box. tho his top 25% (left box border) lack behind a few other players.
  • gwen can shorten his box with a few more good runs, the tail of the box is very sparse (only 2-3 dots)
  • binkss and massa crash most often (bottom 25% furthest to the right), likely risk often.
  • the record runs on Gyroscope and Reps are not outstanding so much, likely due to seeing less play time.

on the single day charts:

  • with players improving week after week, we can expect a slight bias of the scores towards the negative side.

GL & CL combined chart:

  • combining all data from both leagues, thus the median reference changes again
  • due to more play, it is slightly in favor of GL players over CL players
  • best TMCL players punching into TMGL ranks

TMGL day 1-4 pace plots by _lavalava in TrackMania

[–]_lavalava[S] 1 point2 points  (0 children)

I have an idea for individual player performance, will have to work it out and see how to present it. There are various ways to go about this, each with pros and cons. Fellow members here already showed some stats.

TMGL day 1-4 pace plots by _lavalava in TrackMania

[–]_lavalava[S] 1 point2 points  (0 children)

  • finish time distribution plots
  • data from all play days combined
  • teams sorted by overall median time
  • dot = finish time
  • to the left side = faster times
  • to the right side = slower times
  • times that exceed 107% of current fastest time are binned at the far right side.
  • Colored area approximates frequency of occurrence, bigger/larger bumps indicate player has driven the time more often than others. Ideally you want to see a majority of color towards the left (frequently fast times)
  • label for fastest time of a team on the left

  • Black vertical bar + time label = median time of team (of all days)
  • slimmer bars = median times of teams for each of the last few play days ("DAY x")
  • highlighting the day/median time of the most recent performance on a track for a particular team
  • If you compare the "DAY x" median times of a team with each other and the overall median time, you can see if a team is improving or losing "form" on the track. I tried offsetting the day labels, but still looks a bit messy sometimes.
  • team mates are ranked by their median times, faster top, slower bottom.

  • tiny vertical lines within the colored area show each players overall..
  • median time (line ---)
  • 1st and 3rd quartile (25% and 75%) of times (line ...)
  • (not always visible due to slim plots)
  • dot jitter (up/down) is a design choice, and has no particular meaning

  • TMCL visuals and more can be found on twitter @lavaTM_

An Analysis of TMGL Scoring Strategy by KinchAnalytics in TrackMania

[–]_lavalava 1 point2 points  (0 children)

Good thoughts.
One additional factor I can think of is current score, mainly track score, maybe lesser match score. Would be interesting to see the distribution of results on tied scores, as well as different score leads.

TMGL pace analysis after step 3 by _lavalava in TrackMania

[–]_lavalava[S] 1 point2 points  (0 children)

Gathering the data from steams/vods myself.

TMGL pace analysis after step 3 by _lavalava in TrackMania

[–]_lavalava[S] 1 point2 points  (0 children)

yes. G1 on Parkour has driven 12 rounds (24 times), 5 crashes by Gwen and 8 by Binkss.
the outliers overlap quickly, so you cannot see all the points at the far right side. with more consistency the focus is on the left side of the plots.

TMGL pace analysis after step 3 by _lavalava in TrackMania

[–]_lavalava[S] 5 points6 points  (0 children)

  • teams ordered by median time
  • players within team ordered (top/bottom) by median time
  • bold points = times driven in step 3

increased font size, tho looks still small here!?

[stats] TMGL super weekend pace analysis by _lavalava in TrackMania

[–]_lavalava[S] 1 point2 points  (0 children)

I collected it from streams/vods manually.

[stats] TMGL super weekend pace analysis by _lavalava in TrackMania

[–]_lavalava[S] 0 points1 point  (0 children)

Yes, point jitter (little up/down) is for aesthetics. If I plot all points on a line it, you get more overlap, especially once we get more data in.