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Speed + corrections on calculations
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@BrennanB
BrennanB committed Sep 13, 2024
1 parent 21a25ac commit bbb5e63
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Showing 2 changed files with 39 additions and 37 deletions.
8 changes: 6 additions & 2 deletions ranked/templates/ranked/player_info.html
View file
Original file line number Diff line number Diff line change
Expand Up @@ -91,14 +91,16 @@ <h5 class="mb-0">
<tr>
<th>Player</th>
<th>Win Rate</th>
<th>W-T-L</th>
<th>Total Matches</th>
</tr>
</thead>
<tbody>
{% for player_with in players_with %}
<tr>
<td>{{ player_with.player__username }}</td>
<td>{{ player_with.username }}</td>
<td>{{ player_with.win_rate|floatformat:2 }}%</td>
<td>{{ player_with.wins }}-{{ player_with.ties }}-{{ player_with.losses }}</td>
<td>{{ player_with.total_matches }}</td>
</tr>
{% endfor %}
Expand All @@ -124,14 +126,16 @@ <h5 class="mb-0">
<tr>
<th>Player</th>
<th>Win Rate</th>
<th>W-T-L</th>
<th>Total Matches</th>
</tr>
</thead>
<tbody>
{% for player_against in players_against %}
<tr>
<td>{{ player_against.player__username }}</td>
<td>{{ player_against.username }}</td>
<td>{{ player_against.win_rate|floatformat:2 }}%</td>
<td>{{ player_against.wins }}-{{ player_against.ties }}-{{ player_against.losses }}</td>
<td>{{ player_against.total_matches }}</td>
</tr>
{% endfor %}
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68 changes: 33 additions & 35 deletions ranked/views.py
View file
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
from django.shortcuts import render, HttpResponseRedirect
from django.db.models import Max, Min, F, Q, Count, ExpressionWrapper, FloatField, Case, When, Value
from django.db.models import Max, Min, F, Q, Count, ExpressionWrapper, FloatField, Case, When, Value, IntegerField, Sum
from django.utils import timezone
from datetime import datetime, timedelta
import math
Expand Down Expand Up @@ -122,23 +122,22 @@ def player_info(request, name, player_id):
Q(blue_alliance__in=matches.filter(blue_alliance=player.player))
).exclude(id=player.player.id).distinct()

players_with_stats = []
for played_with in players_with:
matches_together = matches.filter(
(Q(red_alliance=player.player) & Q(red_alliance=played_with)) |
(Q(blue_alliance=player.player) & Q(blue_alliance=played_with))
)
total_matches = matches_together.count()
wins = matches_together.filter(
(Q(red_alliance=player.player) & Q(red_alliance=played_with) & Q(red_score__gt=F('blue_score'))) |
(Q(blue_alliance=player.player) & Q(blue_alliance=played_with) & Q(blue_score__gt=F('red_score')))
).count()
win_rate = (wins / total_matches * 100) if total_matches > 0 else 0
players_with_stats.append({
'player__username': played_with.username,
'total_matches': total_matches,
'win_rate': win_rate
})
players_with_stats = players_with.annotate(
total_matches=Count('red_alliance', filter=Q(red_alliance__in=matches)) +
Count('blue_alliance', filter=Q(blue_alliance__in=matches)),
wins=Count(Case(
When(Q(red_alliance__in=matches.filter(red_alliance=player.player), red_score__gt=F('blue_score')), then=1),
When(Q(blue_alliance__in=matches.filter(blue_alliance=player.player), blue_score__gt=F('red_score')), then=1),
output_field=IntegerField(),
)),
ties=Count(Case(
When(Q(red_alliance__in=matches) | Q(blue_alliance__in=matches), red_score=F('blue_score'), then=1),
output_field=IntegerField(),
)),
).annotate(
losses=F('total_matches') - F('wins') - F('ties'),
win_rate=(F('wins') * 2 + F('ties')) * 100.0 / (F('total_matches') * 2)
).values('username', 'total_matches', 'wins', 'ties', 'losses', 'win_rate')

players_with_stats = sorted(players_with_stats, key=lambda x: (-x['win_rate'], -x['total_matches']))

Expand All @@ -148,23 +147,22 @@ def player_info(request, name, player_id):
Q(blue_alliance__in=matches.filter(red_alliance=player.player))
).distinct()

players_against_stats = []
for played_against in players_against:
matches_against = matches.filter(
(Q(red_alliance=player.player) & Q(blue_alliance=played_against)) |
(Q(blue_alliance=player.player) & Q(red_alliance=played_against))
)
total_matches = matches_against.count()
wins = matches_against.filter(
(Q(red_alliance=player.player) & Q(red_score__gt=F('blue_score'))) |
(Q(blue_alliance=player.player) & Q(blue_score__gt=F('red_score')))
).count()
win_rate = (wins / total_matches * 100) if total_matches > 0 else 0
players_against_stats.append({
'player__username': played_against.username,
'total_matches': total_matches,
'win_rate': win_rate
})
players_against_stats = players_against.annotate(
total_matches=Count('red_alliance', filter=Q(red_alliance__in=matches)) +
Count('blue_alliance', filter=Q(blue_alliance__in=matches)),
wins=Count(Case(
When(Q(red_alliance__in=matches.filter(blue_alliance=player.player), red_score__gt=F('blue_score')), then=1),
When(Q(blue_alliance__in=matches.filter(red_alliance=player.player), blue_score__gt=F('red_score')), then=1),
output_field=IntegerField(),
)),
ties=Count(Case(
When(Q(red_alliance__in=matches) | Q(blue_alliance__in=matches), red_score=F('blue_score'), then=1),
output_field=IntegerField(),
)),
).annotate(
losses=F('total_matches') - F('wins') - F('ties'),
win_rate=(F('wins') * 2 + F('ties')) * 100.0 / (F('total_matches') * 2)
).values('username', 'total_matches', 'wins', 'ties', 'losses', 'win_rate')

players_against_stats = sorted(players_against_stats, key=lambda x: (-x['win_rate'], -x['total_matches']))

Expand Down

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